Customer lifetime value (CLV) is widely discussed in marketing, but in practice relying on broad averages that hide important differences in how customers generate long-term value is still the norm. In this Q&A, Ioannis Koukoulis, our Senior Director of the Innovation Hub, explains why looking at CLV through a product-category lens offers a more practical and actionable approach. Rather than relying on complex predictive models, category-level CLV helps marketers connect acquisition signals with real commercial outcomes such as margins, returns, and repeat purchasing behavior, giving both marketing and leadership teams clearer guidance on where profitable growth truly comes from.

Q1: Ok, First Thing’s First: What Is Category-Level CLV Modeling?

Ioannis: A category-level CLV modeling is a practical way to make CLV more useful for marketing without having to build complicated predictive models that will predict future customer behaviors. Calculating and using one average CLV per market (even an average per channel) is a good start, but it still treats every new customer the same, so bidding systems can’t really tell the difference between someone who’ll become a great long-term customer and someone who won’t. A fully predictive CLV model can solve that, but it’s often a bigger lift because you need solid first‑party data and more ongoing modeling work.

Category-based CLV sits in the middle: you look at what category someone buys in their first basket, and then you can assign category-level values like expected margin, return rate, and average CLV. In the end, you are giving to the advertising platform a bidding signal that reflects the kind of customer you’re likely getting, not just an overall average.

Q2: Why Does Looking at CLV at a Product Category Level Change How Businesses Think About Growth vs. Optimization?

Ioannis: Thanks for asking this. This a common thing we have seen happening with many retailers. Looking at CLV on a product‑category level changes the growth conversation because it stops you from being “blinded by volume.” A lot of retailers see certain categories pumping out big revenue and assume that’s where they should scale, but the truth is that those same categories can have very different economics once you factor in what actually matters: contribution margin, return rates, and whether that category is a real new‑customer driver.

Category‑level CLV brings those dimensions back into the decision, because you’re effectively telling your bidding system: “Don’t just chase sales, but rather chase the categories that tend to create higher lifetime value and healthier profit after margins and returns.” That’s the moment teams shift from short‑term optimisation (more orders, more revenue) to true growth (more valuable customers, better long‑term contribution)—because different categories can lead to very different customer journeys and business outcomes.

Q3: How Does This Approach Help Separate Profitable Growth From Volume-Driven Growth?

Ioannis: Well, a category‑level CLV makes profitability visible in a way that top‑line metrics can’t. If you connect actual product margins, returns, and downstream buying behavior to each category, you uncover which categories attract customers who become high‑value over time and which ones don’t. This way you can avoid pouring budget into categories that bring in lots of orders but very little long‑term contribution, and instead move advertising budgets toward the ones that consistently drive repeat purchases and healthier economics. The result is a much clearer separation between growth that only looks good in marketing dashboards and growth that genuinely strengthens the business.

Q4: In What Ways Can Category-Level CLV Help Leadership Teams Prioritize Which Parts of the Business to Scale or Protect?

Ioannis: Leadership teams can easily create a financial map of where value is created in the assortment, helping them identify the categories that consistently deliver strong lifetime contribution and deserve protection even if they don’t immediately appear as top selling categories. Also it can give clear indication on which categories have the potential to scale profitably because they attract customers who return frequently or purchase across multiple parts of the catalog. On the other hand, it can flags categories that may be volume‑heavy but value‑light, enabling decisions around deprioritization, pricing strategy, or marketing throttling. Ultimately, it brings clarity to what should grow, what should stabilize, and what may need rethinking

Q5: What Blind Spots Do Companies Create When They Rely on Customer-Level or Channel-Level CLV Alone?

Ioannis: The truth is that when companies only track CLV at the customer or channel level, they end up masking the true drivers of value because they lose the link between the first product a customer buys and the value they ultimately generate. Two customers acquired through the same channel can end up with wildly different CLVs depending on the category they entered through. This blind spot often leads to over‑investing in channels that lead to cheaper acquisition or campaigns that appear to perform well on short‑term metrics but actually pull in low‑value categories, ultimately distorting budget decisions and long‑term strategy.

‍Q6: What Decisions Become Materially Better When CLV Is Viewed Through a Category Lens Rather Than a Campaign Lens?

Ioannis: Seeing CLV through a category lens improves decisions across bidding, budgeting, merchandising, and even forecasting because you’re finally aligning marketing investment with the true economic value of what customers buy. It allows the marketers to set bidding targets that reflect real margins and expected lifetime value by category, not just campaign‑level ROAS. It also helps merch teams understand which categories drive valuable customers, informs assortment strategy, and gives finance and leadership a more accurate basis for growth planning. Also, merch teams can design their promotions accordingly. In short, it ensures that operational, marketing, and strategic decisions are based on the long‑term value of the categories being sold, not just the performance of the campaigns promoting them.

Key Takeaways for Growth Leaders

· Category-level CLV bridges the gap between simple averages and complex predictive models, giving marketing platforms better signals about the long-term value of the customers they acquire.‍

· It shifts teams from chasing volume to pursuing profitable growth, factoring in margins, return rates, and repeat purchase behaviour across different product categories.‍

· It improves cross-functional decision making, helping marketing, merchandising, and leadership align investment, assortment, and growth planning around categories that create the strongest long-term value.

---

Need help implementing category-level CLV modelling onto your conversion tracking on Google Ads or any other ad platforms? Reach out to us!

Relevant Insights:

· Article: Q&A: Lessons from Managing and Auditing Global Paid Media Budgets across Retailers and DTC Brands

· Article: Q&A: How Can Scripts Help Scale and Optimize Paid Campaigns at Speed?

· Report: Great ROAS, Terrible Results: The Case for CLV-Centric Advertising

About Crealytics

Crealytics is an award-winning full-funnel digital marketing agency fueling the profitable growth of over 100 well-known B2C and B2B businesses, including ASOS, The Hut Group, Staples and Urban Outfitters. A global company with an inclusive team of 100+ international employees, we operate from our hubs in Berlin, New York, Chicago, London, and Mumbai.