Increasing relevant product recall through smart use of customer behavioral data

Kramp is a B2B wholesale company in the agricultural sector, selling over 1.7 million technical products across 26 countries. Most of our business runs through our digital channels, where our customers need to find and order the right parts and products as quickly as possible .

Our key challenge is poor product data quality, which results in customers not being able to find the products they need, even though Kramp sells it. To improve recall for specific queries, we use customer behavioral data to enrich search results . In short, we track search behavior and query refinements during a ‘search session’, allowing us to identify patterns to relate products with interactions to earlier unsuccessful search queries.

We ran AB-tests with this feature and we see a clear positive impact of this functionality on key metrics such as product interactions, add-to-carts and 0-result pages. But we also found some interesting negative side-effects which we plan to tackle in the near-future.

Eric Rongen

Kramp Hub

Eric Rongen is Product Manager responsible for product findability at Kramp Hub. Together with multiple product teams he works on improving the search experience on the webshop, so customers can easily, quickly and with certainty find the products they need.

Jelmer Krauwer

Kramp Hub

Jelmer Krauwer is an architect for data, machine learning and experimentation at Kramp Hub. He works together with teams on topics like improving search relevance, product recommendations and visual search.