Customer sucess story

L'Oreal

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

Challenge

Enhance your recommendation engine with consumer feedback.

Utilize consumer reviews on your brand as well as competitors' products to enhance the performance of your recommendation engine

?
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.

Challenge

Enhance your recommendation engine with consumer feedback.

Utilize consumer reviews on your brand as well as competitors' products to enhance the performance of your recommendation engine

?

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.

Result

BOOST PERFORMANCES

4%

Statistical performance on A/B tests.

600k

verbatim analyzed

Solution

Popularity Based Recommendation

Sensory Customer Journey

It operates based on the sensory attributes trend for each customer segment.

Content personalized to the customer profile

Utilize the best wording for the most popular review in each customer segment.

Solution

Popularity Based Recommendation

Sensory Customer Journey

It operates based on the sensory attributes trend for each customer segment.

Content personalized to the customer profile

Utilize the best wording for the most popular review in each customer segment.

Results

BOOST PERFORMANCES

4%

Statistical performance on A/B tests.

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