The Black Friday-ification of the 4th of July: what a decade of email data told us about America’s 250th

Though the final numbers aren’t in yet, America’s 250th anniversary is shaping up to have been the most commercially significant Independence Day in the nation’s history. 

To understand how brands actually approached the holiday – how they tackled the tensions around patriotic language at a time when the country is increasingly divided – Jacquard analysed 368,000 promotional email subject lines sent by major B2C brands between 2016 and 2025, in partnership with Ariela Nerubay Turndorf, Adjunct Professor of Digital Marketing and Multicultural Marketing at the University of Southern California. 

The results revealed a clear pattern of a national holiday being steadily absorbed into the retail calendar – and a tension regarding how brands embrace the sentiment behind it. 

Patriotic language has nearly tripled in under a decade

Core patriotic references – mentions of America, the 4th of July, freedom, and red, white and blue – have grown more than 25 times since 2016, with 2025 already the highest rate on record. The jump from 2024 to 2025 alone was 116%, the largest single-year increase in the dataset.

The 4th of July accounts for roughly 60% of all patriotic language across the dataset. During the core promotional window of 25 June to 7 July, brands are 50 times more likely to use patriotic language than at any other point in the year, with June standing out as the peak month as brands build momentum ahead of the holiday itself.

The promotional window keeps getting longer

Phrases like “Epic 4th of July Sale” now appear as early as June, having previously been concentrated in the final days before the holiday. Based on the trajectory of the last few years, promotional activity around Independence Day could now realistically begin as early as May.

Memorial Day is following a similar path. It’s grown from essentially nothing before 2019 into the second-largest patriotic commercial moment, now rivalling Labor Day as a major marketing occasion in its own right.

Words, not images

Despite years of investment in patriotic language, patriotic imagery is almost entirely absent. Across all 368,000 subject lines:

• The US flag emoji appeared fewer than 10 times
• The Statue of Liberty emoji appeared just five times
• The eagle emoji didn’t appear at all until 2024, tied to a Presidents’ Day campaign

The data also points to a clear preference for celebratory rather than ideological patriotism. References to BBQs, cookouts, fireworks and the backyard have grown steadily, while explicitly political language remains rare. Brands appear to have gravitated, largely without coordination, toward the more inclusive end of the patriotic spectrum. 

What this means for the 250th

Ahead of the 250th, our CPO, Toby Coulthard, said: “What we’re seeing is the Black Friday-ification of Independence Day – a national holiday that has been steadily absorbed into the commercial calendar.”

Ariela Nerubay Turndorf added a note of caution for brands tempted to lean harder into imagery for the sake of it: “What this data reflects is a broader tension in American marketing – brands want to tap into patriotic sentiment, but they’re cautious about what that sentiment means to different communities right now. Defaulting to transactional language like ‘5th of July Sale’ is the path of least resistance. The brands that will stand out around the 250th are those willing to engage with American identity in a more considered, culturally nuanced way.”

The takeaway

The data suggests two things are true at once: patriotic marketing is intensifying, and it’s doing so through transaction rather than meaning. Brands are zeroing in on consumer interest in the holiday rather than necessarily on the sentiment behind patriotism itself.

What actually happens when an AI inbox compresses your email?

An AI summary keeps facts and drops texture. Give a model 150 words of carefully voiced copy and it will reliably preserve what's on offer and when it ends — and just as reliably discard the rhythm, the wit and the phrasing that made the message yours.

That has two consequences. First, if your offer isn't stated plainly, it can vanish entirely: a teaser subject line like "Something special is waiting…" summarises to nothing at all. Second, every brand that writes vaguely ends up sounding identical after the squeeze — the model replaces your voice with its own house style.

The one line an AI shows before anyone opens is now the most valuable real estate in the message. Most brands don't even know what theirs says.

Why does this matter beyond the inbox?

The same dynamic plays out in AI search. When a shopper asks an assistant for "the best laptop deal this weekend", the answer names one or two brands and describes them in a sentence. Whether your brand gets named — and whether the description sounds like you or like a category average — depends on the language you've published everywhere, not just in one email.

This is measurable. You can score how often assistants mention a brand, how favourably they describe it, and which published phrases earn the citation. We call this AI visibility, and it behaves like SEO did in 2005: most brands ignore it, a few compound an advantage.

How do you write language that survives?

Three structural habits make more difference than any amount of polish:

1. Lead with the offer, in numbers. "Up to 40% off for 24 hours" survives any summariser. "Don't miss our biggest event of the season" survives none of them.
2. Make the brand the subject of the sentence. Models echo grammatical structure — copy that says "Sephora has free next-day delivery on orders over £25" gets the brand named in the answer; copy that buries the brand in a footer doesn't.
3. Test the compressed version, not just the original. Before sending, summarise your own message with the models your customers' inboxes run. Treat the one-line output as a first-class deliverable — write, test and optimise it the way you would a subject line.

None of this means flattening your voice into bullet points. It means knowing which parts of a message carry the brand and which parts carry the facts, and making sure both survive independently. That's a writing discipline — and it's exactly the kind of constraint that's better enforced by a system than a style guide PDF nobody opens.

Where to start this week

Pull your last ten campaigns, run each through a current model with the prompt "summarise this email in one line", and put the outputs in a spreadsheet next to your subject lines. You'll know within an hour whether your offers are surviving and whether anything in the summaries still sounds like you. If the answer is no — that's the brief.

Why we'll be there

Movable Ink and Jacquard solve two halves of the same problem. Movable Ink personalises the creative — every pixel assembled per person at the moment of open. Jacquard writes and optimises the language — every line on-brand, tuned to the reader and to the number it should move. Put them together and a single campaign can be individually relevant and unmistakably yours, at enterprise scale.

If you're running both — or wondering whether you should be — Think Summit is the right room for that conversation.

What we're bringing

• Live brand reads. Give us your website and watch Jacquard map your tone of voice, score your AI visibility, and write your first subject lines on the spot — the same analyser that runs on our homepage.
• The brand model, hands on. See how approving content and sending campaigns grows the on-brand and performance regions of your language space — and why the overlap is where your best content lives.
• AI visibility in practice. How your brand reads in AI inboxes and AI search answers today, and how to shape it.

Find us there

If you'd like a slot rather than a hallway chat, book a demo before the event and mention Think Summit — we'll pin time in New York. Otherwise, look for the Jacquard team on the floor: we're the ones asking what your brand sounds like.

The future of the copywriter: Working to a deeper understandings

The story so far

There’s a version of the AI story in which the copywriter disappears. It goes like this: the machine creates competent marketing copy in seconds, and the human who used to write it becomes redundant. 

As a story, it makes a kind of sense. But, crucially, it’s wrong. What’s actually happening is more interesting, more nuanced – and, for the copywriters paying attention, it’s much more promising. 

For most of its history, copywriting has involved two very different kinds of work. The first is strategic. It’s based around understanding a brand’s voice, its customers, and what a piece of language is trying to achieve. The second is mechanical – it’s to do with actually producing the words, editing them, formatting them, and repeating that process across however many variants a campaign requires. These two kinds of work have always been part of the same job description, but they’re not the same thing. AI is now capable of handling the second. The first remains human.

What’s copywriting for, anyway? 

The distinction matters because it reframes what a copywriter is actually for. No copywriter’s value ever really resided in their ability to type quickly or to produce grammatically correct sentences at volume. A good copywriter isn’t assessed by their words-per-minute on a keyboard. Instead, the value resides in their understanding of what those sentences are supposed to do. And, with AI handling generation at scale, that judgement – as to voice, or intention – only becomes more valuable. 

The role, in practice, shifts from producing content to directing the system that produces it. The copywriter sets the brand guardrails, evaluates the outputs, identifies what’s working and what isn’t, and ensures that a voice built over years of careful work remains intact across thousands of personalised messages. That is a harder and more sophisticated job than producing those messages manually would have been. It requires expertise, built up over years of experience, and bolstered by a deep understanding of cultural and linguistic nuances. 

This shift has a practical consequence that teams are only beginning to reckon with. The content demands placed on modern marketing operations have grown well beyond what any human writing team could manually meet. Human copywriters, however talented and numerous, cannot scale to meet this volume.

The problem at hand

The temptation is to throw a generic AI tool at the problem. But this introduces a different failure mode: if everyone is generating content from the same foundational model, trained on the same public data, the resulting copy exhibits the same patterns and the same cadences. Consumers have grown adept at recognising it. The volume problem gets solved while a differentiation problem is created in its place.

What the best-positioned teams are doing now is something more considered. They are using AI that has been trained specifically on their brand’s own linguistic patterns and historical performance data – systems that can generate thousands of variants whilst maintaining the voice that makes a brand distinct. The copywriter, in this model, is the person who built and continues to shape those guardrails. Their expertise is embedded in the system, rather than expressed through individual pieces of output.

Where next?

The copywriters who will struggle in the next few years are those who define their role by the mechanical half of it. Those who understand their value as strategic and editorial — the people who know what good looks like, and can build the infrastructure to produce it at scale — are in a stronger position than they might currently believe.

The machine needs directing. And that remains – and will remain – a human job.

Earlier this year, we launched Adaptive Generation Strategies — an update to how Jacquard searches for high-performing language. It introduced AI-driven feedback loops that let our Optimisation campaigns learn from live performance, your human control, and your team’s approval decisions — and adapt generation in response.

Today, we’re extending that capability to Contextual Messaging (CM).

It’s a bigger step than it sounds. In Optimise, a campaign learns about one audience. In CM, a single campaign runs across many contextual categories at once — different customer segments, behaviours, or moments, each with its own mini-landscape of what works. Until now, each of those categories largely had to learn on its own. From today, they learn together.

A search space that multiplies with every category.

Contextual Messaging already does something distinctive. It uses a contextual multi-armed bandit (CMAB) to match the right variant to the right customer context — so the language someone sees is shaped by who they are and what they’re doing, not just what the campaign is about.

But this creates a harder version of the search problem we described in our last update. Every contextual category is its own terrain of peaks and valleys. Multiply that by the number of categories in a campaign, and the cost of learning from scratch in each one adds up fast — especially in “cold start” categories, where the CMAB hasn’t yet seen enough engagements to act confidently. With this update however, learnings from one category will transfer and accelerate all others.

Meta-analysis across categories.

The new capability runs a meta-analysis across all contextual categories in a campaign. It deconstructs and segments the linguistic and contextual cues shared by high-performing language — and, just as importantly, by low-performing language — right across the campaign.

Those patterns become seeds for new content generation. Our upgraded generation process uses them to produce a diverse set of variants with targeted coverage of the strategies we already know are working. We also draw on your human control to extend the information and linguistic coverage beyond what the brief alone provides.

The effect is that a winning pattern discovered in one category doesn’t stay there. It informs generation for the rest of the campaign — including categories still waiting on their first wave of engagement data. What one part of the campaign learns, the whole campaign benefits from.

Language intelligence, language performance, customer context.

Adaptive Generation Strategies in Optimise showed what was possible when language generation could respond to real-world performance. Extending it to CM brings together the three things that matter most for genuine 1:1 messaging at scale:

• Language intelligence — generation that understands brand voice, intent, and creative strategy.
• Language performance — feedback loops that learn from what actually works in-market.
• Customer context — the CMAB matching the right language to the right moment.

Individually, each is useful. Together, they compound. Every impression becomes a signal that improves generation. Every category strengthens every other. Every campaign you run makes the next one start from a better position.

This is the direction the platform is heading: less a tool you use, more a system that learns — across language, across audience, across time.

Available today.

The improvements to Contextual Messaging take effect immediately for both live campaigns and newly set-up CM campaigns. No user action is needed. Existing campaigns will begin benefiting from cross-category learning on their next generation cycle.

Book a demo to see what Jacquard can do for your 1:1 messaging.

Adaptive Generation Strategies for Contextual Messaging is available today to all customers using Jacquard’s CM module.

Jacquard Valentine’s Report 2026: Your Customers Are Sick of “Love” 2026 Marketing Predictions

Every year, as Valentine’s Day draws closer, brand inboxes fill up with the same things: heart emojis, the word “love”, a flash sale, a countdown timer. And every year, consumers largely ignore them. New research from Jacquard – drawn from over 61,000 email subject lines sent during the Valentine’s period between 2015 and 2025 – reveals just how much is being left on the table when brands reach for the obvious.

The person, not the occasion

The single most instructive finding in the data is also one of the simplest. Subject lines that refer to “your Valentine” – the person receiving the gift – outperform those that reference “Valentine’s Day” – the event – by 22%. If we drill down further, “Valentine” as a noun for a person drives a 10.8% uplift, while “Valentine’s” as a possessive tied to the holiday causes an 11.1% drop.

People buy gifts for someone specific, as opposed to buying solely for a date in the calendar. Messaging that acknowledges that human relationship, rather than the retail occasion, consistently resonates more. The linguistic shift is small, but the performance gap is significant.

Love language

Surprisingly, “love” – arguably the defining word of Valentine’s Day – actively reduces email engagement by 6.6%. “Heart” drops performance by 15.6%. “Sweet” is down 14.3%. Meanwhile, “adore” drives a 16.9% uplift, and “romantic” an 11.7% increase.

Generic romantic vocabulary has been deployed so heavily and so uniformly across Valentine’s campaigns that it has essentially lost its charge. More specific, less reflexive emotional language cuts through precisely because it feels considered. The data rewards brands that put genuine thought into their word choices over those that reach for the nearest cliché. 

The Galentine’s effect

Valentine’s Day is no longer a holiday that belongs exclusively to romantic couples, and the email data reflects this clearly. “Friend” drives a 10.9% uplift in engagement, whilst “partner” causes a 4.1% decline.

With 25% of consumers in 2025 planning to mark Galentine’s Day, campaigns oriented around friendship are reaching a genuinely large audience. Brands that continue to default to couple-focused messaging are not only excluding a significant portion of their customer base – they’re also producing content that, according to the data, performs worse.

Practical messaging, unpushy

The highest-performing word in the entire dataset is not a romantic term at all. “Shipping” drives a 28.3% engagement uplift. “Free” and “offer” also perform well. By contrast, “shop” causes a 21.3% decline, “save” is down 10.3%, and “limited” drops performance by 18.8%.

Valentine’s Day is a deadline-driven purchase. Consumers want to know whether a gift will actually arrive in time – not to be pressured into a transaction they’ve already decided to make. Answering that practical question outperforms manufactured urgency by a considerable margin.

What it all points to

The findings point toward a consistent underlying principle: Valentine’s Day shoppers respond to language that treats them as thoughtful people rather than targets to be converted. Every year, inboxes grow more crowded, and competing for attention gets harder. Reverting to simple, predictable language no longer cuts it. Small, thoughtful linguistic choices, made deliberately, are what separate the brands that cut through from those that don’t.

CAA Club Group (CCG) serves more than 700,000 members and wanted to increase engagement across its weekly email campaigns.

The team aimed to better align subject-line language with evolving member preferences across merchandise, travel, rewards, and newsletter communications.

The challenge:

CAA Club Group (CCG) wanted to increase engagement across its weekly email campaigns and better
align subject-line language with the evolving preferences of its 700,000 members.

The solution:

By partnering with Jacquard, CCG used AI-powered language testing across its merchandise, travel,
rewards, and newsletter segments to identify the tones and styles that resonate most—integrating seamlessly with Salesforce Marketing Cloud.

Impact

Jacquard outperformed human-written subject lines 97% of the time, driving major engagement gains,
including a 26% average click-rate uplift and nearly one million incremental opens.

“AI-generated content has given us a data-driven way to drive real engament with our email marketing.”

Avidian De Lara
CAA Club Group

With its email marketing stuck in a manual testing bottleneck, insurance

comparison platform Confused.com turned to Jacquard for AI-powered
language optimisation at scale.

The context:

Confused.com is a UK-based insurance comparison platform serving millions of customers across motor, home, and van insurance products. Despite having sophisticated audience segmentation and decisioning engines, the company faced a critical challenge: scaling personalised content to match the granularity of its data capabilities.

The challenge:

Confused.com was hampered by a fundamental scalability problem in its email marketing operations. While the platform possessed incredibly sophisticated decisioning engines capable of segmenting audiences down to the individual level, it was still sending the same handful of generic messages to millions of customers.

The core issue was operational and technical. With a small team of copywriters responsible for millions of emails across multiple insurance products, and with each conversion representing hundreds or thousands of pounds in lifetime value, traditional manual A/B testing simply couldn’t deliver meaningful personalisation at scale. Testing five subject line variations over a fortnight left enormous performance gains on the table.

The stakes are uniquely high in insurance marketing. When a customer receives a quote but doesn’t convert, it’s not just one lost sale but potentially years of lifetime value lost. In motor insurance alone – where Confused.com processes a high volume of quotes daily – even small improvements in conversion rates compound rapidly.

