{"id":6989,"date":"2026-05-24T18:23:20","date_gmt":"2026-05-24T11:23:20","guid":{"rendered":"https:\/\/adtek.agency\/ai-in-fashion-marketing-case-study\/"},"modified":"2026-10-20T22:55:16","modified_gmt":"2026-10-20T15:55:16","slug":"ai-in-fashion-marketing-case-study","status":"publish","type":"post","link":"https:\/\/adtek.agency\/en\/ai-in-fashion-marketing-case-study\/","title":{"rendered":"Case study: an AI playbook for fashion and beauty marketers"},"content":{"rendered":"

Updated on October 19, 2026: reviewed and updated the data.<\/em><\/p>\n

Marketers are no longer just “experimenting” with AI. Many of them have started to treat it as a core part of the way they operate every day. Used the right way, AI can raise productivity and give human creativity more room to work.<\/p>\n

This article summarizes a case study by The Business of Fashion (BoF) on AI in fashion marketing and beauty marketing. It focuses on how teams can streamline their workflows with AI while keeping their brand identity and the “human” element of marketing intact.<\/p>\n

Marketing in the fashion and beauty industries is going through a real transformation thanks to AI. The technology is now having an effect on almost every single stage of the marketing journey.<\/p>\n

At the top of the funnel, where brands fight for attention, labels such as Prada and Valentino have used AI to create campaigns that stand out in a “sea of content” and are big enough to spark wide discussion, even if not every reaction is positive. Other brands, such as Beekman 1802, focus on using AI to make sure their products show up when people look for skincare products on AI search platforms.<\/p>\n

Further down the conversion funnel, AI is used to refine and personalize marketing messages that guide customers, step by step, toward a purchase. Fashion e-commerce platform Zalando, for example, has personalized content around the fashion trends in each major European city to raise interest and conversion rates.<\/p>\n\"Case\n

AI is also giving brands entirely new ways to measure marketing performance. That ranges from analyzing a video second by second to find what needs to improve, to measuring the “halo effect” of communication campaigns and media budgets so brands understand exactly what is lifting sales both online and offline. All of this shows that today’s AI tools are helping brands compete far more effectively than before.<\/p>\n

AI also carries plenty of risk. Consumers are still fairly skeptical of the technology, which means a brand that applies AI in the wrong way can easily end up facing a backlash. Companies also need to avoid trading away creativity just to move faster or save money. For marketers, who are the people responsible for telling the brand’s story, striking a balance between adopting new technology and keeping creativity that carries a human touch is especially important.<\/p>\n

As Alexa Ritacco, Chief Marketing Officer of Goop, puts it: this is not a story where you have to choose between scaling up and protecting your brand identity and creative quality.<\/p>\n

This case study looks at the most effective ways to bring AI into everyday workflows so that marketing teams sharpen their strategic thinking and creativity without damaging the brand’s image.<\/p>\n\"Case\n

It draws on real examples from a range of brands: Goop and Beekman 1802 in beauty, French fashion label Maison Kitsun\u00e9, luxury resale platform The RealReal and e-commerce platform Zalando. The article shows how these businesses are using AI to save time and money. More importantly, they treat AI as a supporting tool that sparks new ideas and builds momentum for distinctive creative thinking. It is not there to replace the people doing the work.<\/p>\n

For brands that want to get more out of their marketing budgets and build deeper connections with customers, AI is becoming an extremely powerful tool. Used properly, it can help hit business goals more efficiently and also bring the “human” side of marketing further into the foreground.<\/p>\n

Market context: the new AI in fashion marketing toolkit<\/h2>\n

When H&M announced in March 2025 that it would use “digital twins”, AI-generated replicas of real models, in some of its advertising campaigns, the brand ran into a strong wave of opposition. Consumers felt uncomfortable looking at AI-generated images of people, while the fashion industry raised concerns about the jobs of models, photographers, makeup artists and the wider image production crew.<\/p>\n\"Market\n

David Baker, Chief Revenue Officer (CRO) of Beekman 1802, recalls the mood at the time: the general feeling in the market, and in his own team, was that AI was coming to take their jobs.<\/p>\n

Even so, Baker says that only a few months later, that fear had gradually turned into a mindset of “going all in on AI”, with the team looking for ways to use the technology to work more strategically and more effectively.<\/p>\n

