Latest / The CMO Podcast with Fexingo: Marketing Leadership, Budgets, and Executive Strategy / Why CMOs Are Betting on Zero-Party Data Pods
Transcript
- Lucas: So you know how for years the marketing conversation around data has been about first-party versus third-party, with everyone scrambling after the cookie deprecation. Luna: Right, like the entire industry pivoted to building first-party data strategies. Lucas: Exactly. But there's a newer, more intentional layer emerging now — it's called zero-party data. And it's not just a semantic upgrade. It's data that a customer proactively and deliberately shares with a brand. Not inferred, not observed, not purchased. Explicitly handed over. Luna: So we're talking about preference centers, interactive quizzes, things like that? Lucas: That's part of it. But the specific structure I want to talk about today is something called zero-party data pods. These are small, opt-in data exchanges where the consumer decides exactly what they share and gets something tangible back — not just generic points, but a genuinely personalized experience. Luna: I've seen this in beauty and skincare especially. Brands asking you to take a skin quiz before recommending products. Lucas: That's exactly the archetype. And the poster child right now is Sephora's Beauty Insider program. They've been iterating on this for years, but in early 2026 they launched what they call a 'Beauty Insider Plus' tier — it's a zero-party data pod. Customers voluntarily share their skin type, concerns, preferred ingredients, fragrance sensitivities, even their budget range. Luna: And in return? Lucas: In return, they get a hyper-personalized product feed, exclusive access to limited drops that match their profile, and a dedicated beauty advisor who actually knows their preferences. No generic emails. No 'you might also like' based on what someone else bought. Luna: How has it performed? I'm guessing Sephora didn't roll this out without serious testing. Lucas: They piloted it in Q4 of 2025 across 200 stores and their app. The internal numbers they shared at a marketing conference in April this year showed that zero-party data pod members had a 34% higher repeat purchase rate compared to standard Beauty Insider members. And average order value was up 18%. Luna: That's significant. But I wonder — is that because the data pod actually improves targeting, or because the people who opt in are just more engaged shoppers to begin with? Lucas: That's the classic selection bias question, and it's fair. Sephora controlled for that by comparing against a matched cohort of standard members with similar historical purchase frequency. The pod still outperformed by 22% on repeat rate. So there's a real effect. Luna: Okay, so the performance is there. But from a CMO's perspective, the cost of building and maintaining these pods is non-trivial. You need the tech infrastructure, the content to personalize, the human touch. How do CMOs think about the ROI? Lucas: This is where I think the argument gets really interesting. According to a survey from the CMO Council published last month, 43% of CMOs at consumer brands are now actively building zero-party data capabilities. And they're reallocating an average of 12% of their martech budgets toward it this year alone. Luna: That's a big shift. Where's that money coming from? Lucas: Mostly from legacy personalization engines and third-party data brokers. The logic is: a data pod might cost more per active data point — maybe $2 to $5 per opted-in profile per year, versus pennies for inferred data — but the signal quality is dramatically higher. And churn is lower. Customers who've shared their preferences are stickier. Luna: So it's not about scale. It's about depth. Lucas: Exactly. And there's a privacy angle that CMOs are leaning into hard. With regulators in Europe and a few US states tightening consent requirements, zero-party data is practically audit-proof. You can't get in trouble for using data someone explicitly gave you. Luna: That's a compelling argument for the legal team. But what about brands that don't have Sephora's budget or tech team? Can a mid-market brand do this well? Lucas: I think they can, but they have to be more focused. A great example is a DTC supplement brand called Care/of — actually, they were acquired by Bayer a few years ago, but their model is instructive. They started with a simple daily quiz, just seven questions about health goals and dietary restrictions. They built a zero-party data pod that fed a personalized monthly pack. No massive tech stack, just a well-designed survey and a rules engine. Luna: And did it work for them? Lucas: Before the acquisition, they reported that customers who completed the quiz had a 60% higher 12-month retention rate than those who didn't. The quiz itself became a competitive moat — it was hard for competitors to replicate the experience without the same data foundation. Luna: So the barrier to entry isn't really technology. It's the willingness to ask and the discipline to actually use the data you collect. Lucas: That's exactly right. And that's where I see some brands tripping up. They build a preference center, but they don't integrate it with their