Confused.com needed a system that could test thousands of variations, identify successful linguistic patterns that consistently drive engagement, and apply those insights systematically across every campaign, trigger, and customer touchpoint.

The results:

The shift to intelligent content testing delivered immediate and substantial returns. By combining Jacquard’s platform with a systematic approach to language optimisation, Confused.com transformed its email marketing performance:

• 3.9% uplift in open rates and 12.3% uplift in click rates across all campaigns
• 11.7% increase in opens and 23.9% increase in clicks for newsletter campaigns
• 3.4% open rate uplift and 11.7% click rate uplift for automated trigger campaigns
• 2,000+ subject line variations tested across 75 trigger experiments and four broadcast campaigns – a scale no human team could replicate

The programme is now expanding to new campaign types, including welcome programmes and winback campaigns, with plans to apply insights beyond email to other channels and customer touchpoints.

Currys, one of the UK’s leading retailers, wanted to elevate its Black Tag Event with deeper customer insight and more personalised email campaigns.

The goal was to increase relevance and performance at scale, driving stronger engagement and revenue across its customer base.

The challenge:

Currys wanted to elevate its Black Tag Event with deeper customer insight and more personalized, performing email campaigns.

The solution:

By combining a large-scale segmentation study with Jacquard’s AI-generated language and Moveable Ink’s dynamic creative, Currys delivered personalized, data-driven messages across customer segments – boosting email frequency and relevance throughout the event.

Impact

The campaign achieved 42% uplift in opens, 93% uplift in clicks, and 102% increase in revenue. Optimizing abandoned-cart messages with Jacquard later added £2.5M in annual revenue.

“It’s been amazing to truly combine transactional marketing with real-time optimisation by integrating with Jacquard. It really shows the value of AI-powered event based messaging.”

David Pallant
Senior CRM personalization manager, Currys

Home Chef operates in a highly competitive meal-kit market, where capturing attention and re-engaging customers is critical to growth.

The team set out to improve the effectiveness of its email acquisition and reactivation campaigns through more impactful, data-driven messaging.

The challenge:

Home Chef needed to stand out in an increasingly competitive meal-kit market and improve performance across its email acquisition and reactivation campaigns.

The solution:

Jacquard’s AI-powered language optimization was used to test and refine email messaging at scale,
integrating directly with Salesforce Marketing Cloud to deploy high-performing subject lines and copy.

Impact

Over nine months, Home Chef saw 21% lift in open rates and 29% lift in click
rates, with clearer insights into what language resonates with customers.

“Jacquard allows us to refine our recipe for success when it comes to engaging customers with our content. We can also see the real-time results and tweak our tactics based on how our customers are responding.”

Lauren MacArtney
Senior Lifecycle Marketing Manager, Home Chef

P&O Cruises, a leading British cruise line, set out to improve email engagement by moving from instinct-led copywriting to a more data-driven approach.

The goal was to uncover new language styles that would consistently resonate with customers and drive stronger performance.

The challenge:

P&O Cruises wanted to move beyond gut instinct and diversify its marketing language with data-driven insight to improve email engagement.

The solution:

Using Jacquards AI-generated content, P&O Cruises tested and optimized subject lines and email
copy, discovering new styles and lengths that consistently outperformed human-written versions.

Impact

P&O Cruises achieved a 13% lift in open rates and 18% lift in clicks, unlocking stronger customer engagement and language that drives results.

“It’s endlessly fascinating how Jacquard manages to find patterns and trend that we just wouldn’t know by ourselves. Each quarterly report shows that our performance has improved. That and the fact that Jacquard’s copy always beat ours!”

Matthew Cooper
Email Marketing Manager, P&O Cruises

When Jacquard introduced Language****2, our LLM-based generation platform, we established it as the start of a journey, not the destination. Language2 unlocked the ability to generate on-brand, creative, and diverse copy at massive scale. But in the world of enterprise communication, the goal isn’t just to generate language, it’s to improve business results.

Today, we are releasing Adaptive Generation Strategies, a sophisticated update that changes how Jacquard navigates the vast landscape of language. By intelligently narrowing the search for what works, this release delivers higher-performing content faster, and reduces the cost of experimentation.

Navigating the Search Space

Think of the “search space” for language as a vast, multi-dimensional terrain. It represents every possible combination of words, tones, and styles available to your brand. Within this space, performance outcomes are not evenly distributed; there are peaks and valleys.

The challenge for any generation engine is the sheer size of this space. Exploring it without a map incurs an opportunity cost which can accumulate quickly. Every impression spent testing content that lands in a “valley” (low performance) may be a learning moment, but it’s also a testing cost that needs to be overcome.

To minimise this cost, we need to move from broad exploration to targeted precision. We need to identify where the highest performance peaks are and focus more energy there.

Continuous Learning: Inspiration and Adaptation

Available today, Adaptive Generation Strategies now turn every interaction into a learning moment. The system continuously synthesises a rich array of data points – from live performance metrics and audience engagement to brand compliance approvals and rejection patterns.

This intelligence takes effect through two mechanisms:

1. Intelligent Inspiration We analyse the stylistic DNA of high-performing content, whether that is your original Control or a new winning variant discovered by the AI. We deconstruct the syntactic, emotional, and semantic patterns that define that success.

The system then generates new variants that utilise those proven strategies. This ensures that the generated language is not only creative but also positions new clusters of variants around the highest-performing areas of the landscape.

2. AI Feedback Loops The system actively adapts based on real-time data. We monitor the performance landscape continuously. When we detect a region of the language space that is delivering results, we optimise our feedback loop to explore that area further.

Crucially, this also applies to human feedback. By analyzing what your team approves and rejects, the system refines its understanding of your brand preferences, further narrowing the search space to content that is both brand safe and highly performant.

These strategies work in tandem to find high performing language faster.

Solving the ‘Cold Start’

Learning from data makes sense, but it doesn’t yet help on day 1. This is where Neural****2, our proprietary performance prediction capability, is pivotal. Neural2 helps us solve the ‘Cold Start’ problem by effectively mapping the terrain before we even begin.

When you launch a campaign, your existing Control content acts as a critical initial signal. It serves as a coordinate on the map. By mathematically assessing its potential, we’re able to adjust our language generation to most efficiently explore the total space whilst discarding quickly those options that won’t stack up.

The Result: Faster Convergence on Value

The introduction of Adaptive Generation Strategies accelerates how Jacquard customers arrive at high performance content. This shift translates directly into customer value:

• Faster Convergence: Because we actively steer away from low-performing areas and double down on what works, we find winning variants significantly faster.
• Decreased Cost of Experimentation: By reducing the time spent in the “valleys” of the search space, we minimise the impressions wasted on sub-optimal content.
• Greater Likelihood of Success: By combining diversity with the proven characteristics of your best-performing assets, we increase the probability that the next variant we generate will be a winner.

Language2 gave us the vehicle; Adaptive Generation Strategies gives us the GPS to optimal performance. By intelligently mapping the search space and minimising the cost of testing, Jacquard ensures that your campaigns are not just running, but actively evolving towards higher performance from day one.

Adaptive Generation Strategies is immediately available to customers currently using the Jacquard Language2 platform.

Brand Voice & Scaling Content: Jacquard’s 2026 Marketing Predictions

We’ve seen a seismic shift in the adoption of AI this year. And what was supposed to solve marketing’s content problem has instead created two new ones. Here at Jacquard, we see the balancing act of these two problems as the fundamental challenge marketing teams have to grapple with in 2026. 

85% of brands now use ChatGPT for production marketing content. It would make sense to think that this might have made marketing easier. But instead we’re seeing brands converge – globally – on a singular voice. It’s one that we can all recognise at this point: a familiar AI-inflected cadence that sounds the same no matter where you see it. Meaningful differentiation is harder than ever. But this doesn’t mean that brands need to turn away from AI: in fact, brands should lean in, utilising the strengths of these powerful tools – the hyper-personalisation they afford, the sheer scale of content they can produce – to ensure that their brand voice stands out from the crowd. 

This will be the first problem marketers have to reckon with in 2026. How to ensure your brand voice stands out, and actually says something meaningful. When ChatGPT handles the copy for everyone, we see the same basic competency embraced on all sides. When a multinational conglomerate and a local startup sound identical because they’re both clicking “generate” on the same prompts, something fundamental breaks down in brand communication.

It’s not that AI is bad at copywriting. It’s about a more fundamental challenge: when everyone uses the same tool, differentiation evaporates. A distinct brand voice, built for performance, once a nice-to-have, is now essential competitive infrastructure. We’ve seen firsthand at Jacquard how the brands that will win in 2026 are those that have moved beyond prompt engineering and built systematic approaches to maintaining linguistic identity at scale and optimising it for engagement and conversion. 

Consumers are already wise to generic AI writing – Google searches of the ‘em-dash’ often used by ChatGPT increased by 400% in 2025 – They are increasingly gravitating towards brands that make the effort to sound genuinely different. The human touch can’t be overstated. Nuances in language hold more weight than ever, and the AI chatter is getting ever louder. Standing out requires more than just better prompts, it requires real depth and understanding. Solving this challenge demands sophisticated infrastructure. At Jacquard, we’ve built tools trained on billions of data points and a decade of language expertise to do exactly that.

Our second prediction is that 2026 will see content creation become the new bottleneck for marketers. We’ve all but solved the data problem – but that’s only left us with a content problem. 

A decade ago, the challenge was collecting, analysing, and activating customer data. Today, with sophisticated tools like AI Decisioning readily available, that’s no longer the primary constraint for most brands. But as audience segmentation and decisioning becomes more sophisticated – and we see increasingly complex groupings based on behaviour, location, language, channel, purchase history and lifecycle stage – content demands multiply exponentially.

Consider the mathematics: if you’re segmenting your audience into hundreds of micro-segments, each requiring personalised messaging across email, push, SMS, and in-app channels, you’re looking at thousands of content variants. This is not a task human copywriters can scale to meet, no matter how talented or numerous. Ask any over-worked copywriting department, and they’ll tell you these numbers mean their task just isn’t feasible. 

The temptation is to throw ChatGPT at the problem. But this creates the very issue outlined above: you solve the volume problem whilst creating a differentiation problem. You end up with content that sounds exactly like your competitors, it doesn’t perform, and you still face the manual effort of distributing that content across channels.

So marketers are looking at managing a difficult balancing act – the content supply chain. Teams are required to create enough (meaningfully) personalised content for all their segments, across all relevant channels, while maintaining a distinctive brand voice. 

This is the bottleneck that most marketing teams haven’t yet acknowledged, let alone solved. Data and tools are abundant. Genuinely on-brand, performant, personalised content at scale remains scarce.

This is where Jacquard’s approach differs from generic AI tools. Our platform learns and replicates a brand’s unique linguistic patterns, allowing marketing teams to generate thousands of personalised message variants that maintain brand consistency whilst driving measurable performance improvements using proprietary performance modelling. We’ve seen brands using this approach achieve click-through rate improvements of up to 89% and conversion rate increases of 30% and more, all whilst producing content at a scale that would be impossible through manual processes. The technology addresses both challenges: maintaining differentiation through brand-specific language models, and solving the content bottleneck through automated, multi-channel distribution.

Our two 2026 predictions – ensuring a distinct brand voice optimised for performance, and handling the content bottleneck – are really two sides of the same coin. As more brands recognise that generic AI tools create sameness rather than differentiation, and as content demands continue to multiply with sophisticated, necessary AI strategies, 2026 will be the year that separates the organisations with proper content infrastructure from those still relying on prompt engineering and manual distribution.

To thrive, marketers will need to move away from focusing solely on prompt engineering and decisioning. They’ll have to find ways to solve the fundamental challenge of maintaining linguistic identity whilst meeting the content demands of modern, hyper-segmented, hyper-personalised marketing.

The question of whether or not to use AI is a thing of the past – the numbers show this starkly. Instead, the question for marketers is now how to use the power and scale AI offers to ensure that their brand voice – that they’ve worked so hard to cultivate and build – doesn’t fade into the cliché-ridden static.

Holiday Shoppers Reject Discounts of Under 10% During Cost of Living Crisis, Ten-Year Study Finds

• New Holiday Marketing report includes research from over 200 billion emails sent across global retailers from 2015 to 2025. Email subject lines that include customer names, exclamation marks, discounts of 10% or less, or urgent phrases like “last chance” or “ending soon” perform the worst in the holiday season
• Question marks found to be four times more effective than exclamation marks in grabbing customer attention 
• The Christmas tree emoji (🎄) is the strongest performing emoji over the holidays, whilst use of snowflake (❄️) actively hurts performance 

Wednesday, November 26th – [LONDON/NEW YORK]: As retailers prepare for a record-breaking $253 billion online holiday season, shoppers navigating a cost-of-living crisis are rejecting small discounts as inadequate. A nine-year study of almost 200 billion email sends carried out by marketing platform Jacquard (www.jacquard.com) has found that discounts under 10% actively hurt engagement during the holidays, with shoppers holding out for offers of 30% or more.

The research also reveals engagement with discount language has increased year-on-year, demonstrating growing consumer focus on value. The finding comes as brands compete more fiercely than ever for consumer spending, with many racing to offer deeper discounts to stand out.

Jacquard’s Holiday Marketing Report 2025 analysed 200,000 promotional email subject lines of email campaigns sent almost 200 billion times from major retailers. The research challenges several established marketing practices: urgent language like “last chance” is 75% less effective during the holidays, while discounts of over 60% provide no benefit whatsoever. 

Jacquard combines AI technology with a team of computational linguists who calibrate campaign language to ensure it resonates authentically with customers, balancing algorithmic precision with human nuance. Jacquard customers include Sephora, Dick’s Sporting Goods, Sam’s Club, Best Buy, and Currys. 

With 2025 poised to deliver the first-ever quarter-trillion-dollar holiday season, Jacquard’s findings reveal which tactics will help brands stand out, and which industry conventions are destined to fail this year.

***

The Goldilocks Discount

Mid-range discounts significantly outperform both shallow and deep discounts during the holidays, according to Jacquard’s analysis.

The data also shows discount language is becoming increasingly engaged with year-on-year, reflecting growing consumer focus on value during the cost of living crisis.

The data showed:

• 40-49% off performs best across all discount ranges
• 30-39% off also performs strongly
• 60%+ off shows essentially no benefit – neutral performance
• Under 10% off actively hurts engagement

Toby Coulthard, CPO at Jacquard comments: “Most brands assume bigger is better with discounts, but shoppers are inundated with emails, and don’t have time to assess whether a 70% offer is genuine or what the catch is – they’ve already moved on. 

Meanwhile, anything under 10% feels insulting when consumers know bigger offers are out there, especially during a cost of living crisis. What we’re also seeing year-on-year is that shoppers are engaging more with discount language overall – value has become the primary driver. The sweet spot is right in the middle, according to our data.” 

Unpopular Personalisation

Adding “for you” and first names to email subject lines reduces engagement, Jacquard’s research found – a trend that becomes particularly costly during the high-stakes holiday period when every email must perform. The finding comes as new Lloyd’s Bank data shows 43% of retailers plan to introduce personalised marketing campaigns this holiday season.

Toby Coulthard, CPO at Jacquard comments: “Consumers remember the brands they regularly engage with, so getting a personalised email from a retailer you made one purchase with years ago feels algorithmic and manipulative. Surface-level personalisation – such as simply inserting a name – ironically makes messaging feel less personal. Meaningful personalisation requires understanding the context of who you are reaching out to. Anything else risks appearing lazy.”

The Punctuation Debate

A single question mark in an email subject line drives 4X higher engagement than an exclamation point during the holidays, Jacquard’s data shows

The analysis also found:

• Use of a single exclamation point has minimal positive impact
• Three exclamation points hurt performance

Toby Coulthard, CPO at Jacquard comments: “Exclamation marks contribute to what is already an excessively noisy holiday season, with every brand clamouring for attention across a variety of social platforms. Inboxes filled with rows of exclamation marks are only going to make shoppers feel like they’re being shouted at. A question mark is more human, offering the reader a chance to respond.“

The Right Emoji

The Christmas tree emoji (🎄) outperforms the use of an exclamation point by 13X in driving engagement, making it the strongest single holiday marketing tactic measured in Jacquard’s study. However, the snowflake emoji (❄️) actively hurts email performance during the holidays.

Analysis of emoji use across 200,000 unique holiday marketing email subject lines showed: 

• 🎄 (Christmas tree) was the strongest single performer across all holiday marketing tactics measured
• 🎁 (gift) had a strong positive impact
• 🔥 (fire): was the next strongest performing emoji
• ❄️ (snowflake): had a negative impact on customer engagement 

“The Christmas tree is universally understood and emotionally resonant – it cuts through the noise,” said Toby Coulthard, CPO at Jacquard. “The snowflake, by contrast, feels generic and wintery rather than festive. Small distinctions matter when inboxes are this crowded. Even something like an emoji can make all the difference.”