AI has since become an important part of day-to-day marketing activity at many companies. From brainstorming ideas and producing campaign assets to tracking performance, AI shows up at almost every step. Businesses had in fact been using machine learning for tasks such as personalizing experiences for many years. But the arrival of large language models (LLMs) and generative AI tools such as ChatGPT sharply accelerated the adoption of AI in marketing, because these tools are easy to use and can be rolled out widely.<\/p>\n\"Market\n

According to Jasper’s State of AI in Marketing 2026 report, a survey of 1,400 marketers, 91% of marketing teams now use AI, a sharp rise from 63% the year before (Jasper, January 2026<\/a>).<\/p>\n

One reason behind this trend is the growing pressure on marketing teams. Teams have to manage content from both the brand and creators across a large number of digital and offline channels, which are more fragmented than ever. All of that makes the work of producing huge volumes of content, tracking how it performs and optimizing it continuously more and more complicated.<\/p>\n

Today’s marketers need to personalize their messages for each customer segment, and they also have to test many versions of their content on platforms such as Instagram to find the best performer and improve ROAS (return on ad spend).<\/p>\n

With AI, brands can quickly produce countless versions of the same piece of content. According to Jasper’s survey, ideation is still the most common AI use case (56%), but a growing share of marketers (51%) use AI to build campaigns made up of many assets across multiple formats and channels. That frees marketing teams to spend more time on top-of-funnel brand campaigns or breakthrough videos, instead of sitting there “changing 150 versions of a headline on the same image”, as Alexa Ritacco of Goop put it.<\/p>\n

These top-of-funnel campaigns are becoming more important as brands compete to be “recommended” to shoppers by AI platforms such as ChatGPT, Google Gemini and Claude while people shop online. Brands have little direct control over whether an AI system chooses to give priority to their products. But if the brand’s storytelling and its wider brand ecosystem communicate its core value clearly at every touchpoint, it has a better chance of appearing in front of the right customers.<\/p>\n

AI is also moving past a handful of isolated tasks and into a phase where it is built into the entire marketing process. Loreal Lynch, CMO of Jasper, calls this the “operational era of AI”, in which AI is embedded at every layer of the marketing funnel.<\/p>\n

In 2025, most of Jasper’s clients were still at the AI testing stage. Now they have started to form a clear picture of how AI agents will be built into their operations in the future.<\/p>\n\"Market\n

Luxury resale platform The RealReal has taken the initiative and rebuilt its entire marketing process around AI, with the aim of saving time and running its operations more efficiently.<\/p>\n\"Market\n

Lindsay Ferstandig, Senior Vice President of Strategy and Marketing at The RealReal, explains: “Our thinking quickly moved on from simply ‘testing AI’ to building an AI-supported operating ecosystem that creates momentum for growth across the whole business.<\/p>\n

“We no longer see AI as a tool for optimizing one small step in the marketing funnel or a single operational process. What we care about is how to apply AI across the entire resale ecosystem.”<\/p>\n

Restructuring processes around AI is far from simple, though. Many companies still struggle to integrate AI into their workflows and to get measurable value out of the technology.<\/p>\n

In PwC’s 29th Global CEO Survey, published in early 2026 and covering 4,454 CEOs in 95 countries and territories, 56% of CEOs said their companies had seen neither higher revenue nor lower costs from AI over the previous 12 months (Search Engine Journal, January 2026<\/a>).<\/p>\n

To adapt, large groups such as Kering and Lululemon have started hiring a Chief AI Officer to rebuild how they operate. According to Jasper, about 34% of marketing teams also plan to hire an AI Transformation Lead within the next 12 months.<\/p>\n

That hiring priority ranks second only to specialists in visibility on AI search engines, a discipline known as Generative Engine Optimisation (GEO), which 40% of teams plan to hire for.<\/p>\n

Companies may also have to change their whole organizational structure in order to adapt to AI. Zalando, the German fashion e-commerce platform and one of the early movers in bringing AI into its entire marketing process, says many of its teams have had to restructure so that AI takes over the manual, time-consuming work of the past and marketers can focus more on strategic tasks.<\/p>\n\"Market\n

