Case Study: a major cosmetics company boosts profitability with Sigmoid's multi-armed bandit personalization solution

Major Cosmetics Company boosts profitability 8% with Sigmoid

The customer, a major cosmetics company, faced the challenge of maximizing sales and conversion rates from its new website. Their existing system relied on fixed business rules for recommendations and lacked the ability to test and understand the performance of different personalization strategies. They engaged Sigmoid to develop a personalized digital recommender system.

Sigmoid implemented a multi-armed bandit reinforcement learning solution to generate personalized recommendations based on customer purchase history. This system learned from real campaign feedback to select the best-performing strategies for individual users. As a result, Sigmoid's solution led to an 8% improvement in profitability and a 24% increase in average sales per consultant for the client.