E-commerce & Digital
AI-generated size and fit recommendations
Use purchase and return data to recommend the right size for each customer and product combination. Reduce size-related returns by predicting fit before purchase.
10–25%
reduction in size-related returns
Opportunity assessment
Moderate impact. Meaningful cost or revenue improvement, likely noticeable at function level but modest relative to total business scale.
Moderate effort. Requires configuration, prompt engineering, and testing. A capable team can get there but expect several months.
Demanding data requirements. Relies on clean, integrated data across multiple systems. Significant data preparation work typically needed.
Moderate risk. Some customer or external exposure. Errors create rework or reputational impact but are recoverable.
Light people impact. A new tool slots into an existing workflow. Minimal training needed. Most people will adapt quickly.
Tooling required
Things to consider
Requires detailed garment measurement data at SKU level and sufficient purchase/return history to build the prediction model. Most fashion retailers have the return data but not the garment measurements.
Size recommendation accuracy is category-dependent. Structured items (jeans, shoes) are easier to predict than unstructured items (knitwear, outerwear) where fit preference is more subjective.
Stitch Fix demonstrated that AI-driven personalisation (including fit prediction) increased average order value by 40% and doubled annual revenue through improved retention and reduced returns (eTail West).
Experiment starter: For your highest-return-rate category, analyse return reason data to isolate size-related returns. If size accounts for 30%+ of returns in that category, trial a fit recommendation tool on those products for 3 months and measure the return rate change.
Go deeper in the playbook
Section — Opportunity Identification, including the AI Opportunity Assessment ScorecardSection — RAG and Knowledge Systems: Unlocking Proprietary DataThis is an decision support opportunity — see the relevant playbook section for how to approach it.More in E-commerce & Digital
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