For brands, the ability to move quickly and flexibly in the future will depend on how fast they adapt to a new way of working, one where people operate alongside AI processes: setting the strategy, giving creative direction and controlling the quality of the output throughout.<\/p>\n

Jasper’s Lynch says: “Marketers used to be the ones doing the work. Now they are moving into a role of managing and supervising.”<\/p>\n

On top of this, companies also have to adapt to new legal rules that govern the use of AI. In the EU, from August 2, 2026, Article 50 of the AI Act requires content generated by AI systems to carry machine-readable marking, and businesses must disclose when they use deepfake content (images, audio or video that simulate real people or events). The United States has no federal law yet, but New York State passed a law in December 2025, effective June 9, 2026, that requires advertisements to clearly disclose the use of AI-generated “synthetic performers” (Cooley, January 2026<\/a>).<\/p>\n

With regulations still changing constantly, Anthony Lupo, chairman of law firm ArentFox Schiff, offers simple advice: “When in doubt, disclose the use of AI.”<\/p>\n

So brands need to be careful about how they label AI content, and they also have to think hard about whether AI is really the right creative tool for each individual project.<\/p>\n

Donatas Smailys, CEO and co-founder of creator marketing agency Billo, says AI can be a useful tool for pushing the limits of creative production. For content that needs to convey a real experience or capture the human element, though, a traditional shoot sometimes still delivers better results and more authenticity.<\/p>\n\"Market\n

Strategy: building an AI marketing plan<\/h2>\n

1. Smart targeting<\/h3>\n

Before launching a new campaign, the first thing a brand needs to settle is who it wants to reach. AI is helping marketers find the customer groups most likely to respond well to the brand’s message.<\/p>\n

In the past, customer segmentation used to be fairly “broad” and quite basic. It relied mostly on age, gender and location, or on a few simple “customer personas”. According to Beekman 1802’s David Baker, those personas were often built from “a survey of about 1,000 people nationwide, or just three marketers sitting in a room brainstorming”.<\/p>\n

Today, marketers use AI to build customer profiles that are far more detailed and much closer to reality. AI can combine data from shopping behavior, purchase history and many other sources to paint a much clearer picture of who the brand is actually selling to.<\/p>\n\"Smart\n

PMG’s in-house AI platform, “Alli”, which serves brands such as Ralph Lauren and Lilly Pulitzer, lets brands build “living personas” that keep changing with real customer behavior and update themselves automatically over time.<\/p>\n

Using data on entertainment preferences, favorite influencers or the sports customers follow, brands can create many different kinds of persona. One example is the “aspirational family trendsetter”, a head of household who loves fashion and wants to keep up with new trends. Marketers can then ask the AI whether a specific marketing idea is a good fit for that customer group.<\/p>\n

Beekman 1802 also uses Bezel AI, a platform that mines Shopify data and more than 14 years of digital consumer behavior to build five AI personas that represent the brand’s core customer groups.<\/p>\n

Two of the main ones are:<\/p>\n

    \n
  • “Healthy Hannah”, a customer group focused on health and longevity<\/li>\n
  • “Luxury Linda”, a group that loves premium skincare<\/li>\n<\/ul>\n

    The marketing team can interact directly with each of these AI personas to get a better understanding of each group’s preferences, behavior and buying motivations.<\/p>\n

    By combining those personas with sales data from Prescient AI, a cross-channel marketing measurement tool, Beekman 1802 can pinpoint whether a Meta or Google campaign aimed at “Healthy Hannah” is really generating the revenue it was expected to.<\/p>\n

    For many brands, building their own customer personas with AI matters even more now that Meta recommends shifting the focus from niche targeting to creative diversification, while audiences that are too narrow tend to push delivery costs up.<\/p>\n

    Rather than rewarding very specific targeting, Meta now favors brands that test many different creative versions built around their main customer personas.<\/p>\n

    Goop’s Alexa Ritacco says: “They’ll penalize you a little if you target too granularly.”<\/p>\n

    So instead of relying entirely on ad targeting, brands are switching to this approach:<\/p>\n

      \n
    • Build creative based on the insights from each customer persona<\/li>\n
    • Then use AI to produce a large batch of different content versions<\/li>\n
    • Test them in Meta’s ad system to find the version that performs best.<\/li>\n<\/ul>\n

