Ahead of this year’s Digital Transformation Expo Europe, Linda Cereda, Nike’s VP of Marketing Data, offers an insider’s perspective into Nike’s martech evolution – a journey propelled by scalable AI, unified data infrastructure, and engineering-driven change management. Her approach reveals how Nike is balancing precision marketing with privacy, enabling personalisation at scale through advanced data orchestration and composable tech.
How is Nike evolving its use of marketing data in the digital age?
Nike has been investing heavily in data for two macro use cases for marketing. First, better decision-making – we in-housed marketing mix modeling, and complemented with experimentation, and attribution. Second, personalisation at scale. We built a unified customer data platform with underlying ML/AI models that power everything from our journey orchestration to how we personalise digital experiences.
What key challenges do you face balancing data privacy and personalisation?
Consumer trust is everything to us. We have a simple rule: if we’re asking for your data, we better be giving consumers real value in return – better products, more relevant communication, or experiences that actually matter to you.
The tricky part is the execution. Making sure consumers clearly understand how data is used and can easily change their minds about what data they want to share, and doing this consistently in different countries with different regulations and cultural attitudes toward privacy. It’s complex, but it forces us to be really intentional about every piece of data we collect.
How do you foster a culture of data litreacy in marketing teams?
It starts at the top – if leadership isn’t walking the walk with data, why would anyone else? We’ve also invested in learning programmes that are engaging. We ran competitions through a gamified app, kept the content bite-sized so people could fit it into their actual work schedules, and made sure to reinforce it regularly because, let’s be honest, people forget.
But the real game-changer is baking data into how we work. What data do you bring to a quarterly business review? How easy is it for a marketer to get the insights they need? When data becomes part of the process, not an extra step, that’s when you see real adoption.
What are the most powerful data tools or platforms you’re using today?
We built an integrated martech stack – customer data platform, journey orchestration, digital optimisation tools, supported by analytics. But honestly, with how fast AI is moving, I’m spending a lot of time looking at what’s next. Composable stacks that adapt faster and AI-native tools that can make decisions – like AI decisioning engines – not just predictions, and lead to true 1:1 personalisation. Even synthetic personas that can help us test and iterate on go-to-market strategies without waiting months for real consumer feedback.
What key insight will you be bringing to TechEx Europe?
Despite the AI hype, 80% of projects still fail to deliver expected ROI. I’ll share a suggested framework for developing AI strategies that create sustainable competitive advantage, beyond delivering short term efficiency gains, grounded in a decade of AI deployment experience at Nike. I’ll explore what I believe will and won’t change in the retail and brand landscape, and more importantly, what I’d recommend brands and retailers start doing differently today to get ready for that future. It’s about being strategic now, not reactive later.
Want to learn more about digital transformation from industry leaders? Check out Digital Transformation Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including AI & Big Data Expo, IoT Tech Expo and Cyber Security Expo.
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