We’ve been long working on improving the user experience in UGC products with machine learning. Here are our ten key lessons of implementing recommendation systems in business to build a really good product.
1. Define a Goal that Really Contributes to the Business Tasks
The global task of the recommendation system is to select a shortlist of content from a large catalog that is most suitable for a particular user. The content itself can be different — from products in the online store and articles to banking services. FunCorp product team works with the most interesting kind of content — we recommend memes.
To do this, we rely on the history of the user’s interaction with the service. But “good recommendations” from a user perspective and from a business perspective are not always the same thing. For example, we found that increasing the number of likes that a user clicks thanks to more accurate recommendations does not affect retention, a metric that is important for our business. So we started focusing on models that optimize time spent in the app instead of likes.
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