Creating effective content for users means meeting their interests over time. To do so, a customer’s journey must be developed that is close to his or her current and future needs.

Using a mix of AI algorithms, it is possible to predict users’ interests and behaviors, identify the optimal actions and content to propose, and maximize the effectiveness of marketing campaigns, progressively reducing the abandonment rate.

Results

+ 80% correctly profiled interests
70% accuracy of churn risk prediction

In the multi-store environment, stock planning is crucial to be able to cover the demand for products in a timely manner and to improve sales.

AI algorithms can determine the right strategy of action: on the one hand, the amount of merchandise needed from week to week is suggested; on the other hand, sales and promotional campaigns are monitored.

Results

– 30% decrease in remaining stock on a weekly basis, for specific merchandise functions

Getting to know your customers closely is the first step in building an effective sales strategy. AI tools exist that can raise the level of customer knowledge, enhancing promotion and sales activities.

A recommendation engine suggests the “next best product” and the most suitable discounts for specific customer groups, based on purchasing behavior recorded over time (number of pieces/year, spend/year, average discount, etc.).

Results

• +3% ​Marginality per customer