email system or their product recommendation engine. So a customer says 'I'm vegan and I avoid artificial sweeteners,' and then they get a promotion for a whey protein bar. That's worse than not collecting the data at all. Luna: It breaks trust. You're essentially telling the customer you didn't listen. Lucas: Precisely. And once that trust is broken, it's very hard to win back. So the CMOs who are doing this well are the ones who treat zero-party data as a product in itself. They design the experience of sharing data to be valuable on its own, not just a means to an end. Luna: Can you give me an example of a brand that does that well — beyond Sephora? Lucas: Sure. Nike's membership app has a feature called 'Nike Fit' — it's an ar based foot scanning tool. But before you scan, they ask you about your running habits, your preferred terrain, your injury history. You get a personalized shoe recommendation and a fit guarantee. The data pod here is the combination of physical measurement and preference data. Nike uses it to reduce returns — their return rate for recommended shoes is reportedly 8% lower than for non-recommended ones. Luna: That's a direct bottom-line impact. And it's a better customer experience too. Lucas: Right. And that's the kind of win that gets a CFO's attention. Marketing isn't just spending — it's reducing cost and improving margin. Luna: I want to push back a little, though. There's a risk that zero-party data pods become just another loyalty tier, another thing for the customer to manage. Aren't we adding friction? Lucas: It's a real risk. That's why the best implementations are single-purpose, not giant data dumps. Sephora's pod is specifically about beauty preferences. Nike's is about fitness and footwear. If a brand asks you to fill out a 20-question profile just to get a 10% off coupon, you're right, that's friction. Luna: So the key is to keep it narrow and immediately rewarding. Lucas: Exactly. And there's an emerging best practice: the 'one-click opt-in with progressive profiling.' You ask one question at a time, and each answer unlocks a small benefit. Over time, you build a rich profile without the initial hurdle. Luna: That's smart. So where do you see this going? Is zero-party data going to become table stakes for every consumer brand? Lucas: I think within three years, it will be. The regulatory direction is clear — consent is becoming mandatory, not optional. And customers are increasingly savvy about the value of their data. They're willing to share, but only if they get something clear in return. Luna: So the CMOs who build these pods now are essentially future-proofing their marketing. Lucas: That's the argument. And I think it's a strong one. The brands that wait will find themselves scrambling, just like they did with the cookie deprecation. Luna: You know, if these conversations have sparked something you've actually used in your own work, or even just a new way of thinking about your own data, we should mention that there's a way to support the show directly. Lucas: Yeah, we keep this podcast ad-free by design, and listener support is what makes that possible. Honestly, if today's episode was worth a coffee to you, you can find us at buy me a coffee dot com slash fexingo. Luna: It's a small gesture that goes a long way in keeping these conversations going. And we really appreciate it. Lucas: Alright, so back to zero-party data. One more angle I want to touch on is measurement. How do CMOs measure the ROI of a data pod when the payoff is in retention and lifetime value, not immediate conversion? Luna: That's the tricky part. Because marketing has been trained to optimize for last-click or same-session metrics. Lucas: Right. And zero-party data doesn't fit that model. The value shows up over 6 to 12 months. So the CMOs who are succeeding are building cohort-based dashboards. They're tracking retention curves, not conversion rates. One CPG brand I spoke with — a specialty food company — saw that customers who completed a taste preference pod had a 40% higher 90-day repurchase rate, but their initial conversion from the pod was actually slightly lower than the control group. Luna: Because the pod asked them to think, and that slowed the purchase. Lucas: Exactly. But the stickier behavior more than compensated. So the CMO had to educate the board on why a short-term dip was actually a long-term win. Luna: That takes conviction. And a patient CFO. Lucas: It does. But I think the data is starting to speak for itself. As more brands share their zero-party data results, the narrative is shifting. It's no longer a speculative bet — it's a proven strategy. Luna: And for the CMOs listening, what's the one concrete step they could take this week to start? Lucas: Audit your current data collection points. Find one place where you already ask customers a question — it could be a preference on an email sign-up, a size selector, a quiz — and make that answer immediately actionable. If you ask someone their favorite category, send them a personalized recommendation within 24 hours. That's the seed of a data pod. Luna: Start small, prove the value, then scale. Lucas: Exactly. And that's the CMO playbook for 2026 in a nutshell.