How Zalando tells better stories 

Telling a great fashion story takes two things that don't always go together: speed and something that feels genuinely human. In this two-part series, we go behind the scenes of how different teams blend technology and editorial instinct to give our customers the most relevant and authentic content.

In this first part, we explore how our content production team moved from a rigid, weeks-long production calendar to a system that can go from spotting a trend to publishing it in a few days. In the second part, we'll meet the Global Social Media and Content Creation team — the editorial team keeping Zalando at the heart of cultural conversations.

Where to start? When we shared our financial results for 2025, one of the figures stood out: 90% of Zalando’s on-site marketing content is now generated by AI. We sat down with Matthias Haase, VP of Content Solutions, to dig into the background of that number and find out how we’re using technology and why it’s making our storytelling better.

Matthias, first of all, could you please explain what 90% figure actually means?

It means that when you open the Zalando web or app and scroll through — banners, trend highlights, campaign imagery, teasers —  most of this content is created using generative AI. Not product detail page or advertising outside Zalando, but the editorial and marketing content you see on-site, meaning the "inspiration layer" for our platform. Of course, you'll see those major human-led productions living on-site – like our current Spring/Summer campaign with Lily Collins. But while those hero campaigns provide our global seasonal direction, the other 90% of our on-site content is now about local relevance. It’s the fast-moving, trend-led content that makes your daily feed feel fresh.

A year ago, that number was almost zero. How could you scale so fast?

Honestly, we had to. In the past, we worked off a rigid yearly calendar and had to be very selective about which global campaigns we prioritised. With 27 different markets, we simply couldn't afford to localise everything. A single production cycle could take six to eight weeks.

But fashion doesn't move in eight-week cycles anymore. Trends change overnight — one day it's a specific musician aesthetic, the next it's animal print. Our traditional production just couldn't keep up with that pace. Generative AI was the solution to that bottleneck. It allowed us to move from a "planning" mindset to a "reacting" one, cutting those weeks of work down to just a few days — and our target this year is under 24 hours from spotting a trend to going live.

Could you explain the behind-the-scenes of this reacting process? How do you spot and style a trend that quickly?

Everything starts with our own platform. With 50+ million customers on our platform, we have a unique signal — we can see search spikes, browsing shifts, and sales patterns in real time. When something starts moving on Zalando, we know about it immediately. This helps us identify the top trends every single day. We even show our customers these peaking trends on our platform through our Trend Spotter, which we update every week. 

We then validate that with our internal social listening tool, which analyses media coverage and creator content to confirm whether a trend has broader cultural momentum. Once we have the trend, the engine can even generate a simple prompt for the initial visualisation. But that’s just the base layer. Our creative team still defines the taste and the final vibe. In a real photoshoot, there are messy, human details that make an image feel authentic. We guide our AI to keep those – the subtle textures and real-life lighting that make our content feel like a human moment rather than robotic perfection. AI is just a high-speed tool that helps our creators get there.

This sounds like a huge change for the production team, but what’s the shift for the customers scrolling through the app? Does it actually change how they shop?

It makes the shop feel much more alive. Because we've cut production from weeks to hours, we can be incredibly local and relevant. We can style a product differently for a customer in Milan versus someone in Berlin, ensuring the look actually fits their environment — or even the weather.

We're already seeing that this relevance works. Customers are engaging 10% more with this content and spending more time on the platform. But the real win is confidence. When content is more vivid and informative, people make better choices — they find what they want faster and, importantly, they return less. We aren't using AI for the sake of it. We're using it to move at the same speed as our customers' wardrobes.

We’ve talked a lot about the inspiration layer, but what’s next – how AI is changing product experience?

We're moving way beyond flat images on product pages. We've already produced 170,000 AI-generated videos based on our existing product photography — and today, if you open a product page and a video is available, that's the first thing you see. It brings the fabric and the movement of a garment to life in a way a static photo never could. Producing video at that scale simply wasn't feasible with traditional methods. What was once an exception is now a standard.

But the bigger shift is personalisation. The next step is to lose the "one size fits all" approach entirely — we're heading towards a world where the product page itself is dynamic, looking different depending on where you are, what brands you follow, or what you actually love. Our goal is to show you exactly how a piece fits into your lifestyle.

In part two of this series, we’ll talk to Tulani Andre, VP Social Media and Content Creation, about how our teams take these insights and turn them into cultural moments – from curated Boards to talent-led stories – that keep the human spark at the heart of everything we do.