Urgency Fatigue

Generic urgency tactics are 75% less effective during the holiday season than the rest of the year, according to Jacquard’s report. 

The data showed:

• Urgency language performs modestly well outside the holiday season
• During November-December, urgency becomes 75% less effective
• The holiday calendar itself creates urgency – adding more becomes redundant

Toby Coulthard, CPO at Jacquard comments: “When every brand is screaming “last chance,” “ending soon,” and “final hours,” the tactic becomes white noise – an inbox filled with a deluge of superlatives. Shoppers already feel deadline pressure from the calendar itself – they know Christmas is coming. Specific deadlines like “Order by Friday for Christmas delivery” cut through because they provide actual utility rather than manufactured panic.”

“New” and “Exclusive” Turn Shoppers Off

Jacquard’s data analysis found that shoppers are more responsive to deals than “new” or “exclusive” items. 

The data showed:

• “New” messaging (new items, just dropped, introducing) in email subject lines actively hurts performance
• “Exclusive/VIP” language has essentially no impact on shopper engagement – completely neutral

Toby Coulthard, CPO at Jacquard comments, “Throughout the year, “exclusive” and “new” drive interest. But during Black Friday through Christmas, shoppers are in a different mindset. During the holidays, consumers’ focus is on securing value rather than hunting for new trends.” 

Methodology:

This analysis examined almost 200 billion email sends from split tests conducted between 2015-2025, focusing on retail and e-commerce campaigns during Black Friday, Cyber Monday, and Christmas periods. Performance was measured using normalised engagement scores across multiple tests.

The data reveals not just what worked in the past, but trending patterns showing which tactics are strengthening (percent-off language) and which are declining (urgency language) heading into this season.

Marketing automation has come a long way.

But despite advances, most teams still experience the workflow as a patchwork of somewhat disconnected tools.

The workflow bottleneck.

Useful tools exist for almost every step of the process, yet marketers still find themselves spending valuable time moving between those systems to complete a single task. For example, creating a typical marketing campaign still follows a familiar but clunky rhythm: a marketer drafts a brief in a document, passes it to a copywriter, circulates it via email for review, involves legal for adjustments, versions it across channels, and finally schedules it manually for send—if it gets approved. Even with modern marketing platforms, each step introduces friction by involving too many tools, too many handoffs, and too many opportunities for misalignment and human error.

This fragmentation is more than just a workflow problem. It’s a creative bottleneck, and it simply does not scale.

The rise of agentic AI.

We see a better way forward. Agentic AI isn’t just another tool for marketers. It acts as a senior teammate who just gets it. Who is more efficient, more productive, and most importantly, better performing than even the top member of your group. In our vision for the (near) future, once a task begins, AI agents take action and complete the work independently.

How they work.

These agents are powered by our content-generation engine (Language2) and performance prediction model (Neural2). They can read a campaign brief, understand its intent, and generate high-performing content for any messaging channel. Crucially, this content is fully aligned with your brand tone and voice—learned from your existing materials as well as your published brand and style guides.

From there, the agents move seamlessly through the pipeline. They route content through brand and compliance workflows using intelligent review triggers. Then, they execute campaigns via your integrated Customer Engagement Platform (CEP) and leverage real-time and historical data to test, learn, and optimise at scale.

Notably, all of this happens within a controlled, brand-safe environment—so your creative integrity is never compromised.

We believe this is the next evolution of marketing work: agentic automation that brings structure, scale, creativity, and velocity to content teams’ operations. That means fewer handoffs, faster execution, and better-performing content, without the tradeoffs. It doesn’t just streamline the workflow. It solves it.

No dashboard required.

These agents don’t need to live in a dashboard. They can be embedded directly into your workflow. Our API-first model separates content creation and optimisation from where it appears, like your CEP or website homepage.

This flexibility lets platforms trigger content creation and optimisation dynamically, so marketers don’t need to log into extra tools. Agent-triggered pipelines mean that creating a campaign brief automatically sets off a chain reaction—from content generation and performance prediction to approvals and optimisation. Importantly, it all happens seamlessly, invisibly, and instantly.

The Future is already here.

That’s why we’re building for a new reality at Jacquard—one where creative and strategic teams aren’t bogged down by tools, but empowered by them. By taking on the tactical legwork and bridging disconnected systems, AI agents free up humans to do what we do best: shape the brand, generate standout ideas, and build deeper customer connections.

This isn’t some distant vision. We’re already making it real—with embeddable, extensible and scalable infrastructure powered by APIs and over a decade of expertise in generating and optimising billions of messages. Backed by rich training data and performance insights, we’re entering a new era of autonomous, on-brand content generation.

Marketers who embrace this shift won’t just be faster. They’ll be freer to think bigger, test bolder, and deliver more impactful work; and they’ll outperform on every engagement metric.

And we’re not alone.

As Agentic AI permeates our online lives and becomes more ingrained in the day-to-day function of The Internet, the largest and most influential players in AI are setting up shop. Amazon, Google, Microsoft, and Salesforce have all recently announced plans, and even already launched products, to give consumers and businesses access to agents through a marketplace.

As these marketplaces go live, Jacquard will be there with our powerful toolset ready to integrate into hundreds of partners with just a few clicks. It’s like onboarding a highly productive and super-efficient team member—without the time or cost of interviews, training, or onboarding—and mathematically guaranteed to outperform any human. Calling this game-changing is no understatement.

We’re not just imagining the future, we’re bringing it to life.

Takeaways:

• Agentic AI is more than automation—it acts on your behalf, streamlining execution while preserving creative integrity.
• Fewer handoffs, faster workflows—AI agents reduce friction by integrating directly into your marketing ecosystem.
• Built for brand, built for performance—Jacquard agents align to your voice and optimise for results from the start.
• This isn’t future-gazing—it’s already happening, and teams adopting this model are already seeing the upside.

Imagine eagerly hitting “purchase” on an online sale, only to find the “limited-time” discount still active days later. Frustrating, right?

This exact scenario has led to lawsuits against major apparel retailers in Washington State since 2023, including one filed as recently as earlier this month. Washington residents have claimed that certain brands have used email subject lines containing false or misleading information about the duration of its promotions such as “today only!” and “sale ends tonight!” to create false urgency and drive sales.  Doing so is in violation of Washington’s Commercial Electronic Mail Act (CEMA).

The performance dilemma.

How could major brands send such problematic content? Often, the culprit might be the AI vendor in their marketing tech stack. These systems can unintentionally generate false and misleading content, especially when prioritizing short-term performance metrics like open rates and click rates, potentially ignoring the long-term damage of increased unsubscription rates.

As aptly stated by Scott Zalaznik, ex-CDO adidas and Jacquard Advisor: “If you send an email that triggers unsubscription rates, that is a red alert. The siren should be going off in the hall.” (Check out Episode 1 of Jacquard’s The Array podcast for more great insights on this.)

The plaintiffs have targeted the brands themselves, and the courts have generally allowed those cases to proceed, because the emails were sent under the brand’s direction and control.  This highlights the importance of a brand’s accountability for the content generated and sent by its martech vendors.

Jacquard’s approach to brand integrity.

At Jacquard, we believe in protecting creativity and brand integrity alongside performance. Here’s how we minimize the risk of generating false and misleading content:

• Separation of Generation and Optimization: Our Language² engine generates diverse message variants tailored to your brand’s voice, tone, and goals. Then, our Neural² predictive engine evaluates these variants for performance potential. This ensures content isn’t just generated to score well; it’s diverse, on-brand, and then optimized to resonate everywhere.
• Built-in Diversity and Uniqueness: We avoid repetition and ad fatigue by enforcing uniqueness constraints, applying semantic spacing, and ensuring our scoring model doesn’t overvalue overused phrases. Even high-performing messages are de-prioritized over time to prevent saturation. This fosters genuine engagement rather than simply chasing conversions.
• Transparency and Control: Our engines generate a curated shortlist of strong, diverse options with sentiment charts and scores. Our integrations allow for testing fresh variants in live campaigns, empowering marketers with control and insights. 
• Calibration Equals Quality**:**  The quality of our content is assured by a team of linguistic experts who regularly fine tune and constantly calibrate our generation models, tracking and eliminating errors.  This gives our customers a data-driven way to trust machine output at scale.
• Brand Voice Consistency: All content is filtered through your specific voice and tone guidelines, ensuring every message, even new creative explorations, feels authentically on-brand.
• Ethical Business Model: Unlike some vendors who profit from short-term revenue share, Jacquard uses a “unit of work” SaaS pricing model. This encourages nurturing long-term customer engagement and retention, not just quick wins.

Jacquard is designed to balance scale, performance, and originality, helping brands grow without sounding like everyone else (at best) or tarnishing their hard-earned reputation (at worst).  Which also keeps its marketing campaigns in the news headlines for all the right reasons.

With over 20 years of experience counseling corporations, Peter provides strategic and practical legal advice to Jacquard.  He advises on best practices and compliance with international laws and regulations pertaining to data privacy, processing and protection, and a growing body of artificial intelligence directives.  His mission is to help the company’s stakeholders focus on minimizing and managing legal, operational, strategic and reputational risks, while enabling the company to grow and scale its innovative generative AI solutions.

The healthcare division of Sodexo needed new ways to enhance demand generation, streamline their marketing processes, and boost productivity. Jacquard’s AI-powered content generation emerged as a true solution.

The challenge: Turn a growing team into a smarter team.

Sodexo’s healthcare marketing team needed a solution to tackle their growing workload while maintaining creativity and efficiency. As Adam Puterbaugh, Sr. Marketing Manager, explains, “We have a small team. So we have to be nimble and do more with less. For us, Jacquard is about being more effective with the time we have.” The Jacquard Platform presented an opportunity to support their lean team with efficient, high-quality content generation.

The pilot implementation of Jacquard came at a time when the team was feeling the pressure. The team had been balancing multiple initiatives and needed a way to alleviate some of the strain on content creation. Jacquard offered a fresh perspective: a tool that could reduce the burden of day-to-day content production, allowing the team to focus on strategic initiatives. “Budgets are always a topic,” Stacie Sands, VP of Growth & Enablement Marketing, added. “So it’s about how you use tools to be more efficient with your spend and your time.”

Turning time saved into higher output.

One of the key benefits of using Jacquard was the time savings it provided for the team. Jacquard’s platform enables marketers to generate brand-safe messaging at scale, producing up to 2,500 brand-compliant message variants curated for performance in just 30 seconds from a single brief. This capability allowed Puterbaugh, who is responsible for creating content for multiple personas across various campaigns, to balance his workload more effectively. “With Jacquard, I can do more with less. It’s like a partner that helps me output more content,” Puterbaugh explained. The team uses the tool to increase output and produce messaging for a variety of personas within two archetypes across multiple campaigns. Leveraging Jacquard has allowed us them to move faster.

Sands echoed this sentiment, highlighting how Jacquard had freed up time for the team to focus on additional value-driving initiatives, such as automated email campaigns that could run alongside or as follow-up nurture sequences. “It has definitely improved output and productivity,” Sands said. “Jacquard has allowed the team to be more flexible and address more when we need it. It absolutely increases team capacity.”

Boosting creativity and beating fatigue.

Beyond efficiency, Jacquard has also played a vital role in enhancing creativity within the marketing team. Content creation can often be mentally taxing, leading to creative fatigue – a challenge that Jacquard is helping to solve. As Puterbaugh put it,”Jacquard helps us diversify our messaging and avoid falling into repetitive patterns.”

Jacquard’s style guide and AI tone-of-voice (TOV) analysis ensure that the content generated always sounds like it has been written by Sodexo’s own copywriters, providing quality assurance at scale. With over 50 customisable brand language settings – shaped by editorial standards from the world’s best brands and TOV insights – the platform allowed the team to tailor content to different personas, adding layers of customisation to each campaign. “We’ve been able to leverage the tone-of-voice feature a lot as our segmentation has evolved,” Puterbaugh shared. “Depending on who we’re targeting, we can create messaging that resonates more deeply with specific audiences.”

Sands added that Jacquard provided a level of creative freedom, allowing the team to test different approaches and reduce the “blank page problem.” “It saves time from a creation standpoint but also gives creative freedom to look at things differently,” she said. “It’s the best of both worlds when you have a tool that helps you be creative and pragmatic.”

The result: More productive, more creative, more engaging.

Since implementing Jacquard, the Sodexo team has seen positive engagement results. Jacquard’s Performance Prediction Engine, trained on years of copy-based experiments, accurately predicts the language, emojis, and sentiments most likely to resonate with an audience. This feature helps the Sodexo team to ensure campaigns are always populated with optimal messaging. Recent campaigns have shown increased click-to-open rates, indicating that the tailored messaging created with Jacquard is resonating with their audience. Puterbaugh also highlighted how the platform has helped them craft more emotionally-driven content for new personas, such as clinicians and dietitians, resulting in better engagement.

“Jacquard has helped us tailor messaging outside of our normal tone to resonate with different audiences,” Puterbaugh noted. “We saw really good engagement from the messaging that myself and Jacquard put together.”

Both Puterbaugh and Sands agree that Jacquard has significantly improved their productivity and ability to meet deadlines. “I cannot imagine if we didn’t have Jacquard. We would need much longer lead times to meet our campaign deadlines” Sands said. “It has freed up time to focus on other priorities and increased our overall productivity.”

A new creative partner.

For Sodexo’s healthcare marketing team, Jacquard has proven to be more than just a tool for content generation – it has become a partner in driving efficiency, enhancing creativity, and supporting human ingenuity. By providing the team with the ability to do more with less, Jacquard has empowered them to focus on what matters most: creating meaningful, resonant content that drives engagement and supports Sodexo Healthcare’s mission of providing quality experiences for every customer, everywhere.

“The moral of the story, at least for me, has been efficiency and creativity,” Puterbaugh concluded. “Jacquard has opened my eyes to other ways of phrasing things, and enabled us to take a data-driven approach to content creation. It’s been very nice to have that support.”

Marketers talk about performance like it’s the ultimate goal. But here’s the truth: when performance is pursued at the expense of creativity and brand integrity, it becomes a short-term game.

And nowhere is that more obvious than in the rise of ad fatigue.

Engagement doesn’t drop off because customers see too much—it drops off because they stop seeing something that feels worth engaging with. Eventually, customers stop clicking. They tune it out. Not because of frequency, but because the creative no longer resonates—it feels repetitive.

At Jacquard, we believe solving for ad fatigue doesn’t come from chasing short-term metrics. It comes from delivering on-brand, high-quality creative at scale, over time.

The real cost of over-indexing on performance.

CRM and lifecycle teams are often tasked with proving quick wins. Opens. Clicks. Conversions. It’s understandable—but over time, over-optimizing for immediate performance can lead to content that lacks depth and distinctiveness.

AI decisioning tools help, but they’re limited. These models often optimize what’s already working, not what will resonate next. They don’t understand brand nuance or shifting audience expectations.

That’s where ad fatigue creeps in—not because the audience has changed, but because the creative hasn’t. In fact, studies show that seeing the same creative just four times can lead to a ~45% drop in conversions—proof that fatigue isn’t about overexposure, it’s about creative staleness.

Ad fatigue isn’t solved by sending less—it’s solved by delivering messages that stay relevant, fresh, and unmistakably on-brand. That requires a system built not just for output, but for evolution. That’s where Jacquard comes in.

Jacquard is built to help teams scale brand-aligned creative without sacrificing nuance, control, or performance. It learns what works, adapts to shifting audience behavior, and generates fresh, on-brand messaging—automatically.

This enables marketers to deliver hundreds of message variants across channels that feel personalized, cohesive, and never stale—without burning out their teams or their audience.

And it matters: Google reports that 70% of a campaign’s success is driven by the creative. That means investing in intelligent, adaptive messaging isn’t optional—it’s the foundation of sustained performance.

Sustained Performance > Short-Term Lift

A single performance spike isn’t the goal. At Jacquard, we’re focused on compounding uplift—the kind that happens when every message builds trust, maintains consistency, and performs just a little better than the last.

When creative reflects your brand and adapts to audience behavior, fatigue doesn’t stand a chance. That’s how you unlock real momentum—and avoid the trap of always chasing “what worked yesterday.”

Key takeaways.

• Ad fatigue isn’t just about frequency—it’s about creative that stops resonating
• Chasing short-term metrics can erode brand trust and long-term performance
• Jacquard helps teams scale brand-aligned, high-performing messaging that adapts over time
• Sustained performance comes from creative that evolves—not just performs once

The last mile.

Think of how e-commerce giants build sophisticated logistics spanning the globe, all designed to deliver on customers’ expectations. Yet it’s the final step — getting packages delivered safely into customers’ hands — where those investments could still come to nothing. If there’s a problem in the ‘last mile’, brutally, it can shape the entire customer experience.