      To produce this creative, brands can either use external AI tools or turn to Meta’s own AI toolkit, which supports many features such as AI-generated voice-overs.<\/p>\n

      The RealReal also uses AI to improve ad performance through a “smart prospecting” tool. The tool helps the company identify who is likely to become a prospective buyer of luxury products, based on their shopping history and consumer behavior.<\/p>\n\"Smart\n

      As Lindsay Ferstandig told The Business of Fashion, performance marketing campaigns that use smart prospecting cost less than the average on Meta and are bringing in a significant share of The RealReal’s prospective customers from that channel.<\/p>\n

      Beyond finding the right customers, AI is also helping brands find the right creators to work with. AI platforms such as Heylist, Fohr, Agentio and Statusphere, along with Meta’s Advantage+ toolkit, let brands quickly evaluate creators based on the type of content they make, how well they fit the brand and its audience, their experience running ads, or how they perform compared with other creators.<\/p>\n

      The RealReal now uses Fohr to find suitable creators and predict how well a partnership will perform. That replaces the old manual approach, which relied mostly on follower counts or a best guess.<\/p>\n

      2. Driving brand awareness<\/h3>\n

      The role of AI in marketing campaigns<\/p>\n

      To launch its first collection under new creative director Abigail Smiley Smith, Maison Kitsun\u00e9, a fashion brand with French and Japanese DNA, worked with AI artist Sybille de Saint Louvent on a campaign inspired by the meeting of nature and city in the brand’s two “home towns”.<\/p>\n

      To tie the spirit of the two cities together smoothly, Sybille built an “Alice in Wonderland”-style campaign that tells the story of a man chasing a fox, the Maison Kitsun\u00e9 emblem, through Tokyo and Paris.<\/p>\n\"Driving\n

      The campaign launched in February 2026. It opens with the man waking from a dream and setting off after the fox through train stations, streets and gardens in Tokyo and Paris. The two worlds gradually blend together as he passes people wearing the brand’s coats, sweaters and sweatshirts, and skirts. At the end, the fox returns to the room from the opening scene and finds the man still fast asleep.<\/p>\n

      Sybille de Saint Louvent explains: “I’m not trying to reproduce reality exactly as it is. I always want to add a little twist.” Although she is known for her AI art, she stresses that using AI in a campaign must always have a clear reason and serve the creative idea.<\/p>\n

      The ability to create high-quality images and content is now one of generative AI’s biggest strengths. It gives brands a powerful extra tool for visualizing ideas during brainstorming, producing visuals faster and streamlining many creative marketing tasks.<\/p>\n

      AI comes with plenty of risk as well, especially since many people online are still wary of content that has been generated by AI.<\/p>\n

      According to Jasper’s Loreal Lynch, brands should treat AI as a “creative accelerator”, a tool that speeds up creativity rather than replacing human creative thinking. Beekman 1802, for example, uses AI to generate ideas for ad copy. The tool can quickly produce dozens of concepts for the team to review, assess and develop further.<\/p>\n

      As David Baker sees it, AI speeds up the creative process instead of leaving the team stuck with “writer’s block”, where coming up with 20 ideas can sometimes take a very long time.<\/p>\n

      Zalando uses AI with a similar goal in mind but applies it in a different way. Its Trendspotter tool uses AI to analyze standout fashion trends in major cities such as Paris and Berlin, then suggests campaign concepts that match products sold on the platform.<\/p>\n\"Driving\n

      Brands can of course also use AI to create the imagery for a campaign. This is an area that calls for particular care, though, because even if consumers only “think” AI was used, the brand can still face a backlash.<\/p>\n

      Guess, Valentino, Gucci and Prada have all been criticized over suspected AI use, including in cases where there was no clear evidence that AI had actually been used.<\/p>\n

      According to Anthony Lupo, controversy is hard to avoid in this early phase, while brands are still experimenting with AI in advertising. What matters is that brands make sure their use of AI matches the level of acceptance and the expectations of their own customers.<\/p>\n

      “It’s important to always have a read on the market sentiment. But this is no different from other controversial campaigns that have failed in the past.”<\/p>\n

      A prime example is Prada’s Spring\/Summer 2026 campaign, created by digital artist Jordan Wolfson. The campaign has a surreal, fantastical tone and features actors Nicholas Hoult and Hunter Schafer alongside giant CGI creatures that are half human and half bird.<\/p>\n

