The press service reported that the new method will allow users to “save the time spent on creating a particular basket, and will also remind you to purchase a product that the user may have forgotten.” At the same time, using the algorithm developed by Tinkoff will help businesses “increase customer satisfaction, increase purchase conversion and stimulate average check growth.”
Tinkoff researchers conducted experiments, specifically using the dataset from the Chinese online platform Taobao. As a result, TAIW became the most effective method among its peers in the next basket recommendation (NBR) task. According to experimental results, the algorithm increases the accuracy of the recommendation system to 8%.
This breakthrough was demonstrated at the ACM RecSys conference. The Tinkoff algorithm doesn’t just track your purchase history; is a personal assistant that travels through time and adapts to your unique shopping preferences.
Source: Ferra
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