Marketers face a similar challenge with brand communications. Despite substantial investments in customer insights, at the very moment brands have something to say, messages can end up in the ‘personalisation gap’. With 89% of businesses expecting to compete based on customer experience (Gartner, 2024), data-led personalisation strategies are a key pillar. But does simply mentioning a customer’s name or product preference in communications deliver on the promise of personalised experience?

At Jacquard, we really pay attention to how big a difference it makes when your messaging is crafted to resonate. For brands using our platform, it’s like having an expert writer on the team who operates at limitless scale. This amplifies results everywhere. It really is the perfect opportunity to do more with less.

Scaled language, not stale language.

Your company may have also invested time and significant budget building out data and insight capabilities. Customer data platforms, engagement platforms, data lakes, pipelines, warehouses and data science teams – all delivering profiles and insights on your customers and what they want. AI decisioning engines might even be targeting customers with the products and offers to work out ‘what’ to say.

Yet when it comes to actually speaking to these well-understood customers, brands often hit a wall. Customer insights rarely translate into truly engaging language. Why? Because creating great brand language at scale can now only be done viably by embracing specialist AI technology, not by using LLMs off the shelf.

“We’ve spent three years building this customer data infrastructure,” a CMO recently told us. “But our comms sound like they could be coming from anyone. We should be doing better than this.”

Ten years ago, teams managed a handful of touchpoints. Today, brands try to be engaging across websites, apps, emails, SMS, social platforms, chatbots – with each demanding content that’s:

1. True to your brand voice
2. Optimised for specific channels, campaigns and the range of offers
3. Compliant with regulations
4. Delivered at unprecedented speed and scale

Even with the best data foundation, manually transforming insights into personalised messages across all these touchpoints overwhelms marketing teams. The content bottleneck is real–but it’s solvable, and you don’t need to await the completion of those customer data integration projects to deliver value.

Why wait to resonate?

Here’s where traditional thinking needs challenging: you don’t need your customer data projects finished to improve your brand messaging in ways that customers respond to. In fact, great customer communications can be your quick-win. Demonstrate value immediately while longer-term data projects continue to mature. With this mindset, brands can immediately capitalise on the opportunities to achieve more with less.

Jacquard allows you to jump straight over the personalisation gap. Our customers are already showing this by:

• Scaling up great creative content generation without scaling their teams
• Forging bandwidth in creative teams to tackle more human-level problems
• Refining messaging based on evidence from 60 billion historic data points
• Maintaining brand voice consistently across channels and languages, while personalising for customers and campaigns

Best of all, these solutions work with your existing capabilities to immediately improve how you engage with customers across all your channels.

The companies pulling ahead aren’t only those with the most sophisticated data infrastructure. They’re the ones who go that last mile to generate meaningful, personalised communications. By focusing on this critical messaging aspect of customer marketing, brands can rapidly unlock the value of all those upstream investments. After all, your customers don’t experience your data strategy – they experience your communications.

Isn’t it time you benefited from an AI-powered copywriting team that can meet your content needs?

Be the first to see true 1:1 personalisation in action

Our latest offering tailors your messaging to each individual and delivers contextually relevant language that resonates with every customer – every time

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Every brand knows what they want to say. The challenge is saying it in a way that actually works.

That’s where Language² and Neural² come in—Jacquard’s latest product updates designed to master the how of messaging.

Language² is our most advanced generative engine yet—built to deliver diverse, compliant, brand-aligned messaging at speed. Neural² is our patent-pending predictive engine, designed to forecast message performance and improve ROI with every campaign.

Together, they’re a brand’s highest-performing below-the-line copywriter—giving marketers a way to scale content without losing nuance, consistency, or control.

In this short video, Toby Coulthard (CPO) and Jasper Pye (CTO) break down:

• The four factors that drive message engagement
• How Language² generates diverse, compliant, on-brand copy
• How Neural² predicts content performance with precision
• What’s coming next in the Jacquard product roadmap

Spring is a natural time for fresh starts, and at Jacquard, we’re stepping into the season with two major product updates that are revolutionising brand messaging.

Introducing Language2 and Neural2

People engage with brand messaging for four reasons: Who (Brand), Where/When (Channel /Timing), What (Product/Offer), and, critically for the attention economy that we all live in, the How (the creative language and imagery that conveys the message). Jacquard perfects the “How” of brand language, with purpose-built technology and a massive data set, refined over 10 years, that empowers brands with messaging that resonates everywhere.

To further this mission, we’re announcing two major developments: Language2 and Neural2.

Language2: Advanced Generative AI for Diverse, Optimal and Compliant Messaging

Our original language generation platform, Language1, was developed over the 7 years that preceded the general availability of LLMs. It was the basis for a business that understands the complexity and power of brand language like no other. 

With LLMs came the potential for much greater creativity…but such power had to be met with equal power to control such vast and diverse output.

Only Jacquard, with its unusual specialism and expertise in brand language, had the mechanics and understanding to harness and control the power of LLMs for the needs of mature businesses…and this comes with the release of Language2.

Language2 uses a multi-agent architecture for language diversity while maintaining compliance without managed services. It is much faster than its predecessor, meaning users can immediately prompt the system without prior configuration. It enables far more use cases such as non-repetitive content like current affairs and viral campaign language.

Creativity and control with Language2 unlocks the power of AI to automate the content supply chain given that outputs are calibrated for machine scale; to a far higher degree than with brand guidelines alone.

From a technical perspective, Language2 takes a sophisticated neurosymbolic approach. It integrates probabilistic AI  agents—responsible for dynamically generating context-aware, engaging content—with deterministic rules and filters designed to ensure strict compliance with brand guidelines and regulatory standards.

For every content variant deployed in a campaign, Language2 first creates hundreds to thousands of potential message candidates. Each candidate undergoes rigorous evaluation, with only the highest-performing, brand-compliant variants ultimately being selected. Agents within Language2 specialise in key tasks such as tone consistency, contextual precision, and brand alignment, ensuring every message is maximally impactful, contextualised, or both.

Neural2: Predictive AI Powered by Patent-Pending Technology

Drawing from an immense repository of over 60 billion data points collected from a decade of global campaigns, Neural2 predicts message performance with remarkable accuracy before deployment.

The win rate of Neural2’s predicted champion vs. controls is 66% (tending to 100% with testing), which means it is statistically inevitable that Neural2 will outperform human and LLM generated content alone.

This predictive power helps brands consistently deliver content that achieves higher engagement, strengthens customer relationships and optimizes return on investment. AI decisioning platforms like Hightouch, Offerfit, Aampe, Databricks and Movable Ink Da Vinci can tell a brand what to say, Neural2 finds the best way to say it.

Neural2 extends the application and performance of our original Neural Engine to new languages and channels. In turn, this improves performance over time given the expanding data set; the 66% baseline win rate will only improve.

Neural2 enhances Jacquard’s capabilities by leveraging patent-pending technology and Bidirectional Encoder Representations from Transformers (BERT) with cross-language embeddings. Think of it as an advanced translator for customer engagement, decoding precisely what resonates most effectively across any language or cultural context.

Language2 + Neural2 = The Best Below-the-Line Copywriter

Together, Language2 and Neural2 are a brand’s highest performing below-the-line copywriter.

They significantly outperform human efforts (with or without an LLM or LLM wrapper): Brands achieve measurable uplifts of 20% on average and in some cases surpassing 200% improvement through continuous optimisation. Some Jacquard customers have seen engagement improvements exceeding 105% on average across more than 80 campaigns.

These two powerful engines feed directly into Jacquard’s Contextual1 and Optimise1 decisioning engines, enabling contextual messaging for differentiated relevance that is true to the brand, as well as dynamic content optimisation at scale.

What’s Next?

Looking ahead, Jacquard is investing heavily in expanding the intelligent analytics suite. This year, expect to see deeper, actionable insights into brand language performance and customer engagement. We’re also entering the exciting domain of new content types, starting with imagery, allowing brands to communicate even more effectively.

Upcoming enhancements include upgraded AI generation models, robust self-serve insights, and expanded integrations with top marketing platforms such as Braze, Iterable, and Insider.

Language2 and Neural2 are available today, with more features and integrations rolling out over the coming weeks. In the coming weeks, we’ll also launch our new analytics suite and innovative collaborative features designed specifically for your marketing teams.

Want a closer look?

Hear directly from our CPO Toby Coulthard and CTO Jasper Pye as they walk through what’s new in the Spring Release. Watch the full breakdown below.

Get exclusive insights not shared in episode #008 with this 4-minute bonus episode, “Cut through this sea of sameness.”

Host

Toby Coulthard, CPO, Jacquard Jasper Pye, CTO, Jacquard

Guest

Grace Cowlard, Creative Director

Listen to the full episode →

Grace Cowlard—Creative Director (formerly of Adidas)—joins The Array to talk about using AI to amplify human creativity, not replace it. Drawing from her experience across fashion, lifestyle, and sustainable brands, Grace offers an honest and hopeful take on where marketing is headed.

Together, we explore how enterprise brands can:

• Keep emotional intelligence at the heart of creative work (3:57)

• Use AI to scale volume—without compromising brand expression (10:12)

• Avoid the “sea of sameness” by flexing tone across channels (19:20)

• Embrace AI experimentation while protecting what makes your brand human (26:33)

Plus, we discuss AI as aesthetic, why creatives should treat AI like an intern, and the debut of “Go Out and Play” as our unofficial 2025 motto.

Host

Toby Coulthard, CPO, Jacquard Jasper Pye, CTO, Jacquard

Guest

Grace Cowlard, Creative Director

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TUI Group, one of the world’s leading tourism companies, has over 20 million customers globally – and multiple brands, including TUI, First Choice, and Marella Cruises. TUI Group’s goal has been to increase their reach and engagement by expanding optimisation efforts across more languages and channels, while reducing the cost of sales.

The challenge: Increasing engagement through owned channels.

Testing content to find the right message for the right person is crucial for optimising campaign performance. However, for global brands like TUI Group with large, highly segmented audiences, doing this consistently and at scale across multiple brands, channels, and languages is both time-consuming and resource-intensive. As a result, many marketers fall into the trap of conducting tests sporadically or focusing on just one channel, limiting their effectiveness.

TUI Group needed a solution to automate its content creation and scale its testing process, allowing them to break free from a single-channel approach and fully leverage the capabilities of their existing tech stack.

The solution: Automating content generation and optimisation.

In May 2022, TUI Group turned to Jacquard to help automate content generation and experimentation. And the partnership began with a focus on generating and optimising email content in English (UK) for its TUI brand.

The consistent approach to campaign optimisation quickly demonstrated its impact by increasing engagement and streamlining content production for TUI’s email campaigns. This set the foundation for further expansion.

From one brand to many.

By February 2023, TUI decided to leverage Jacquard’s capabilities to manage content for additional brands, First Choice and Marella Cruises. Each of these brands carries a unique identity, and Jacquard’s ability to differentiate messaging for each was crucial in maintaining authenticity while driving cross-brand efficiency. “Being able to differentiate between our brands is valuable because, although we are under one umbrella company, all three brands that we work across are very different,” says Jinnie Martin, Senior CRM Manager at TUI. “We’ve seen really strong success in the TUI and Marella brands with Jacquard.”

Expanding to a multi-lingual approach.

Recognising the power of tailored communication and realising they could now do far more testing in much less time, TUI added German as an additional language in which to generate and optimise content. With Jacquard’s multi-language support, TUI began executing effective, localised campaigns in both English and German, managed seamlessly by regional teams. This provided a consistent yet localised customer experience, ensuring that every message resonated with its audience and remained brand-aligned. Jinnie Martin adds, “The results we’ve seen are positive, and we’re looking forward to scaling similar success across additional languages as we move forward.”

Scaling success through channel and campaign expansion.

The increased productivity, efficiency, and engagement meant TUI could now start a multi-channel testing strategy, leveraging Jacquard to optimise content across web and mobile push channels alongside email. The partnership also moved beyond simple broadcast campaigns, adding automated trigger-based campaigns across these channels. “Basically it works,” says Simon Baines, Head of CRM for TUI UK & Ireland, “Jacquard is instrumental in driving up engagement across our email and app channels, resulting in more direct, organic traffic. The more we can drive engagement through our email and app channels, the less money we have to spend on third-party channels.”

Delivering tangible value across the tech stack.

By using Jacquard, TUI has seen a significant expansion in its marketing strategy: from a single-language, single-brand email testing strategy to a complex, multi-language, multi-brand approach spanning email, web push, and mobile app push. This expansion has not only amplified TUI’s owned channel engagement but also maximised the value of TUI’s existing tech stack investments. By driving better performance through their CEP and supporting multi-channel, multi-language content execution, Jacquard has made TUI’s technology investments more valuable and cost-effective.

Jacquard’s audience optimisation feature was instrumental in TUI’s ability to expand its campaigns effectively. By integrating with TUI’s existing tech stack – including tools like Braze – Jacquard enabled TUI to test up to 10 language variants simultaneously and adjust distribution in real-time based on performance. This allowed TUI to identify the best-performing content for different segments, automatically removing underperforming variants and introducing new ones as needed, resulting in sustained engagement growth.

The result: Realising the true value of existing investments.

TUI’s journey with Jacquard demonstrates how brands can realise the full value of their existing tech stack by expanding their marketing capabilities across more channels and languages. TUI has not only improved efficiency and engagement within its CEP but also created new opportunities for growth across its owned channels. The results speak for themselves: increased engagement, enhanced brand differentiation, and optimised marketing operations – all leading to a stronger, more cohesive presence across markets. For TUI, the value of their tech stack has not only been preserved but significantly amplified, making the idea of turning off Jacquard an increasingly costly consideration.

Executive summary.

TUI Group, one of the world’s leading tourism companies, operates a complex marketing landscape involving multiple brands, languages, and channels. To keep customers engaged and reduce customer acquisition costs, TUI turned to Jacquard to optimise their marketing messages across owned channels – specifically email and app push campaigns. The results were significant: enhanced engagement, streamlined content creation, and increased website traffic, supporting TUI’s goal of becoming one of the most loved holiday brands in Europe.

Introduction.

With over 20 million global customers, TUI’s goal is to reduce the cost of sales by increasing engagement through owned channels. Simon Baines, Head of CRM for TUI UK & Ireland, highlights the importance of engaging more customers directly: “Our wider marketing objectives are about how we reduce our costs of sale. The more we can drive engagement through our email and app channels, the more direct, organic traffic that generates, which means less money we have to spend on third-party channels.”

To achieve this, TUI needed more than just their customer engagement platform (CEP), Braze, to distribute communications. They needed a solution that could amplify marketing activity through Braze by creating on-brand, data-driven content at scale, while finding the right message for their audiences through a test-and-learn approach. This is where Jacquard came in.

Tailoring messaging across multiple brands and languages.

TUI operates several brands, each with its own distinct identity and audience. For Jinnie Martin, Senior CRM Manager at TUI UK, Jacquard’s ability to differentiate between these brands has been invaluable: “Being able to differentiate between our brands is valuable because, although we are under one umbrella company, all three brands that we work across are very different. We’ve seen really strong success in the TUI and Marella brands with Jacquard.”

The ability to tailor messaging was crucial, especially given TUI’s diverse range of customers across different countries. Jacquard’s multi-language support enabled TUI to deliver effective, localised campaigns in English and German – all managed by separate regional teams. This not only streamlined operations but also ensured that each message resonated with its intended audience while maintaining a consistent and recognisable tone of voice across TUI’s communications.

Optimising performance with predictive analytics and experimentation.

Jacquard’s neural network enabled data-driven content generation, and automated testing at scale allowed TUI to continually improve campaign performance without manual intervention. Simon Baines notes: “Having science behind the subject lines being suggested – combined with easy integration into our processes and the ability to execute the optimisation activity – was the value that set Jacquard apart for us.”

Simon Baines highlights how Jacquard’s predictive capabilities stand out from traditional methods: “Given a collection of subject lines, I couldn’t consistently pick the winner. The machine does a better job than people and does it consistently.” Because Jacquard’s neural network predicts the content most likely to perform with 94% accuracy, the experiments TUI conducted started with high-performing content from the outset, driving better results.

He continues, “There’s still variety in the language being produced, which means you would struggle to spot the machine-written ones.” Demonstrating how Jacquard’s AI not only outperforms human selection but also maintains the creative quality needed to keep content engaging and authentic over time.

Integrating Jacquard into TUI’s tech stack.

Integrating Jacquard into TUI’s existing tech stack was crucial for maximising its impact and improving the campaigns deployed via Braze. Jacquard’s patent-pending audience optimisation technology allowed TUI to test up to 10 language variants and automatically adjust their distribution based on audience response rates. Underperforming variants were removed, while new ones were introduced to sustain engagement. This real-time optimisation ensured that TUI’s best-performing messages consistently reached a wider audience, enabling TUI to expand and refine its campaigns across more channels, brands, and territories.