      Throughout the campaign, the characters keep repeating the line: “I… I… I am Prada.” The creatures are presented as their “alter egos”, raising questions about identity and self-image.<\/p>\n

      AI was only used in post-production to create the CGI creatures, which Jordan Wolfson designed himself. Even so, many people online assumed the entire campaign had been made with AI.<\/p>\n

      For Prada, AI played the same role as Photoshop or modern CGI technology (both of which already have AI built in): a support tool that extends human creativity, not a replacement for it.<\/p>\n

      On the other side of the debate, many brands see AI as a way to bring to life ideas that would be very hard to execute with traditional production methods.<\/p>\n

      On Maison Kitsun\u00e9’s fox campaign, Myl\u00e8ne Atlan, the brand’s Head of Image, says AI was the best medium for bringing this reimagined story to life.<\/p>\n\"Driving\n

      She adds that Sybille built a dreamlike world that moves back and forth between reality and fantasy, helping the brand convey the spirit of the collection in a more seamless and immersive way.<\/p>\n

      Some brands, by contrast, go out of their way to highlight the fact that they “don’t use AI”, and make that part of their storytelling and their brand values.<\/p>\n

      While pioneering brands use AI to create surreal stories, brands such as Aerie, which has built its image around natural beauty and a commitment not to retouch bodies in photos, take a firm stance: no AI in advertising.<\/p>\n

      In a March 2026 campaign, Aerie had model Pamela Anderson ask a chatbot to generate images of female models. The AI-generated images all looked unnatural and slightly creepy, before the campaign switched to real people wearing the brand’s products.<\/p>\n

      As marketers try to find their way through the “new territory” of AI, Billo CEO and co-founder Donatas Smailys stresses that whoever distributes content has a responsibility to tell people whether what they are seeing is real or AI-generated.<\/p>\n

      How can a brand get onto AI search’s radar?<\/strong><\/p>\n

      Building and maintaining brand awareness today is no longer only about social media or traditional SEO. AI platforms such as ChatGPT, Claude and Gemini are gradually becoming the places where people look for information, discover brands and make purchase decisions.<\/p>\n

      As a result, more and more brands are realizing that beyond SEO, they also need to invest in GEO (Generative Engine Optimisation), meaning optimizing to appear in the answers that AI search tools give.<\/p>\n

      Many brands, Beekman 1802 among them, are using platforms such as Yotpo Discover or Profound to understand why the brand does or does not appear in AI search, in what context AI is mentioning the brand, and what needs to be done to make AI more likely to recommend it to users.<\/p>\n\"Driving\n

      For queries related to “sensitive skin”, for example, these tools can help Beekman 1802 work out how to make its products more likely to be recommended by AI when people ask about skincare for sensitive skin.<\/p>\n

      From there, the brand can see which channels it is currently missing out on and where it needs to invest more to increase its presence in AI search.<\/p>\n

      For a skincare brand like Beekman 1802, that might mean appearing more often in Reddit discussions about sensitive skin, which are currently an important data source that ChatGPT often draws on. It might even mean stepping up its PR strategy to appear more often in reputable publications, which AI search tools also tend to prioritize as sources to cite.<\/p>\n

      Baker says: “These tools mean GEO is no longer a ‘mystery box’. A brand’s website and content marketing need to be updated in a way that is natural and close to the language real users actually use.”<\/p>\n

      In practice, this means product descriptions should be written in the way real people ask questions, rather than packed with flowery advertising phrases that actual consumers never search for.<\/p>\n

      For example, instead of only writing “Advanced biological age-reversing formula”, the content should answer questions that are close to real search behavior, such as “Which moisturizer is suitable for sensitive, easily irritated skin?”<\/p>\n

      Conversational platforms such as Substack are also becoming more important, because the way people interact on them is quite similar to the way they ask questions of AI search tools.<\/p>\n

      Another strategy that is working better and better is to have many different “voices” talking about the product in different ways: creators, communities, the press and user-generated content. That gives AI more context to understand the brand and recommend it more naturally.<\/p>\n\"Driving\n

