Acquisition of Customers
The Mahou beer company needs to optimize its customer acquisition strategy in the hospitality sector. Currently, this strategy depends on the empirical knowledge of its sales representatives, which limits the effectiveness and scalability of the process, due to the subjective component that is presented. The main challenge is to identify the competitive bars most likely to be attracted, based not only on their similarity to current customers, but also on their profitability, considering factors such as sales volume and prices. The lack of an automated, objective system that combines these variables makes it difficult to prioritize business efforts strategically.
We developed an advanced clustering algorithm that segments bars based on their key characteristics, using HDBSCAN and reducing dimensionality with UMAP to maximize the segmentation capacity of the algorithm. This system generates an initial ranking of competing bars that are more similar to Mahou's current customers. This ranking is then reordered according to a profitability indicator that weighs factors such as sales volume and prices, resulting in an optimized final ranking. The results are directly integrated into Mahou's CRM, providing salespeople with immediate access to detailed information about priority bars, their characteristics and the reason for their inclusion in the list.
This solution transforms Mahou's recruitment strategy, providing a data-based approach that replaces empirical criteria. Commercials now have an optimized ranking that prioritizes bars with high recruitment potential and profitability, maximizing the return on sales visits. With this system, Mahou can direct its efforts towards the most strategic Points of Sale, increasing commercial efficiency and strengthening its position in the hospitality sector.
