Recommendation Engines

Personalized product recommendations that lift basket size and conversion.

Finding what a customer came for matters; so does meeting the product they did not think to look for. Recommendation engines rearrange your catalog for every visitor.

We pick the approach that fits your catalog size and data volume: collaborative filtering that learns from purchase behaviour, content-based matching on product attributes, or a hybrid of the two. Cold start, out-of-stock items, and seasonality are accounted for from the start.

We follow the outcome with measurement: we validate the effect on basket size, click-through, and conversion with A/B tests, and improve the engine from the data.

What's included

  • Collaborative filtering
  • Content-based
  • Hybrid

Deliverables

  • Recommendation engine integration
  • Model documentation
  • Impact report