Jinnie Martin describes the journey as “really seamless,” thanks to regular support from Jacquard’s team: “We had regular catch-ups and a number of training sessions. The team was always on hand to support us.” Simon Baines echoes this sentiment, praising the customer experience compared to other third-party suppliers: “We really enjoy working with Jacquard because the people are always on it. With many suppliers, there’s often a lot of deflection. So what we really appreciate is the openness and transparency of the Jacquard team. We respond really well to that.”

Data-driven language insights.

Another valuable aspect of Jacquard’s platform was their integrated reporting suite, which provided TUI with insights into campaign performance. “We can see the results in an integrated way and also see a breakdown of language patterns, which is a really important feature that we get with Jacquard that wouldn’t have been available with generic tools,” Simon Baines explains.

The results.

The results have been significant. “Basically, it works,” says Simon Baines. “Jacquard is instrumental in driving up engagement across our email and app channels, resulting in more direct, organic traffic. The things that Jacquard said would happen are the things that happened.” Jinnie Martin adds, “The results we’ve seen are positive, and we’re looking forward to scaling similar success across additional brands as we move forward.” This result-oriented partnership has helped TUI strengthen its brand presence and connect more effectively with customers.

Looking ahead.

TUI is eager to explore new opportunities with Jacquard. Since starting with Jacquard on email campaigns for the TUI brand in English, they have expanded to two languages (English and German), three brands (TUI, Marella Cruises and First Choice), and three channels (email, web push and mobile app push) over two and a half years. The next step is Personalised Campaigns, as TUI continues to build on its success. “Personalisation is a big driver for us, understanding how we can create more personalised experiences for our customers in order to drive better engagement,” Jinnie Martin says. By leveraging Jacquard’s Contextual1 Personalisation Engine, TUI aims to deliver even more tailored experiences for its customers, making every interaction more relevant and impactful.

Enterprise marketers have an ever-growing suite of spectacularly powerful engagement tools at their fingertips.

But many brands are still coasting on outdated customer relationship management (CRM) strategies.

And customers are tired.So how can enterprise marketers break old habits and start creating more meaningful connections? Based on insights from The Array podcast, here are 8 ways to fight customer fatigue and transform CRM.

1. Stay focused on practical AI applications.

There are an overwhelming number of AI-driven solutions promising big results. But not every new tool will transform your marketing.

• Test before (and after) you invest. Brands must be willing to experiment.
• Avoid shiny object syndrome. Don’t adopt AI just to be first; focus on real use cases.
• Recognise that tech alone doesn’t solve problems. Tech must be strategically integrated into your existing marketing framework.

TL;DR: AI can streamline processes, but human oversight remains essential to avoid wasted investments and ensure your tools deliver real value.

2. Embrace a culture of experimentation and learning.

The best marketing strategies come from a test-and-learn approach. Brands that refuse to experiment are likely to stagnate. On the flip side, some companies dive into new tech with great eagerness, but may struggle to integrate it effectively.

• Develop a framework for experimentation. Structured testing helps separate effective tools from ineffective ones.
• Accept failure as part of the process. Failure isn’t wasted effort if it leads to valuable insights.
• Use AI to detect patterns faster. Rather than relying on instinct alone, leverage data to guide decisions.

TL;DR: The most successful marketers learn just as much from the things that don’t work as the things that do. Failure isn’t the end point. It’s a mile marker.

3. Don’t rely solely on paid media for engagement.

Many brands still prioritise paid media strategies without fully evaluating their effectiveness. Just because a campaign appears successful on the surface doesn’t mean it’s driving real value.

• Look for ‘the smoke’. Metrics like session time and first sign-in (FSI) speed can reveal fraud or inefficiencies.
• Audit traffic sources. Not all clicks are created equal. Some paid networks inflate KPIs without delivering real customers.
• Shift focus from vanity metrics to revenue impact. Cut underperforming paid strategies and reinvest in more effective engagement tactics.

TL;DR: If cutting ad spend doesn’t impact revenue, you’ve uncovered inefficiencies worth eliminating.

4. Rethink CRM and email engagement.

Traditional CRM channels – especially email – are showing signs of fatigue. Customers are inundated with generic messaging, leading to lower open rates and engagement.

• Segment your audience more intelligently. Not all subscribers should receive the same messages.
• Make email an extension of your brand community. DTC beauty brands, for example, treat email as a relationship-building tool rather than just a promotional channel.
• Measure the right indicators. Channel health, customer retention, and product visibility are stronger success metrics than email open rates alone.

TL;DR: Engagement is about quality, not quantity. Sending more emails won’t fix customer fatigue. Better messaging will.

5. Focus on the ‘persuadable’ audience.

Not every customer is equally likely to engage with your brand. Identifying and targeting those most likely to respond can prevent wasted marketing spend.

• Recognise three key customer segments. Always engaged. Never engaged. And sometimes engaged. This last segment is your persuadable audience.
• Optimise messaging for those on the fence. Test different tones, formats, and content strategies to move them toward conversion.
• Use dynamic engagement throttling. Adjust communication frequency based on user behavior rather than a fixed schedule.

TL;DR: Don’t just send more messages—send the right messages to the right people at the right time.

6. Get more creative with customer engagement.

Today’s customers expect more than the same old marketing tactics. Brands must use their tech stack more creatively to capture attention.

• Gamify interactions. Interactive elements (like streak messaging or rewards for repeated actions) increase engagement.
• Test new formats. Videos, interactive experiences, and immersive campaigns drive better retention than static content.
• Make engagement fun. Customers respond better to messaging that surprises and delights them.

TL;DR: Creative engagement isn’t about gimmicks. It’s about making interactions feel fresh and valuable to the customer.

7. Leverage retail media more effectively.

Many enterprise brands operate marketplaces with huge advertising potential, yet they rely on outdated banner ads that fail to engage customers meaningfully.

• Shift from static ads to immersive experiences. Integrate interactive product placements rather than generic banners.
• Use first-party data for smarter targeting. Brands have more valuable data on their customers than Google or Facebook. Make use of the in-store experience at the point of sale.
• Turn engagement into a revenue driver. Customer interactions should contribute directly to business goals, not just serve as a marketing expense.

TL;DR: Your first-party data is more valuable than ad clicks. Use it to build better customer experiences and increase conversions.ent isn’t about gimmicks. It’s about making interactions feel fresh and valuable to the customer.

8. Build marketing teams that function like product teams.

Marketing is evolving beyond traditional campaign-based work. The future of engagement lies in a hybrid approach – one that blends product thinking with creative execution.

• Automate repetitive tasks. Free up teams to focus on strategy and innovation.
• Appoint ‘owners’ for key metrics. Dedicate people to customer retention, first-time activation, or ancillary service adoption.
• Balance automation with human ingenuity. Let AI handle scaling, while marketers focus on creating remarkable experiences.

TL;DR: The best marketing teams of the future won’t just launch campaigns—they’ll design experiences that customers actually want to engage with.

One key takeaway: good engagement runs on evolution.

AI, automation, and data-driven personalisation offer massive opportunities, but only if they’re used strategically. By focusing on smart technology adoption, creative engagement, and customer-centric decision-making, enterprise marketers can reimagine how they connect with customers – and build loyalty that lasts.

The insights in this series are based on conversations and learnings from The Array podcast**.** Want to learn more? Watch episode #005, featuring Warrick Godfrey, Founding Partner of Fuse.cx.

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Dr. Neil Yager, Chief Data Scientist of Jacquard, charts his journey from AGI skepticism (“This is not a technology that we’ll see in my lifetime, if ever.”) to optimism – before offering his thoughts on what’s required to achieve it, what exactly it is, and what it could mean for our world.

Get exclusive insights not shared in episode #007 with this 4-minute bonus episode, “What’s going on behind closed doors.”

Host

Toby Coulthard, CPO, Jacquard Jasper Pye, CTO, Jacquard

Guest

Dr. Neil Yager, Chief Data Scientist, Jacquard

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Dr. Neil Yager, Chief Data Scientist of Jacquard, joins The Array to offer “a brief history of time as it relates to AI” – mapping the milestones that brought us to where we are, then laying out what lies ahead for enterprise brands as they adopt new technologies.

Neil shares a true data science insider’s perspective for marketers and creatives eager to:

• Explore 20 years of AI breakthroughs – and what’s needed to continue unlocking its potential (4:28)
• Find out what the evolution of AI imagery could mean for marketers (16:07)
• Produce high-quality content in an era of “dead Internet” mediocrity (26:03).

Then we return to (almost) everybody’s favourite future-of-employment segment, “Will AI Take Jasper’s Job?” (Spoiler: it’s not looking good for Jasper, but at least his dreams might offer a future revenue stream.)

Host

Toby Coulthard, CPO, Jacquard Jasper Pye, CTO, Jacquard

Guest

Dr. Neil Yager, Chief Data Scientist, Jacquard

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Warrick Godfrey, Founding Partner of Fuse.cx, looks to the future of marketing and sees transformed team structures – where creatives spend their time “focusing on inventing new stuff and new ways of solving problems” and AI tools take care of repetition and amplification.

Get exclusive insights not shared in episode #005 with this 3-minute bonus episode.

Host

Toby Coulthard, CPO, Jacquard Jasper Pye, CTO, Jacquard

Guest

Warrick Godfrey, Founding Partner, Fuse.cx

Listen to the full episode →

“Customers are tired.”

“You’ve got these cool tools. Let’s use them better.”
_

Warrick Godfrey, Founding Partner of Fuse.cx, arrives to help us kick off season 2 of The Array – with his honest take on the state of customer engagement. (Spoiler: most brands are coasting on old tactics and need to do better. Fortunately, better is within reach.)

Get Warrick’s generous insights into how brands can:

• Sort the AI and MarTech hype from reality (05:07)
• Address customer fatigue in traditional CRM channels (12:30)
• Use old and new tools to build more creative customer engagements (20:12).

And don’t miss the debut of “Pipeline or Hype Line?” – the new game where we debate whether we’re getting our money’s worth from recent tech innovations.

Host

Toby Coulthard, CPO, Jacquard Jasper Pye, CTO, Jacquard

Guest

Warrick Godfrey, Founding Partner, Fuse.cx

Listen to the full episode →

Artificial intelligence (AI) is already transforming marketing operations – reshaping the creative process, decision-making, and business expectations.

Enterprise marketers looking to adopt new AI tools and technologies are overwhelmed with choice (and hype). But the rewards for getting it right are clear: enhanced operational efficiency, personalisation, and customer engagement – and scalable innovation. 

Here are three steps enterprise marketers can take to identify, integrate, and maximise value from AI technologies.

1. Start with the problem, not the technology.

AI adoption often stumbles when organisations leap to solutions without understanding the challenges they aim to address. But the problems that marketers are trying to solve with AI are the same problems they’ve always had: improving customer lifetime value, fostering brand affinity, and enhancing marketing effectiveness. AI isn’t a magic wand; it’s a tool you can use to solve specific pains more efficiently.

Define the marketing problems you face by asking objective-focussed questions, like:

• Are you struggling to create personalised content at scale?
• Are you able to get rich insights from large amounts of customer data?
• Is creative guesswork having a negative impact on campaign effectiveness?

Once your problems are better understood, you can begin to evaluate how AI can help. For example, generative AI models can create individualised messaging tailored to customer preferences. Machine learning models can detect patterns in customer behavior, enabling data-driven decisions about what resonates with your audience.

TL;DR: Approach AI as a partner in solving unique business challenges, not as a one-size-fits-all solution.

2. Scale creativity without sacrificing brand integrity.

AI gives marketers the ability to create things like personalised email and social media content at unprecedented scale. But overreliance on AI risks losing the human touch that makes brands relatable. Instead of delegating everything to AI, it should be used to amplify creativity – while maintaining brand consistency and a sense of authenticity.

Consistency starts with firm brand guardrails, built around:

• Establishing clear tone-of-voice guidelines for AI outputs
• Creating systems to review and refine AI-generated content
• Balancing automation with human oversight for nuanced messaging.

AI’s real value lies in its ability to help marketers multiply efforts by 10x or 100x – not simply reduce workloads. By combining AI’s efficiency with human creativity, brands can engage their audience without diluting the humanity and strength of their identity.

TL;DR: Use AI to enhance your ability to tell unique stories at scale, but ensure the human perspective guides the overall strategy.

3. Embrace data-led decision-making.

T3. Embrace data-led decision-making.

Traditional marketing often starts with a hypothesis: targeting a specific group or addressing a core demographic with pre-determined messaging strategies. But AI enables marketers to bypass initial hypotheses and creative guesswork. Powered by machine learning, neural networks, and large language models, you can now leverage data to drive confident, impactful decision-making.

And this gives your brand the ability to deliver:

• Precision targeting: the right AI tools can identify the most relevant groups to engage with and determine how to communicate effectively.
• Enhanced messaging: AI can tailor messages to meet consumer preferences, ensuring relevance and resonance.
• Increased relevance: AI can eliminate irrelevant or redundant communications by basing decisions on robust data patterns.

TL;DR: Focus on using AI for decision-making rather than just data collection to ensure your marketing efforts are targeted, effective, and aligned with consumer needs.

AI is about revenue generation, not cost-cutting.

One common misconception is that AI’s primary value lies in reducing operational costs. However, the real opportunity lies in driving revenue by enhancing customer engagement and loyalty. As one speaker aptly put it, this is not about trimming expenses—it’s about creating richer experiences that convert audiences into advocates.

AI empowers marketers to:

• Create hyper-personalised messaging that resonates deeply with diverse audiences.
• Understand customers at a granular level and communicate with them more effectively.
• Use insights to drive innovation in product positioning and campaign strategies.

One key takeaway.

AI is a transformative force for enterprise marketers, but its adoption requires intentionality and strategy. By starting with specific problems, scaling creativity responsibly, and embracing data-led decision-making, brands can unlock AI’s true potential.

AI isn’t a panacea for all your marketing problems, but it can be a powerful catalyst for growth – built on deeper connections and smarter innovations.

The insights in this series are based on conversations and learnings you can find in our new podcast, The Array. Want to learn more? Catch up with episode #004, featuring Lucy Colback, Technology Writer for The Financial Times.

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Lucy Colback, Tech Writer for The Financial Times, leads the conversation in the final recap episode of season 1 – getting the answers that enterprise brands need to earn creative buy-in and grow more rewarding customer connections.

Host

Toby Coulthard, CPO, Jacquard Jasper Pye, CTO, Jacquard

Guest

Lucy Colback, Technology Writer for The Financial Times

Listen to the full episode →

“The problem you’re trying to solve with AI is the same problem you’ve always had. And it’s how can you be more effective at marketing?”

“This is not a cost-cutting exercise, people. This is a revenue-generating exercise.”
_

Lucy Colback, Technology Writer for The Financial Times, switches things up for the final episode of our first season, taking over The Array to ask some tough questions – on behalf of the companies and creatives trying to find the right way forward with AI.

Hosts Toby Coulthard, CPO, Jacquard, and Jasper Pye, CTO, Jacquard, share their AI-insider (and creative background) perspective into the value of:

• Seeing AI as an opportunity to scale creativity, rather than outsource it (11:56)
• Enabling brands to speak to consumers the way they want to be spoken to (19:50)
• Showing creatives how AI can empower them (and earning their buy-in first) (22:46)
• Using AI as a tool to help generate revenue, not cut costs (25:41)
• Figuring out the problem that you want to solve, before choosing the AI tool (28:19).

Then stick around for “Around Our World In 80 Seconds” – the game that delivers plenty of TL;DR perspective on good, bad, and bizarre stories from the world of AI.

Host

Toby Coulthard, CPO, Jacquard Jasper Pye, CTO, Jacquard

Guest

Lucy Colback, Tech Writer for The Financial Times

Listen to the full episode →

Daniel Head, CEO, Jacquard, joins The Array to explain how the right brand guardrails can help marketers bring their new machinery into compliance, increase performance (without creating clickbait), and enable greater human creativity.

Host

Toby Coulthard, CPO, Jacquard Jasper Pye, CTO, Jacquard

Guest

Daniel Head, CEO, Jacquard

Listen to the full episode →

The competitive landscape has changed for enterprise marketers – and innovation waits for no brand.

The rapid advancements in artificial intelligence (AI) are forcing brands to adapt fast or risk falling behind those already harnessing these powerful tools to amplify human creativity and scale operations like never before. But this isn’t just about technology. It’s about rethinking how we engage with consumers. AI is here to help marketers put the best of human creativity into action, not replace it. And the time to get started is now.

Finding a partner in creativity (not a replacement).

For all the excitement about AI’s creative potential in enterprise marketing, there’s an equal amount of worry and skepticism. Concern is understandable. Change brings challenges. But here’s the simple truth: AI doesn’t diminish the value of human creativity. It amplifies it. 

Great marketing has always been about clever, engaging ideas. And with AI, we can put those ideas – the thing that humans do best – into production with unprecedented efficiency and scale. Imagine a campaign that delivers personalised messages in multiple languages, tailored to cultural nuances, across every touchpoint. This isn’t a far-off dream, it’s a here-and-now reality that AI tooling makes possible.

