Personalized product recommendations, from session 1
Real-time ranked product sets for every surface. Works on anonymous sessions. No purchase history required.
Three-layer intent model
Every recommendation is the output of three signals combined per session. Session behavior (what this visitor just did), collaborative filtering (patterns from sessions with similar paths), and catalog affinity (which product attributes this session's engagement predicts).
The model doesn't need a logged-in user or purchase history. It builds from the first pageview and refines after every event.
Cold-start products (new arrivals, low-engagement SKUs) are handled through catalog attribute embedding. A new product can surface to the right visitor within hours of catalog sync, without waiting for engagement history to accumulate.
Views, searches, add-to-cart events, purchase intent. Per-event model update, no polling.
Collaborative filteringPattern matching across sessions with similar category and attribute engagement paths.
Catalog affinityProduct attribute embeddings map session engagement to catalog segments. Handles cold-start SKUs.
Where recommendations appear
Homepage Carousel
Replaces or augments your homepage product grid or featured items carousel. Each visitor sees a ranked selection from the full catalog based on session and catalog signals.
Product Detail Page
Related items and "you might also like" slots on PDP, ranked by session affinity rather than static purchase co-occurrence. Updates per session, not per product.
Cart Cross-Sell
Cross-sell slots in cart that surface complementary products based on cart contents and session affinity. Not "frequently bought together" noise based on unrelated purchase pairs.
Ready to see it on your catalog?
Book a demo and we'll walk through what recommendation surfaces look like on your actual SKU set.