B2C Recommendation Engine Using Sensory Data
NYX is a mass-market brand with a broad consumer profile. The goal is to recommend proposals based on purchases, as well as perceptions of the sensory qualities of the products
How to extract information from consumer reviews? What information is most correlated with the performance of the recommendation engine? How to measure the added performance?
Creation of meta-features based on the analysis of consumer reviews to feed the recommendation engine.
It operates based on the sensory attributes trend for each customer segment.
Utilize the best wording for the most popular review in each customer segment.
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