Blueprint · Retail & E-commerce
Conversational Shopping Assistant for an Online Retailer
A blueprint for a shopping assistant grounded in live catalogue, price and stock data.
Illustrative scenario. This shows how we would approach the problem. It does not describe a specific client, and the numbers are targets to validate in a pilot.
The situation
An online retailer has a large catalogue, and shoppers struggle to compare options. Support is busy with order status questions that have nothing to do with selling.
Our approach
- Sync catalogue, price and stock on a schedule
- Build intent-aware product search
- Answer price and stock only through live tool calls
- Handle order status through authenticated lookups
- A/B test against the standard site experience
Typical stack
- Commerce platform APIs
- Vector + attribute search
- Model routing for cost
- Storefront chat widget
- Experiment tracking
What we would measure
| Metric | Target approach |
|---|---|
| Conversion rate of assisted sessions | A/B tested against control |
| Support contacts deflected | Measure resolution, not just containment |
| Cost per conversation | Budget and alert per session |
The lesson
An A/B test is the only honest measure. Assisted shoppers are often already more motivated, so a simple before-and-after will flatter the result.
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