Tokopedia’s recommendation engine relied heavily on behavioral signals, requiring up to 197 product views, 20 add-to-carts, and 5 chats to generate useful personalization for a single user. That level of data takes time, causing users to miss relevant product discovery moments early on.

To solve this, we explored an explicit profile approach asking users directly about their shopping preferences. This provided faster, more accurate inputs for Recommendations, Personalization, and Search, without waiting for long behavioral build-up.