Ebook
Traditional search on your ecommerce site is likely failing your users. They're overwhelmed with hundreds of results that don't match their preferences, making it nearly impossible to find what they actually want.
This frustration leads to decision fatigue, abandoned searches, and lost conversions. Meanwhile, competitors implementing search personalization are seeing 40% more revenue (McKinsey) and 50% higher conversion rates (wisernotify).
But what if you could transform your raw behavioral data into a ranking system that automatically surfaces the most relevant results for each individual user?
Picture a scenario where your users find exactly what they want in seconds, boosting engagement, dramatically increasing conversions, and driving millions in incremental revenue—just like one leading travel company that achieved £2M in additional profit.
Our technical guide shows data builders how to implement the exact Learn-to-Rank personalization framework this travel company built alongside our partner, Infinite Lambda. The guide covers the end-to-end implementation—from architecture and feature engineering to model training and production deployment—and showcases how Snowplow data powers its success.