      3. Performance and personalisation<\/h3>\n

      Test and learn: when AI becomes a “testing machine” for marketing<\/p>\n

      While marketers are using AI to test top-of-funnel content to build brand awareness and improve storytelling, performance marketing is where companies are really starting to “hand work over” to AI.<\/p>\n

      That gives creative teams more time to focus on the campaigns that have a big influence on how the brand is perceived, instead of spending their days on repetitive tasks.<\/p>\n

      At Goop, AI is used to help the team quickly create and then test many different creative versions to find the content that best fits each customer group, then keep optimizing based on real response data.<\/p>\n

      According to Alexa Ritacco, after loading moodboards, the brand deck and guidelines into the AI platform Adora AI, the team can add ad elements directly onto images from real photo shoots.<\/p>\n

      The technology lets Goop quickly create hundreds of different versions of the same product image, such as a peptide serum shown against many different backgrounds and settings.<\/p>\n

      With Adora, the team can keep generating new creative variations to test which elements drive better engagement, such as changing the background texture, switching the context the product is shown in, or adjusting how the images are arranged.<\/p>\n

      The system also keeps testing these elements throughout the life of a campaign, then every few weeks it sends back performance insights and new creative suggestions based on real data.<\/p>\n

      Ritacco says: “This is probably the most effective use case for us. It means the graphic design team can focus on videos or the content that really drives strong results, while Adora supports a test-and-learn mindset.<\/p>\n

      “We can now create a concept in just 10 minutes, where before it could take the whole team several days of work.”<\/p>\n

      In fashion, AI also helps teams create product collages built around a specific concept. For its Spring 2026 campaign, for example, Goop created a collage-style ad featuring a lace-trimmed camisole and jeans by entering the theme “French girl essentials” into Adora.<\/p>\n\"Performance\n

      The result: over a period of six weeks, the ad delivered 80% higher ROAS than the brand’s standard product photography.<\/p>\n

      Better performance measurement<\/strong><\/p>\n

      AI is also helping brands make sure their marketing budgets are spent more effectively. The Prescient AI technology that Beekman 1802 uses lets the company simulate a campaign’s performance in advance, forecast how much revenue it is likely to generate and then track actual performance across many channels, such as streaming TV, TikTok and digital ads.<\/p>\n

      According to Mike True, CEO of Prescient, brands can now get insights within a few days instead of waiting months. That lets them adjust budgets quickly, move media spend to more effective strategies and gives marketers the confidence to take “calculated swings”, meaning risky but well-reasoned decisions.<\/p>\n

      Beekman 1802 also uses Prescient to pull together and consolidate data from Meta, Google, TikTok Ads Manager, Shopify, Amazon and even offline retail.<\/p>\n

      As a result, the brand knows which channels perform best, and it can also measure the “halo effect”, the spillover impact of digital campaigns on offline sales, which used to be very hard to track.<\/p>\n

      For example, TikTok content creators promoting the newly launched Milk Rx eye cream lifted sales on the brand’s website, on Amazon and at the Ulta store chain.<\/p>\n\"Performance\n

      As a result, the product became Beekman 1802’s number one bestseller at Ulta.<\/strong><\/p>\n

      Streaming TV ads, on the other hand, only supported online sales and did not produce the same effect in physical stores.<\/p>\n

      So the brand decided to move nearly seven figures of media budget away from low-performing strategies and into activities that have a strong impact across its entire sales ecosystem.<\/p>\n

      Baker also points out that traditional marketing mix models used to cost millions of dollars and produced a report only once every 6 to 9 months. The company now gets the same amount of data every day.<\/p>\n

      Personalisation: tailoring the customer experience<\/p>\n

      Beyond finding the best-performing ads, many brands also use AI to personalize the content each individual person sees across email, SMS, the website and other communication channels.<\/p>\n

      Personalization has its limits, though. According to Jasper’s Loreal Lynch, problems can arise when a brand lacks a strong enough data foundation, or when it personalizes so heavily that people feel “creeped out”.<\/p>\n

      A classic example: someone mentions to a friend that they need to buy hiking shoes, and a few minutes later Instagram shows them an ad for exactly that product.<\/p>\n

      To avoid the feeling that “AI is watching too closely”, Lynch suggests brands personalize by stage of the customer journey, or localize content around regional trends, rather than personalizing too directly at the individual level.<\/p>\n