Think of it like an advanced production line: just as robots in car factories amplify human engineering skills, AI enhances our ability to create, optimise, and deliver impactful marketing campaigns.

Earning the right to connect.

That’s important because today’s customers are more discerning than ever – and always ready to swiftly decline push notifications or location tracking requests. Unless they can see actual value. So brands must earn the right to communicate with their audience by offering genuinely valuable, contextually relevant, and creative experiences.

This is where lifecycle marketing shines. By leveraging every touchpoint – from initial engagement to ongoing relationship management – brands can nurture prospects and build trust. AI tools enable marketers to use data intelligently, crafting campaigns that feel natural and personalised. The result? Customers are more likely to share their data and engage, creating a virtuous cycle of trust and value.

Cutting through the martech noise.

The martech landscape is saturated with promises of creativity, productivity, and efficiency. But not all tools are created equal. Marketers must discern between platforms that truly enable innovation and those that merely repackage existing capabilities.

One way to navigate this complexity is by examining a tool’s provenance. What was it originally designed to do? Understanding a platform’s core strengths helps marketers identify solutions that align with their needs, whether it’s enhancing creative output, streamlining production, or optimising delivery.

But if the history of technological progress has taught us one thing – from the printing press and automation-led car factories to the internet and social media – early adopters gain an unmistakable competitive edge. AI is no different. Brands that take the time to experiment with AI and learn from the experience today will be the ones defining the standards of marketing excellence tomorrow.

Delivering nuance at scale.

There are plenty of all-in, early-adopter marketers out there, diving into AI technologies and language is everything in effective communication. Sophisticated language connects, inspires, and persuades. But language’s ability to deliver real impact is built on nuance. What works with one person, in one culture or context may fall flat in another.

AI empowers brands to adapt their messaging to resonate with diverse audiences. For example, a message about a limited time offer may require entirely different phrasing and tone depending on the target audience’s language and culture. Scaling this level of personalisation across channels and markets is a monumental task for humans. But it’s a perfect fit for AI. 

Get the combination of human talent and machine capability right and the result is engaging communication that’s as respectful as it is relevant.

Overcoming complexity and amplifying potential.

Brands must compete for attention across countless channels, each with its unique demands and audiences. Traditional approaches to campaign management simply can’t keep pace with customer expectations.

While AI can help to free up marketers and creatives by automating repetitive tasks and optimising campaign timing and delivery, some companies seem content to view AI simply as a means to replace human workflows. But this approach is shortsighted. The real power and long-term value of AI lies in its ability to do things humans could never do.

For instance, AI can generate thousands of message variations, each optimised for a specific audience segment, in seconds – then analyse the performance of that campaign at a scale no human team could achieve. This level of scale and precision is simply unattainable without AI.

Brands must shift their mindset from viewing AI as a productivity assistant to seeing it as a multiplier of human creativity. When used effectively, AI doesn’t just make tasks easier, it can make entirely new possibilities an everyday reality.

One key takeaway.

The question isn’t whether to adopt AI but how quickly and effectively you can integrate it into your operations. The brands that embrace this moment – experimenting, learning, and iterating – will be the ones putting the best of human creativity into production at scale, owning the next era of marketing innovation, and resonating in our imaginations.

Dive in, explore what’s possible with AI, and share your creative discoveries with the world. Because if you’re not doing it, your competitors surely are.

The insights in this series are based on conversations and learnings you can find in our new podcast, “The Array.” Want to learn more? Catch up with our third episode, featuring Daniel Head, CEO, Jacquard.

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Our latest offering tailors your messaging to each individual and delivers contextually relevant language that resonates with every customer – every time

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“Technological development is not going to stop and wait for anyone.”

“You have to dive in and have a go.”
_

Daniel Head, CEO, Jacquard, joins The Array to discuss how AI technologies can help experimentation-minded enterprise brands to:

• Put the best of human creativity into production at scale (11:30)
• Reach more customers with more relevant content (19:35)
• Deliver significant and sustainable creative value (22:13).

Host

Toby Coulthard, CPO, Jacquard Jasper Pye, CTO, Jacquard

Guest

Daniel Head, CEO, Jacquard

Listen to the full episode →

Today’s consumers demand more than just a “Hello, {{first name}}” from the brands they engage with.

They expect authentic, meaningful personalisation that speaks to their needs and preferences. Unfortunately, traditional methods of personalisation have often fallen short, relying on generic rules and resource-intensive processes that fail to deliver true 1:1 experiences. That’s where Jacquard’s latest innovation, Personalised Campaigns, comes in.

Jacquard’s Personalised Campaigns is made up of two interconnected systems: contextual content generation and an advanced audience model. The contextual generation system draws on multiple data contexts—brand, campaign, personal, and product—to generate a rich library of personalised messages. Then, the audience model intelligently selects the best message variant for each individual, learning from customer engagement signals to continually improve. This means every campaign is crafted not only to reach your audience but to connect with them in a meaningful, evolving way.

In this video, Alon Krifcher, Jacquard’s Director of Sales Engineering, explores how Jacquard’s Personalisation Engine is transforming marketing campaigns to build stronger audience connections.

Artificial intelligence (AI) is transforming the marketing landscape and enterprise brands face a big challenge: how to build trust in generative AI while protecting unique brand identities and navigating the risks of bias, inaccuracy, and loss of authenticity. So how can marketers and brand leaders find their way forward? It’s time to embrace experimentation, refine AI’s role in creative processes, and cultivate a balance between human ingenuity and automated efficiency. Here’s how brands can establish trust in AI and unlock its potential for growth.

Mapping the route toward brand trust in AI.

Despite profound excitement, generative AI’s ascent has also been marked by equal amounts of skepticism – particularly around issues with “hallucinations”, biases in training data, and potential copyright issues. CMOs are highlighting misinformation or disinformation as a top concern, and agencies are focused on copyright infringement risks. 

Trust in AI will also grow as technologies improve, offering tools to refine how AI models learn brand nuances, tone, and audience preferences. But marketers must begin working now to build mechanisms that ensure AI aligns with brand values and audiences. This ensures relevance and minimises risks, making marketers more confident about incorporating AI into creative workflows.

Combining people and platforms for creative impact.

Much like autonomous driving, generative AI is a remarkable feat of data and engineering. But both still require attentive and consistent human oversight and judgement to avoid errors. AI also needs that still-unique spark of human inspiration. 

And it’s this synergy between human creativity and machine efficiency that will be essential for brands looking to deliver marketing that cuts through, connects with consumers, and promotes sustained affinity for a distinctive and compelling brand. AI offers unmatchable speed and scale, automating repetitive tasks that amplify messaging while enabling human creatives to focus on ideation and storytelling. (The stuff we’re best at.) By combining talent with technology, brands can execute campaigns that resonate with individual consumers – moving them emotionally, functionally, and transactionally.

Instead of seeing generative AI tools and technologies as the foundation for one big do-my-marketing button, marketers should view AI as a partner – augmenting human creativity, not replacing it. AI will always be best at generating and personalising content at scale while humans curate, contextualise, and infuse campaigns with authentic brand voice and intent.

Avoiding the abyss of mid-tier mediocrity.

One big pitfall of over-reliance on generative AI is the potential for getting lost in an autonomous sea of sameness – where brands run the risk of all looking and sounding alike, and losing their distinctive voice or essence. Marketers must work to embed their unique tone, vibe, and value propositions into AI models to prevent this from happening. This will help to ensure each campaign reflects a brand’s true and wonderfully prickly identity, even as content gets personalised for different audiences and tailored to individual interests and needs.

The challenge is striking a balance: leveraging AI to create relevant, individualised content without diluting brand consistency. Brands should set clear boundaries for AI to operate within while maintaining the flexibility to adapt to customer preferences.

Experimenting your way to AI literacy and confidence.

There are plenty of all-in, early-adopter marketers out there, diving into AI technologies and excitedly building new creative production workflows. But if you’re a cautious marketer worried about the risks of AI (or simply lacking the same level of knowledge around and fluency in AI tooling to feel confident making large-scale recommendations and changes), trust in AI should be built through a phased approach to experimentation:

• Start with text-based applications like ad copy – quick to iterate and less prone to copyright concerns
• Progress to evergreen content like website copy
• Eventually, begin to experiment with visual assets, relying on rights-secured AI tools.

AI’s potential isn’t limited to consumer-facing campaigns. It can also streamline internal processes, from organising insights to automating research summaries. These ‘behind-the-scenes’ use cases provide a low-risk environment for brands to familiarise themselves with AI capabilities.

Finding balance in the future of marketing.

As AI tools evolve, the benefits of scale and efficiency will make their adoption essential for competitive brands. AI enables marketers to execute campaigns across multiple channels, meeting the demand for fresh, engaging content. But its true power lies in augmenting – not replacing – human creativity.

Marketers should embrace AI as a tool to spark innovation, refine workflows, and drive measurable performance. This will enable them to engage audiences in ways that were previously unimaginable, maintaining their brand’s emotional connection while scaling their reach.

One key takeaway.

For brands ready to explore AI’s transformative potential, the path forward begins with trust, experimentation, and a steadfast commitment to creativity. The human-machine partnership isn’t the future of marketing. It’s the new normal.

The insights in this series are based on conversations and learnings you can find in our new podcast, “The Array.” Want to learn more? Catch up with our second episode, featuring Jay Pattisall, VP and Principal Analyst at Forrester.

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Jay Pattisall, VP and Principal Analyst at Forrester, joins The Array to discuss why generative AI should have a permanent place in the marketing toolkit. This is essential listening for do-more-with-less marketers looking to bring greater efficiency to the creative production process and drive better performance at scale.

Host

Toby Coulthard, CPO, Jacquard Jasper Pye, CTO, Jacquard

Guest

Jay Pattisall, VP and Principal Analyst at Forrester

Listen to the full episode →

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“Will there always be a place for human creativity?”

“What’s your advice to people who are cautious about AI adoption?”

_

Jay Pattisall, VP and Principal Analyst at Forrester, joins hosts Toby Coulthard and Jasper Pye to share expert guidance into how you can:

• Build the right combination of people and AI platform into the creative process (09:48)
• Avoid the “autonomous sea of sameness” (17:57)
• Safely experiment with generative AI technologies (26:52)
• Engage with consumers emotionally, functionally, and transactionally (32:48).

Host

Toby Coulthard, CPO, Jacquard Jasper Pye, CTO, Jacquard

Guest

Jay Pattisall, VP and Principal Analyst at Forrester

Listen to the full episode →

Once a cultural phenomenon unique to North America, Black Friday has exploded across the globe in recent years, creating a monumental commercial milestone in the annual retail calendar.

And it’s all about the discount. Sales, reductions, money off. Why not just ‘give it away’ for free? And for months, brands have been honing their Black Friday strategies, eager to maximise sales in the face of a global cost-of-living crisis.

When the average person feels they’ve got less money in their pocket, how do we make a case for them to spend their hard-earned salary, particularly when there are so many other places they could spend it? Why should they spend it with you, on your products, with your brand?

An obvious tactic is to discount heavily. That’s not new or news. But where some  brands might once have offered 25% off, this year many will stretch to 30%, 40% or maybe even 90%+ to encourage customers to part with their cash. After all, when disposable income is under increased pressure, many consumers won’t just need the hard sell, but a heightened sense of ‘value for money’ to justify the expenditure. And they need to feel like they’ve got a great deal.

But it’s time to challenge this notion of deep discounting in order to make sales. If you say 15% or 20% off well, maybe you don’t have to say 30%.

And what does this tell us? That language matters. Having the technology behind a campaign that can optimise language in real time, in line with its performance, or that can personalise emails and push notifications to resonate with what people really care about, is a powerful weapon.

Technology has to perform well given that we’re living in an attention economy. And let’s be realistic: we’re all going to be spammed to high heaven with deals come Friday 29 November.

Which means we need to pay more attention than ever to brand language, because it’s going to determine whether or not a customer opens an email chockful of offers.

But what are the benefits to limiting discounts, aside from keeping Chief Financial Officers happy? Especially when it’s about driving that bottom line forward in challenging economic conditions.

Oftentimes, discounting heavily and discounting again to get customers to click and purchase will cheapen a brand’s value. In some instances, it can even deter them from engaging with a brand and paying full price outside of sale – or silly – season.

Afterall, customers are fickle – and who can blame them? They will migrate towards the greatest perceived value. They’ll do their research, they’ll draw comparisons, and they’ll wait for brands and retailers to make their move.

But the impulse to shop around will be minimised if a customer feels like a brand is speaking to them directly, if it understands them, “talking their language”, surfacing just the right product at the right time; “And wait – with 20% off too? It’s like they know me. I feel seen. And now I don’t have to spend an hour trawling the internet for what I want because it’s right in front of me.”

Suddenly, smaller discounts speak greater volumes.

Black Friday is the moment to start building customer loyalty, to think about what a brand says and how it articulates it, and how it can be executed effectively without discounting so heavily that margins are completely eroded. Erosion is a critical pillar in this process. Because heavy discounting can also erode brand affinity and, in some instances, desirability.

But this can’t be reduced to brands thinking only about how they engage customers during the Black Friday rush. For maximum impact, they need to think about how they engage consumers and the language that inspires them all year round. They need to be wooed long-term, to cultivate an actionable understanding of them, and to build the right to make the approach when Black Friday comes around. Oftentimes it’s about steering customers towards the habits that revolve around a brand; whether that’s opening the monthly newsletter or engaging with a new augmented reality app function.

How do brands speak to consumers en masse but with heightened relevance at peak periods in the retail calendar? And how do they make sure customers feel like a brand is speaking to them as an individual?

The secret is to deploy the right tools to help brands produce effective, brand compliant messaging that speaks a customer’s language – and that does so at scale.

This is where Jacquard comes in. By generating consistently higher engagement and responses from consumers, we can offer brands brand language they trust – for compliance and performance. And trust is more than important: it’s the gateway to automation. When AI is generating and calibrating 30,000 plus language variants from a single prompt, trust is integral. But when that technology proves itself, and proves that it can be trusted, it revolutionises a brand’s ability to cut-through with customers on an individual basis, without having to discount so heavily that margins become non-existent.

This year more than ever before, brands need to embrace trusted language automation in order to unlock maximum value at this mission critical time of year.

Every brand wants to deliver a coherent, engaging, and impactful personalisation experience for their customers.

But realising that dream – and achieving seamless, effective personalisation at scale – has proven far more challenging in practice. Let’s explore why personalisation is so challenging, then highlight key strategies for success and discuss how enterprise marketers can navigate this complex landscape.

The differences between implicit and explicit personalisation.

At its core, personalisation can be divided into two categories: implicit and explicit. It’s essential to understand the different ways they work and the impact they can have when executed well – or done poorly.

Implicit personalisation.

This approach works behind the scenes, delivering content tailored to users based on their behaviours, preferences, or trends. For example, streaming platforms like Netflix excel in making intuitive recommendations based on viewing history. However, implicit personalisation can sometimes feel opaque – with users not fully understanding why they’re seeing specific content, potentially leading to trust issues or frustration.

Explicit personalisation.

This approach is more direct, clearly and openly connecting the dots for users. For instance, “You might also like…” or “Recommended because you liked X” messages in e-commerce show consumers exactly why they’re seeing a suggestion. This transparency can help to build trust and reinforce the value of personalisation.

Most brands operate within one of these buckets, but the ultimate goal should be to combine the two for a seamless, cohesive experience.

Why personalisation is so difficult.

Personalisation requires more than good intentions and technology investments. Here are key reasons why many companies struggle:

Measurement challenges: Identifying the right success metrics and avoiding false positives is a persistent challenge.

Disconnected tech stacks: Many organisations have powerful tools—CRMs, marketing clouds, and data platforms—but fail to integrate them effectively.

Content complexity: Personalisation exponentially increases the need for tailored content across various segments, channels, and contexts.

Change management: Personalisation demands cultural and operational shifts, which can be difficult to implement across teams and stakeholders.

The four layers of personalisation.

To get personalisation right, companies must focus on four fundamental layers:

1. **Who.**Define your segmentation and cohort strategy. Are you targeting based on demographics, preferences, or behaviours?
2. **When.**Decide whether to personalise at planned moments (like a product launch) or triggered moments (based on real-time actions).
3. **Where.**Determine which channels or touchpoints will deliver personalised experiences, from email campaigns to in-store interactions.
4. **What.**Identify what you’re personalising—content, offers, product recommendations, or messaging tone.

Mastering these layers requires aligning technology, data, and creative processes to ensure consistency and relevance across the customer journey.

The content challenge: frameworks and automation.

One of the most daunting aspects of personalisation is content production. As brands move from one-to-many to one-to-few and one-to-one communication, the demand for highly specific content grows exponentially. To overcome this, enterprise marketers must:

• Develop clear frameworks: Establish guidelines for messaging, imagery, and tone that align with personalisation goals.
• Leverage automation: Use AI-powered tools to scale content production and delivery while maintaining quality.

