Enhanced performance of an
e-commerce recommendation engine
“We had two goals: to get high-quality data for training the recommendation system for our ecommerce platform, and to measure the accuracy of our current recommendation algorithm. Toloka helped us improve our model with super fast labeling of tens of thousands of products from our store. Toloka makes the data problem easier so that we can focus on our algorithms. ”
– Ivan Lapitsky, Project manager, Yandex.Market
Improved crowdsourced translations of product descriptions
Results:
budget reduction while achieving optimal quality
Improved the accuracy of a predictive tool using local shopping patterns
Results:
improvement in app accuracy after data collection, reaching 95%
Expanded product coverage for e-commerce price matching
Results:
better coverage of key products
Tuned a 3D foot sizing app for better accuracy
Results:
improvement in app accuracy with accelerated time to market