      The RealReal also uses AI models to decide which message to send, when to send it and which customer group to target, so that its communication through email, paid social and the website experience works as well as possible. That depends on whether the person is showing interest in a product, getting ready to buy or simply browsing for inspiration.<\/p>\n\"Performance\n

      Ferstandig says: “What matters is using AI models so we no longer approach every customer in a ‘one-size-fits-all’ way. Instead, we want to personalize the experience one-to-one (1:1). That means understanding where each person is in their shopping journey so we can nurture and motivate them in a way that fits.”<\/p>\n

      The RealReal also uses AI to personalize the products shown on its website just enough that people feel the content is “made for them”, but not so much that it kills the sense of serendipitous discovery, an important part of shopping for vintage and luxury resale (the buying and selling of pre-owned luxury goods).<\/p>\n

      Zalando, meanwhile, uses AI to create personalized ads on both its website and its app based on each user’s purchase history, browsing behavior and real-time interactions.<\/p>\n

      The platform also shows the standout fashion trends in each city, based on data from its Trendspotter tool. As a result, the personalized ads lifted CTR by 17% in the second half of 2025.<\/p>\n

      Matthias Haase, Vice President of Content Solutions at Zalando, says the company is also aiming to cut the time from spotting a trend to launching a campaign from three days to 24 hours.<\/p>\n

      Zalando also gives shoppers more ways to personalize their own shopping experience themselves. These range from showing outfits on many different body types to creating AI visuals of children’s clothing on digital models aged 4 to 16.<\/p>\n

      Zalando’s “Style It” tool, meanwhile, lets shoppers picture different ways to style a given product on a digital avatar. (Zalando has also updated 170,000 product pages with AI-generated video content to help people see more clearly how a product looks in motion.)<\/p>\n

      Haase says: “According to our data, conversion rates are significantly higher, and engagement with this content format is far above average, regardless of the category.”<\/p>\n

      The reason is not that AI content is better. It is simply that it feels far more relevant and suitable to the person seeing it.<\/p>\n\"Performance\n\"Performance\n

      4. Building customer lifetime value<\/h3>\n

      Keeping customers and growing their loyalty has always been one of the most important goals in marketing, and also one of the hardest problems for brands. Many companies are now expanding their use of AI to build loyalty and encourage repeat purchases over the long term.<\/p>\n

      Brands used to split customers into fairly basic groups, such as new customers, returning customers and customers who had stopped buying, and then send the same type of message to everyone in each group.<\/p>\n

      With AI, however, companies can personalize their communication much more deeply, depending on the stage each customer has actually reached in their journey.<\/p>\n

      For example, when a customer stopped buying (churned), a brand would typically send a discount code right away to win them back. Now brands such as The RealReal and Goop use AI to decide when they should not send a marketing message at all.<\/p>\n\"Building\n

      Instead of constantly pushing people to buy, AI helps brands recognize when it is time to “go quiet”, and then come back later with more relevant product suggestions at the right moment.<\/p>\n

      The RealReal sees the customer journey as one continuous “flywheel”, running from the moment someone buys to the point where they bring luxury items back to the platform.<\/p>\n

      AI helps the brand fine-tune its messages at each stage of that journey. If the system identifies a customer as likely to take that next step, for example, they are shown messages about the benefits of “refreshing their wardrobe” through circular fashion (a model of design, production and consumption that aims to extend the life of clothing as long as possible).<\/p>\n

      Another important part is knowing when to dial back marketing to avoid customer fatigue (the weariness that comes from seeing too many ads). Ferstandig says: “Sometimes it’s time to give the customer a break, because the data shows that at that point, continuing to ‘push’ them is no longer appropriate. What we’re aiming for is to sustain long-term value and create mutual benefit for the brand and the customer.”<\/p>\n

      She adds that rolling out these AI systems has helped The RealReal significantly increase both its customer retention rate and customer lifetime value.<\/p>\n

      AI also helps brands quickly create extra pieces of supporting content to keep customers engaged while video content is still in production.<\/p>\n

      At Goop, videos featuring founder Gwyneth Paltrow tend to perform very well, but producing new video takes a lot of time. So the brand uses AI to quickly create additional static product images to “fill the gap” and keep people engaging with the campaign while the video content is being refreshed.<\/p>\n