Automation not only reduces the manual workload but also enables marketers to focus on strategy and optimisation rather than execution.

Success metrics: measuring what matters.

Personalisation efforts should be guided by a clear hierarchy of success metrics. Here’s how to approach it:

• Avoid false positives: Misinterpreting data—such as assuming first-name usage is ineffective—can lead to flawed strategies.
• Incentivisation of KPIs: Focus on metrics that reflect the broader business goals rather than just immediate performance (e.g., open rates).
• Brand impact: Balance performance-driven metrics with qualitative measures that reflect how personalisation enhances brand perception.

Ultimately, personalisation should create value for the customer and the brand, driving engagement and loyalty in the long term.

The future of personalisation: optimisation and federation.

As personalisation technology evolves, the next frontier lies in optimisation and federated data models. Imagine seamlessly integrating first-party data, neural networks, and predictive analytics to deliver hyper-relevant experiences in real time. This approach requires:

Dynamic feedback loops: Use real-time feedback from users to refine personalisation strategies and remove friction from their experiences.

One key takeaway.

Good personalisation is equal parts art and science. You need the right technology, robust processes, and engaging creative – all built on a deep understanding of who your customers are as real, individual people with unique needs. And while no single brand has brought it all together yet, the journey toward better personalisation is worth taking. 

By aligning customer data, strategy, content, and automation, enterprise marketers can move beyond fragmented and frustrating engagement efforts to deliver on personalisation’s full potential – with transformative experiences that are both relevant and remarkable.

The insights in this series are based on conversations and learnings you can access in our new podcast, “The Array.” Want to learn more? Catch up with our first episode, featuring Scott Zalaznik, Digital Advisor and ex-CDO of adidas.

Subscribe on spotify

Be the first to see true 1:1 personalisation in action

Our latest offering tailors your messaging to each individual and delivers contextually relevant language that resonates with every customer – every time

Book a demo

Scott Zalaznik, Digital Advisor & ex-CDO of adidas, joins The Array to explore the differences between implicit and explicit personalisation, the right way to use customer data, and how brands can leverage technology to better connect with individual customers and drive long-term success, at scale.

Host

Toby Coulthard, CPO, Jacquard Jasper Pye, CTO, Jacquard

Guest

Scott Zalaznik, Digital Advisor & ex-CDO adidas

Listen to the full episode →

Jacquard launches new AI and MarTech podcast to bring clarity to enterprise marketing strategies.

• New podcast launches from Jacquard exploring the AI and MarTech trends shaping enterprise marketing strategies right now
• Guests include thought leaders from across the AI and MarTech landscape, including Scott Zalaznik, ex-CDO of adidas
• Episodes will explore new AI and marketing technologies and industry trends, and provide practical guidance on how businesses and brands can navigate change and reach more customers more effectively.

London – 12 November 2024: Jacquard, the enterprise tooling for brand messaging that resonates everywhere, has released its new industry-focused podcast, ‘The Array’. The podcast explores the rapid evolution of AI and MarTech, what the changes mean for enterprise marketers, and the new, more personal connections being created between brands and customers.

Actionable insights.

MarTech companies are making big promises about new AI products and AI bolt-ons. ‘The Array’ aims to cut through the hype and provide tangible value to enterprise marketers. How? By inviting true AI and MarTech thought leaders to share diverse perspectives and practical, impactful insights focused on increasing customer lifetime value. 

In season one, hosts Toby Coulthard, Chief Product Officer of Jacquard, and Jasper Pye, Chief Technology Officer of Jacquard, will be joined by:

• Scott Zalaznik, Digital Advisor & ex-CDO of adidas
• Jay Pattisall, VP & Principal Analyst at Forrester
• Daniel Head, CEO of Jacquard
• Lucy Colback, Tech Writer for The Financial Times

Scott Zalaznik will get the conversation started on ‘The Array’, examining implicit versus explicit personalisation, how to generate tailored content at scale, choosing the right success metrics, and what good personalisation looks like.

A second season of ‘The Array’ is already in production – with a stellar lineup of guests on hand to answer more probing questions and bring greater strategic clarity to the AI and MarTech conversation.

Snackable content.

The podcast series will feature four full-length episodes (approx. 30-40 minutes) alongside shorter, snackable edits (5-10 minutes) for those looking to get straight to key takeaways . New episodes will be added to Spotify and YouTube every Tuesday.

Co-host Toby Coulthard explains: “There is no single source of truth when it comes to what’s next for AI and MarTech. What there is, is deep intellectual thinking, profound innovation, and unparalleled creativity. ‘The Array’ has created an inviting space for fresh technology and marketing ideas and actionable insights that brands can use to build relationships with customers that deliver lifetime value.”

Lucy Colback, Journalist, Financial Times, comments: “‘The Array’ is a new and welcome voice in the discussion around AI, particularly in MarTech. It’s a vital topic across commerce given the speed of AI development and volume of potential applications – but it’s never worth sacrificing customer trust in the pursuit of technological progress. Most importantly, a business cannot maximise the value of AI without first understanding the problem they’re trying to solve. This is where ‘The Array’ comes in, providing businesses with actionable solutions to the complex challenges they face every day.”

Keep up with the conversation.

‘The Array’ is available now on Spotify and YouTube.

ENDS

About Jacquard

Jacquard is purpose-built architecture for on-brand messaging that resonates wherever people are. Our enterprise tooling unlocks the benefits of AI with speed and scale, language expertise, distribution across all major channels, and performance. Leading global brands like Currys, Pet Supplies Plus, and Walgreens see sustained brand affinity with Jacquard.

For media enquiries, please contact Melissa Scarlett: melissa.scarlett@jacquard.com / (+44)7921 623469.

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“What are the right success metrics?”

“You’re winning clicks, but at what cost?”

_

Scott Zalaznik, Digital Advisor & ex-CDO of adidas, joins hosts Toby Coulthard and Jasper Pye on The Array to answer complex content questions. Get clear, actionable insights into:

• Implicit vs. explicit personalisation (5:04)
• Scalable content production (10:56)
• Identifying the right success metrics (15:08)
• Whether AI will take Jasper’s job (31:20).

Host

Toby Coulthard, CPO, Jacquard Jasper Pye, CTO, Jacquard

Guest

Scott Zalaznik, Digital Advisor & ex-CDO adidas

Listen to the full episode →

The summer holidays have drawn to a close. That familiar back-to-school feeling fills the air. And for the modern marketer, now is the perfect time to start gearing up for the customer engagement challenges that lie ahead. 

Fortunately, Jacquard is ready to unbox a range of exciting updates to our product suite. These improvements are designed to help brands deliver more impactful and efficient personalised content at scale. See what’s possible with:

• Personalised Campaigns. Create and serve up content tailored to each individual customer at scale.
• Redesigned platform experience. Generate content and design content experiments across multiple channels and languages from a single brief. 
• New languages. Expand your global reach with Jacquard’s Generation Engine, Language1 Creative, now supporting Modern Standard Arabic and LATAM Spanish.
• Enhanced CEP integrations. Optimise your campaigns across more channels and streamline content delivery with upgraded integrations with leading CEP platforms.

Read on to explore all the new features and benefits. 

Personalised Campaigns.

What is it?
Launched earlier this year, Personalised Campaigns was built to deliver true 1:1 personalisation at scale. Powered by Jacquard’s Personalisation Engine, Contextual1, users can integrate product, user, and contextual data to generate and allocate hyper-relevant messages for every customer.

**What’s new?**Our Personalised Campaigns solution now includes in-platform reporting. Track the number of personalised messages served to your audience and measure key performance metrics. Analyse how your messaging adapts based on different data dimensions, such as product catalogue data and customer profiles, and compare performance between personalised and non-personalised message variants to see the impact personalisation has on your brands ability to engage 

**Why does it matter?
**Research from McKinsey shows that at least 71% of consumers expect personalised experiences. But traditional personalisation methods often fall short due to their reliance on broad segmentation and error-prone merge tags. Personalised Campaigns delivers sophisticated, context-aware messaging to create a more relevant and engaging customer experience.

Redesigned platform experience.

**What’s new?**Jacquard’s new platform experience brings content creation and experimental design into one unified workflow. This enables users to develop complex lifecycle marketing campaigns across multiple channels, languages, and brands. All from a single brief.

**Why does it matter?**Your brand needs to meet customers wherever they are. But in order to do this, you also need to create and manage large volumes of content – tailored to different channels and audiences across complex, nonlinear journeys. And because customer preferences are constantly evolving, this must be done within a framework that supports testing and learning. 

Traditional copywriting teams can’t keep up with this volume. And AI copywriting assistance simply shifts the problem from content creation to curation. Jacquard’s new unified workflow meets the needs of modern marketing teams by enabling the rapid creation and optimisation of content across channels and languages. All while curating content for brand safety and performance at scale. 

Note: We’ll begin rolling out these updates across customer accounts from the end of September. Existing customers can contact their dedicated customer success manager with any questions.

New languages.

**What’s new?
**In addition to English, French, European Spanish, German, and Italian, Jacquard’s Generation Engine, Language1 Creative, now supports Modern Standard Arabic and LATAM Spanish. This expansion enhances our generation capabilities and gives the world’s marketers the ability to create on-brand content and run optimisation experiments in more languages.

**Why does it matter?**Speaking to customers in their preferred language is crucial for reaching diverse audiences all over the world. By incorporating Arabic and LATAM Spanish, Jacquard helps global enterprises to localise their marketing efforts at scale – and ensure their messaging resonates with customers who prefer their brand communications in a specific language. 

Enhanced CEP integrations.

**What’s new?**We’re thrilled to announce improved integration capabilities with our CEP partners, Braze and Airship. These updates allow you to automatically fulfil your CEP campaigns with Jacquard-generated content across a broader range of channels – including content cards, in-app messages, and mobile push notifications.

**Why does it matter?**CEPs excel in delivering brand messages across channels. And Jacquard’s expertise lies in the creation of high-quality brand messaging. Integrating these technologies gives marketers the tools to build and execute multichannel campaigns more effectively and at scale. Automatically push Jacquard-generated content into your CEP and leverage our patent-pending technology to adapt your messaging in real time for maximum impact.

Advancing automation for marketers

Personalised campaigns. A streamlined workflow. Expanded language support. And enhanced integrations. The product updates starring in our Summer Release 2024 mark significant steps forward in marketing automation. Marketers using Jacquard’s technology can create more content at speed, with richer context, across more channels. And deliver more impactful customer experiences at scale.

Want to get a closer look at our product updates?

Personalised brand messages are no longer just a nice-to-have feature in the fast-paced world of digital marketing; they’re essential to your engagement strategy.

But true personalisation involves more than just plugging a recipient’s name into a one-size-fits-all template. Your ability to nurture a profitable long-term connection with your audience is built on a more sophisticated approach. Here are five key tips from a computational linguist on how to craft personalised brand messages that truly resonate with your audience.

Tip 1: Embrace comprehensive personalisation dimensions.

Personalisation is about more than just adding a few extra data points into your messages. Effective communication demands richly tailored messaging, built on a wide range of data attributes and a clear understanding of each recipient’s specific context.

And that means looking beyond templated language to contextual language.

Templated language is found in traditional merge tags like “Hey {{first_name}}, you left something in your cart”. This approach tends to sound formulaic and impersonal – leading to reduced customer engagement.

Contextualised language goes beyond merge tags to allow for greater creativity and showcase brand personality more effectively – while also using additional layers of information that reflect a deeper understanding of the recipient’s situation. And by factoring in additional dimensions like seasonal language or product features, brands can tailor their language to better match an interaction with a customer’s interests.

For instance, fashion purchases may be driven by feelings and occasions. A personalised message for someone interested in the dress category might read, “Here’s exactly what you need to be party-ready this summer”. Meanwhile, tech purchases are typically influenced by product features when deciding between different models. A tailored message for a potential headphone customer could say, “Take another look at the HH123 noise-cancelling headphones. With 30 hours of battery life, you’ll be singing along all day long!” Leveraging contextual language enables brands to craft more engaging and relevant messages that resonate with their audience.

Tip 2: Master context and language nuance.

Find? Or discover?

Cheap? Or frugal?

House? Or home?

Language is filled with subtle nuances. The meaning of your message can shift dramatically depending on word choice and context. Crafting personalised brand messages requires an understanding of these nuances to avoid misunderstandings or irrelevant content. Because while you might have a “brilliant” high-quality product in the UK, customers in the US might wonder why you want people to think that product is visually striking or super smart.

• Industry context: Common retail phrases like “Snap up” or “Grab” wouldn’t be appropriate for customers in industries like insurance.
• Product context: A phrase like “Run don’t walk” may play with customers looking for new running shoes, but not make sense with someone shopping for a new bicycle.
• Environmental context: A cosmetics brand or fast food chain can tell customers about a new product line that’s “going viral”, but a healthcare provider must show greater consideration.

Contextualised language goes beyond the superficial to recognise a recipient’s unique qualities and mirror the subtleties of natural conversation. This tailored and thoughtful approach will always resonate better with prospects and customers than a generic blast that could apply to anyone.

Tip 3: Maintain your brand voice.

Tone and language are fundamental to your brand identity, directly influencing the relationships you develop with your customers. And as important as it is to tailor your messages to the needs and interests of each recipient, it’s even more vital to ensure that every message retains and showcases your brand voice. Because it can be far too easy to lose control of that voice – and undermine brand equity – by over-personalising your messaging.

Contextual messaging also gives your brand more opportunity to inject personality into your messaging. You can create variants that are tailored at an individual level – adjusting tones to deliver a more personalised and engaging experience for each recipient. All within the clearly defined parameters of your brand voice.

So a luxury fashion brand can avoid sounding inauthentic by using Gen Z slang like “slay” or “lit” – and strike the right balance between personalised language and a consistent brand tone of voice.

Tip 4: Leverage feedback for continuous improvement.

Personalisation should not be a one-off experiment. Effective personalised messaging relies on continuous refinement and optimisation. The brands that see profitable results from their efforts collect feedback and analyse performance data at every opportunity. This ensures they understand which messaging strategies are driving the most impact with different audience segments. 

For example, insights might reveal that specific phrases or tones are better at reactivating lapsed customers than acquiring new ones. By continuously testing and refining your messaging based on this feedback, you can enhance its relevance and effectiveness over time. 

Our customers have proven the value of this approach again and again:

• Loyalty-focused language resonates more with customers in higher tiers of a leading beauty brand’s loyalty scheme. 
• Female shoppers of menswear engaged more with lines that explicitly mention menswear than male shoppers.
• A top pet services brand found that dog owners respond to “Appreciative” sentiment, cat owners to “Surprising”, and owners of other pets to “Urgent” – While “Helpful” sentiment resonated with everyone.

Tip 5: Scale with machines.

Scaling personalised content for a large audience requires a balance between human creativity and machine efficiency. While humans excel at crafting nuanced, contextually aware messages, machines are invaluable for scaling content production.

Making intelligent use of large language models (LLMs) allows you to generate vast amounts of content quickly. But it’s also well known that these models can sometimes overlook subtle linguistic and contextual details essential for maintaining brand consistency. Google AI’s ‘pizza glue’ misstep illustrates the potential pitfalls of relying solely on machine-generated content. So it’s essential to take a considered approach that makes room for human oversight.

Bonus tip: Explore the power of a human and machine partnership.

Jacquard combines human expertise with machine efficiency to create personalised brand messaging that truly resonates. Our team of language specialists ensure that every piece of content not only reflects your brand’s voice but also leverages the power of LLMs to produce content at scale.

We start with a deep understanding of your brand’s tone of voice and previous content. This allows us to establish unique brand parameters tailored to your needs. We continuously gather feedback to refine and adjust our approach, ensuring your messaging remains fresh and relevant.

The qualitative nature of language can make it challenging to understand why certain words, emojis, and tones resonate better than others. But our team’s linguistic backgrounds enable them to expertly analyse and decipher language trends across audiences – offering actionable insights into what works and why. This deep understanding of language trends allows us to fine-tune content for each brand, ensuring that it remains impactful and authentic.

Integrating human creativity with machine efficiency enables us to deliver personalised content that connects with each individual while preserving your brand’s integrity. It’s a powerful approach to creating meaningful connections with your audience and represents the future of brand messaging at scale.

Crafting personalised messaging that truly resonates involves more than simply inserting names and product categories into pre-written templates. By embracing comprehensive personalisation dimensions, understanding language nuances, maintaining your brand voice, leveraging feedback, and combining human creativity with machine efficiency, you can create personalised brand messages that genuinely connect with your audience. As digital marketing continues to evolve, these strategies will help ensure your messaging remains relevant, impactful, and aligned with your brand’s identity.

