Catalog + events
Connect the inputs
Map consistent item identifiers, attributes, and interaction events. Agree which contextual signals are useful and appropriate for the placement.
How it works
From signals to a more relevant next step.
A clear view of the recommendation workflow: connect data, understand intent, retrieve candidates, rank, deliver, and evaluate.
Book a demoCatalogEventsContext
RankNexaCatalog · Events · Context
01 Relevant item02 Related discovery03 Something new
Conceptual workflow. Integration scope and capabilities are discussed for your use case.
Features + representations
Understand relevance
Build meaningful representations of items, sessions, and available user history. Consider content-based approaches when behavioral data is sparse.
A useful starting set
Retrieve candidates
Combine content similarity, collaborative signals, popularity, or semantic retrieval according to the catalog and data maturity.
Relevance + constraints
Rank with intent
Score and order candidates for the experience. Apply availability, eligibility, duplicate suppression, and diversity rules explicitly.
API + placement
Deliver the experience
Return a practical recommendation response to a homepage, feed, detail page, or other application placement. Define appropriate fallback behavior.
Evaluation + iteration
Learn from outcomes
Capture meaningful outcomes, compare strategies against a baseline, and refine the approach with offline evaluation and controlled experiments.
Let’s find your starting point
Great catalogs.
Even better discovery.
Bring your product, your catalog, and your biggest relevance question. Let’s talk about what a better experience could look like.
Book a demo