      Tools such as PMG’s Alli platform also help brands track when a piece of social content starts to “fatigue”, meaning people have seen it too many times and engagement drops.<\/p>\n\"Building\n

      At that point, the brand can tweak the content slightly or replace the creative entirely to keep performance from falling. AI is also especially useful for re-engaging customers who have almost dropped out of the funnel.<\/p>\n

      For example, for people who have stopped opening emails or stopped engaging, Goop uses Adora AI to create new social ads with product images that are completely different from anything those customers have seen before, while still matching their preferences based on their browsing and purchase history.<\/p>\n

      Ritacco says: “We can quickly create personalized product bundles for retention and launch them the very next day. That means the team doesn’t have to reuse old assets that customers may already have seen too many times.”<\/p>\n

      Lessons on AI in fashion marketing<\/h2>\n

      Adapting to AI will require marketers to change the way they think about their work. Lynch says the job is no longer just about producing individual outputs such as an email or a web page. It is about “building systems”, in terms of both the team and the process.<\/p>\n

      Teams that are used to creating and distributing one piece of content at a time are now shifting away from asking AI tools to produce single outputs to building systems that let AI do that work at scale.<\/p>\n

      Lynch puts it this way: “The problem isn’t writing one blog post. It’s rewriting 500 pages of blog posts.”<\/p>\n

      The benefits for marketers who make this shift can be substantial, not only in terms of saving time and money, but also in making the content they use to reach customers more relevant and more far-reaching.<\/p>\n

      Part of that impact comes from more advanced targeting, where brands can build more realistic consumer personas instead of targeting every Gen Z shopper in the same way. When people receive more personalized messages that match their own interests, it becomes much easier for the brand to connect with them. Brands are also using platforms such as Agentio and Fohr to identify the right creators and build more effective partnerships.<\/p>\n

      On the creative side, brands can use AI to come up with ideas, or to create variations of existing images from photo shoots so they have more visual options in different settings or with different content. Those who use AI to create entirely new images and whole new campaigns, however, need to proceed with caution.<\/p>\n\"Lessons\n

      In the luxury sector especially, brands need to make sure AI is a deliberate creative choice and not a shortcut. AI should be used as a storytelling tool, or to create images that could not exist without it.<\/p>\n

      Goop’s Ritacco says: “AI has expanded what we’re able to do almost without limit, which is wonderful. But taste, judgment and brand voice, all of that, is still completely human. A lot of the brands and CMOs I talk to are afraid of losing that. I think this leap is well worth taking, and it stays within your control if you’re willing to put in the effort.”<\/p>\n

      As brands speed up their ability to create many versions of the same content, they can also test those versions against each other faster to see which one resonates best. With platforms such as PMG’s Alli dashboard and Meta’s AI improvements within its Advantage+ tools, much of the manual work in performance marketing and tracking is being simplified. Some of it may even be removed from the marketer’s role entirely, freeing up more time to focus on opportunities at the top of the sales funnel, from big campaigns to live events.<\/p>\n

      Keeping a “human in the loop” approach throughout, meaning teams provide input on and approve content, as well as decisions made by AI at different stages, is essential, and that is likely to remain the case for the foreseeable future.<\/p>\n

      As Beekman 1802’s Baker says: “There will always be a trust-but-verify mindset with anything involving technology.”<\/p>\n

      Adapted by Adtek from original reporting by The Business of Fashion (2026), updated on October 19, 2026.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

      A summary of The Business of Fashion case study on how fashion and beauty brands such as Goop, Zalando, The RealReal and Beekman 1802 put AI to work across the marketing funnel without losing the human touch.<\/p>\n","protected":false},"author":5,"featured_media":5808,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_yoast_wpseo_meta-robots-noindex":"","_yoast_wpseo_opengraph-image":"","_yoast_wpseo_opengraph-image-id":"","_yoast_wpseo_twitter-image":"","_yoast_wpseo_twitter-image-id":"","inline_featured_image":false,"footnotes":""},"categories":[216,217],"tags":[],"class_list":["post-6989","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-digital-marketing-en","category-growth-marketing-en"],"acf":[],"yoast_head":"\nAI in Fashion Marketing: Case Study and Playbook<\/title>\n<meta name=\"description\" content=\"AI in fashion marketing: how Goop, Zalando, The 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