Be the first to see true 1:1 personalisation in action

Our latest offering tailors your messaging to each individual and delivers contextually relevant language that resonates with every customer – every time

Book a demo

Personalisation. Digital marketing’s elusive Holy Grail.

Marketers have been striving to create individualised experiences for their audience, believing that tailored content leads to higher engagement, improved customer satisfaction, and better conversion rates.

But what exactly does ‘personalisation’ mean for marketers? And how is it evolving with the arrival of advanced AI technologies?

Traditional personalisation**.**

Personalisation has typically relied on a combination of basic customisation techniques and audience segmentation.

These approaches include:

Merge tags

The simplest form of personalisation, where placeholders in email templates are replaced with specific customer data like names or account numbers.

Conditional logic

Programming languages like Ampscript and Liquid Syntax – used in platforms like Salesforce Marketing Cloud, Shopify, and Braze – allow for more complex personalisation (e.g. content based on subscriber attributes).

Segmentation

Dividing a broad customer base into smaller, more manageable groups based on shared characteristics such as demographics, behaviours, or preferences. This allows marketers to create more targeted content for each segment.

Once a big step forward from one-size-fits-all marketing, these techniques fall short of true personalisation. A reliance on predetermined rules, limited data points, and broad categorisations typically results in messaging that can’t speak to individual customer nuances. And marketers aiming for greater precision through more granular segmentation often find themselves dealing with an unwieldy number of segments, each requiring its own content strategy.

The AI revolution: Jacquard’s approach to true personalisation.

With our innovative use of Large Language Models (LLMs) and multi-agent systems, Jacquard is redefining personalisation – elevating it from simple data insertion and group-based targeting to sophisticated, context-aware content generation.

Our advanced personalisation engine, Contextual1, enables us to push the boundaries of what’s possible. Here are seven keys to its success:

• Multi-agent systems for massive content generation. Instead of relying on fill-in-the-blank templates, Contextual1 employs multiple AI agents working in concert to generate entirely unique content for each recipient. This allows for previously unimaginable scale and depth of personalisation.
• Logical pairing of attributes. The engine understands the relationships between different data points and uses this insight to create coherent, contextually-appropriate content.
• Advanced language processing. Contextual1 ensures that the generated content is stylistically appropriate for the brand and individual recipients.
• Deep context understanding. By ingesting and analysing vast amounts of user data, Contextual1 can see a recipient’s full story (i.e. preferences, behaviours, purchase history, and even current circumstances) to craft truly relevant messages.
• Brand and product contextualisation. The engine also has a deep grasp of brand voice and product details. This allows it to generate content that feels authentic to the brand while being perfectly tailored to individual recipients.
• Segment of one. With a granular understanding of individual context and brand interactions, Contextual1 can create hyper-personalised content – for up to as many segments as there are customers.
• Deterministic post-processing. Our technology is unique in its use of deterministic, or symbolic-based, post-processing. This step minimises bias and hallucinations while ensuring that all messaging remains consistently on-brand.

The result? Marketing communications that are not only personalised and engaging but also accurate, unbiased, and perfectly aligned with brand guidelines. This combination of AI creativity and deterministic precision sets a new standard for personalised marketing content.

The impact of true personalisation.

Brands that choose to move beyond a basic “Hello {first_name}” or recommending products based on past purchases can expect to:

• Create nuanced, relevant messaging tailored to the customer’s current needs.
• Evolve with the customer journey – growing and changing as their relationship with the brand develops.
• Deliver consistent personalisation across all touchpoints – from email to push and SMS.
• Generate personalised content in real-time, responding to immediate context and triggers.

What’s next for personalisation?

Continued advancements will enable marketers to deliver relevance and resonance once possible only in direct human-to-human interactions. At a scale that can speak to entire customer bases.

The future of personalisation will be about understanding context, anticipating needs, and communicating in individual ways. Beyond just language – in imagery and even video. And with unwavering accuracy and brand consistency. 

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Be the first to see true 1:1 personalisation in action

Our latest offering tailors your messaging to each individual and delivers contextually relevant language that resonates with every customer – every time

Book a demo

Jacquard will share our new brand and show the world’s top marketers how to deliver messaging that resonates everywhere – at the Cannes Lions International Festival of Creativity 2024.

Sunglasses. Sandals. And scalable, hyper-personalised brand messaging. 

We’re bringing all the essentials for today’s enterprise marketers to Cannes’ famed Croisette – from 17-21 June. Will you be joining us?

Here’s a brief overview of Jacquard’s plan for Cannes:

After you’ve been greeted by our bold, colourful brand takeover of Nice Côte d’Azur Airport, you can dive into our inspiring programme of thought leadership events – curated in partnership Brand Innovators. The lineup features:

Day one:

Mastercard AI Track

Time: Monday, June 17 from 10am-2pm

Location: Mastercard Villa

Sponsor: Jacquard

Day two:

Fireside Chat: “You Say McDonald’s, We Say Maccas: Localizing A Global Brand”

Time: Tuesday, 18 June at 11:30am

Location: Armani/Caffè, Showcase Stage and Hospitality Lounge

Speaker: Jasper Pye, CTO, Jacquard

Morgan Stanley, PepsiCo, Ulta, Mazda and Hilton

Time: Tuesday, 18 June from 2-5pm

Location: Armani/Caffè, Showcase Stage and Hospitality Lounge

Emcee: Patrick Forquer, CRO, Jacquard

Day three:

Fireside Chat: AI Content at Scale

Time: Wednesday, 19 June at 12:40pm

Location: Beach Stage

Speakers: Daniel Head, CEO, Jacquard | Toby Coulthard, CPO, Jacquard | Michelle Froah, Global Chief Marketing & Innovation Officer, ETS

Day four:

Future of Creativity and Content Panel Discussion

Time: Thursday, 20 June at 11:45am

Location: La Mandala Beach

Speaker: Daniel Head, CEO, Jacquard

And our visionary CMO, Marissa Aydlett, will be attending a Women’s Leadership networking event. Don’t miss your opportunity to connect.

But we’re also eager to hear from the people who work with our purpose-built brand messaging architecture every day – and learn all that we can about its real-world impact. So we’ll be meeting with partners, clients, and prospects throughout the week.

Meet JACQUARD

Please get in touch with us via LinkedIn, Instagram, or X if you’ll be attending the festival. We’d love to meet up.

BEGIN YOUR JOURNEY

Want to begin your Jacquard experience before Cannes kicks off?

CEO Daniel Head helped to unveil our new brand in his article, “There’s a new name in brand messaging.” Read it now to learn more about the next chapter in our story – and see what Jacquard will mean for enterprise marketers all over the world.

Jacquard is here to deliver enterprise tooling for brand messaging that resonates everywhere.

This is the era of hyper-personalised brand communications. And it offers incredible rewards for the enterprise brands that can get personalisation right.

But for too many, it just means more channels. 

More campaigns. 

More languages. 

More journeys.

Brands are spending too much time on content creation.

Struggling to realise the potential of their cross-channel strategy.

And worried about the damage AI could do to their brand – if they fail to find the right AI solution.

Clearly, brands need help.

For the enterprise marketers looking to keep pace with personalisation demands – while staying on brand – it starts with answering three fundamental questions:

1. How do I access the right AI technologies?
2. How do I scale it into my business processes and workflows?
3. How can I trust AI to guide my organisation to automation?

Jacquard is the answer.

We are purpose-built for brand messaging.

Expertly calibrated.

Producing trusted content at scale.

Driving sustained brand affinity.

And we deliver access, scale, and trust.

Enabling enterprise brands to meet customers where they are. 

In a way that’s measurable.

In a way that shows respect. 

In a way that resonates.

Because brand growth and success in this era of hyper-personalisation is built on the ability to reach and engage people on their terms.

Those that don’t will be left behind.

Jacquard is enterprise tooling for brand messaging that resonates everywhere. 

And we can’t wait to show you all that’s possible.

Marketers looking to optimise their content have long relied onA/B tests to discover what works for their audiences. But this can only deliver real impact when you can trust the quality, accuracy, and diversity of the content being tested.

Goodbye to ‘blank page’ problems.

AI tools make it easier than ever to create multiple variations of text and images for A/B testing and multivariate testing. Marketers can experiment with different headlines, copy, visuals, calls-to-action, and other elements to determine what resonates best with their target audience.

And with generative AI tools like ChatGPT, the click of a button gives you as much content as you can handle. So AI gives you quantity, but what about quality? 

Is your AI-generated content good?  

‘Good’ can mean a few things: 

• Is it factually accurate? Foundational models like ChatGPT can ‘hallucinate’, generating false information.
• Does your messaging have the right meaning? AI isn’t trained on your brand and messaging, so it doesn’t know what you really want.
• Is it on-brand? You need an AI solution that can capture your brand tone of voice and write in your brand’s style.

But there’s one factor that matters more than all others: Does it perform? Are you inspiring people to feel, think or act in the way you intended? After all, that’s the whole purpose of marketing language – chosen with care to stand out and engage with a specific audience.

The keys to high-performance content. 

Many factors contribute to content performance. One important factor is language diversity and the use of different combinations of linguistic features such as words, phrases, emojis, sentiment, semantics, and syntactic structure. 

There is a positive correlation between language diversity and performance. On average, brands that experiment with diverse language in their subject lines enjoy an open rate uplift of 10% and a click rate uplift of 16%. 

But there are millions of ways to write a subject line – and no single formula for success.

Want to know what resonates best with your audience? You need to leverage a wide range of different linguistic features to be tested in a variety of combinations. Looking at individual linguistic variables in isolation (e.g. length or emojis) does not tend to find a correlation with performance.

Humans are not good at writing linguistically diverse marketing messages at scale. With cognitive bias, risk-aversion, and preconceived notions about what will and won’t work, most of us will instinctively lean on language which has performed well in the past, things that sound good to our own ear, or what others have used. 

And if we can’t remove bias in the content we create ourselves, we certainly can’t remove it from the content that we ask AI to generate.

Harnessing generative AI for marketing. 

Now that creation has been democratised and you can create all kinds of content with far less effort, you need to then determine what’s good and what’s bad. What works and what doesn’t. And the only repeatable way of doing this is to use a data-driven model.

Jacquard’s proprietary AI content generation technology exceeds what publicly available large language models (LLMs) can produce on their own. Our Deep Learning model, trained on nearly a decade of content experiments, takes the guesswork out of creating engaging content for your audience – and helps you to drive sustained brand affinity. 

We do this by analysing your content experiments to reveal the words, emojis, and sentiments different audiences respond to most. You can track the performance of your optimisation tests, both at the individual A/B/n experiment level and at the account level across multiple experiments. And the platform will show you exactly how much additional revenue you’re driving through NewCo’s content AI.

When it comes to performance, it’s not good enough to just create more content. Truly great testing comes from language diversity.

According to Forrester, only 6% of enterprises could be called “customer obsessed”.

These organisations are truly operationalising the idea of putting customers at the centre of everything they do to build sustained brand affinity.

Their reward? 1.6 times faster revenue growth. 1.7 times higher profit growth than their non-obsessed counterparts. And an enviable 98% customer approval rate. How can you join this group?

Customer engaged.

Customer committed.

Customer obsessed? 

Most enterprises could claim to be one of the first two. But only 6% of enterprises could be called “customer obsessed”. So what makes them different? 

Let’s explore the pivotal role technology, content, and messaging play in cultivating a customer-obsessed culture and look at how businesses can harness the power of generative AI tools to make this happen. 

The Power of Generative AI.

Generative AI is a powerful and scalable tool that can augment human processes. Here are some practical ways it can help your company to become customer obsessed – and enjoy the benefits: 

1. Personalised and customised experiences: Generative AI can analyse vast amounts of data to help you understand individual customer preferences and behaviours. This data-driven insight can be used to deliver personalised product recommendations, customised offers, and tailored messaging, creating a more engaging and relevant experience for your customers. 
2. Content and messaging generation: Tools like Jacquard can generate content and messaging tailored to your brand and audience at speed and scale. That means up to 2,500 curated message variants for all major channels in 30 seconds – and a 94% likelihood of beating the human control without optimisation. (Over time, 100% of our optimised campaigns outperform the human control.)
3. Predicting future behaviours: By analysing data, generative AI can predict future customer behaviours and preferences. This enables businesses to anticipate customer needs and interests, allowing for targeted and effective marketing campaigns. 
4. Sentiment analysis: All of the above can help you understand how customers respond to your brand and how their sentiment changes over time, helping you make data-driven decisions.
5. Ethical considerations: Finally, to build trust with your customers, you must ensure that you have an AI code of ethics in place.. Working with enterprise-grade tools like Jacquard can provide guardrails and workflow approvals to ensure ethical AI usage.

The role of content and messaging in customer obsession.

Customer-centricity is about prioritising the customer over the marketing channel. So a truly customer-obsessed business does whatever it takes to meet their customer with high-performing content, wherever they are.

Content like this is built on: 

1. Cross-channel consistency: Ensure your content maintains a consistent brand tone and message across all major channels. Whether it’s email, in-app messaging, or social media, the customer should have a unified brand experience. 
2. Personalised messaging: Deliver on-brand, diverse, safe, and optimised content that’s based on what’s proven to resonate with an audience or individual. Optimising content performance allows you to personalise and act on real-time data insights. 
3. Efficient, scalable automation: Enhance productivity with generative AI-powered automation. Doing so allows teams to shift from mundane tasks to more strategic ones and drive better long-term results. 

Enterprise brands that take this approach recognise the need to build a culture of testing, optimisation, and measurement. They maximise engagement with new and existing customers by creating more personalised, effective, and automated content at speed and scale.

What does that look like in practice?

Jacquard works with Currys, one of our customers and a leading omnichannel retailer, to streamline content creation and drive customer engagement. We did this by enabling them to automate experimentation to identify the most effective email elements – including headlines, calls to action, and subject lines.

Starting your journey to customer obsession.

Operationalised customer obsession isn’t built overnight. But a few simple steps can soon lead to rewarding results and genuine brand affinity. Here’s our advice for businesses looking to begin the transformation: 

1. Build a culture of testing and optimisation. Implementing a culture of experimentation enables you to measure the impact of each test and gather impactful insights from your data.
2. Use data to inform strategy. Use the data you collect to inform decision-making and personalise strategies across different areas of your organisation. 
3. Take a customer-first approach. Shift your organisation’s mindset to prioritise the customer in every decision and strategy. 

AI is a powerful ally in your quest to become customer-obsessed. It can be used to automate marketing content generation, ensure brand safety, and provide deep customer insights – and help you build lasting customer connections.

Large language models (LLMs) like ChatGPT should be great for creating marketing content. So why do they rarely hit the mark?

Jacquard recently established a set of best practices for creating your own AI solution for producing high-quality marketing content at scale – and discovered significant limitations of LLMs through our research. 

Let’s explore the limitations of LLMs and see why marketers should be looking for purpose-built architecture for brand messaging: 

1. Brand Safety

One of the most pressing concerns with LLMs is the risk of outputting biased or inappropriate language. While things have come on leaps and bounds since the early days of LLMs, including techniques like “reinforcement learning from human feedback” (RLHF), these solutions are still imperfect. 

Some open-source models may even provide raw, unfiltered output. In today’s climate, a single viral misstep can severely damage a brand’s reputation. Ensuring that your content aligns with your brand’s values and guidelines is crucial, but not always guaranteed with LLMs.

2. Factual Errors

One word: hallucinations. Another major issue is the tendency of LLMs to produce content that ranges from misleading to outright false, a phenomenon known as ‘hallucinations’. This happens because LLMs don’t operate from an underlying knowledge base but from probability distributions. They generate content based on what fits contextually rather than factual correctness. 

As a result, marketers may find themselves dealing with inaccuracies that could misinform their audience and damage their credibility.

3. Tone Errors

The nature of LLMs means that their output won’t always be appropriate, correct, or on-brand. Factual errors, tone mismatches, and other issues are common. Unlike traditional software development, where bugs can be fixed with code changes, addressing problems in LLMs requires modifying prompts or retraining the models. 

But these changes can affect the output across all inputs, potentially introducing new issues while solving existing ones. This unpredictability makes it challenging to ensure consistent quality and reliability in marketing content.

So while LLMs offer truly exciting possibilities for content generation, marketers need to be aware of the pitfalls.

Generative AI offers enterprises huge creative, efficiency, and accuracy advantages that traditional content production methods can’t match.

Marketers should eagerly explore implementing generative AI to capitalise on these benefits. But enterprise marketers must bring the same level of scrutiny to evaluating AI content solutions as they do to any other enterprise application.

How to use this RFP template.

We’ve compiled a list of essential questions you need to consider when evaluating different AI content providers. These questions will help you better understand your requirements and assess the capabilities, reliability, and suitability of different AI content providers in relation to those needs.

Simply download a copy of the template in your preferred format and share it with the vendor(s) you are assessing for them to complete.

Microsoft Word format

Download

Google Docs format

Download