Solving Size Uncertainty to Improve Zalando Conversion Rates
Eight interviews in Germany, ending in a single conclusion that Zalando's size problem lives on the product detail page
✳The problem they went after
Utility shoppers on Zalando are need-based buyers who care about fit accuracy and want returns to be effortless. For them size uncertainty makes buying fashion online feel riskier than walking into a store. Interviews turned up the same patterns repeatedly: a preference for physical stores to avoid returns, avoidance of unfamiliar brands because sizing is unpredictable, and far more trust in peer reviews than in manufacturer size charts.
✳What they actually did
Eight user interviews in Germany feed a narrowing exercise that lands on the product detail page as the conversion bottleneck. Shoppers arrive with clear intent and leave without buying because they cannot judge fit across brands, and the existing guidance is brand-level and generic. Roughly a third of Zalando returns trace to size and fit. Secondary problems, finding applicable offers during sales and friction in the return process, are logged and parked. The direction points at personalised, prominent size recommendations and confidence signals.
✳What you can take from it
Worth stealing
- Eight German user interviews behind the framing
- Utility shopper segment defined by fit and return effort
- PDP named as the single conversion bottleneck
- Secondary problems logged and deliberately parked
Read this if
PMs learning to turn a pile of interview notes into one defensible P0
The transferable bitThis is a good model for getting from raw interview notes to one defensible P0 statement. Naming the exact screen where the problem is felt shrinks the solution space to something buildable, and holding secondary problems on the list without acting on them shows how to acknowledge scope without letting it dilute the focus.
✳The submission itself
Open the PDF →Reading on a phone? The embedded viewer is cramped — open the PDF in a new tab instead.
