One of the biggest challenges was understanding demand patterns and, from there, determining the ideal frequency for communications and visits to each client.

The goal was to increase sales by maximizing the value obtained from each type of client. Faced with this challenge and an increasingly competitive market, it was crucial to thoroughly understand the behavior of their clients.

Solution

At Strategic Platform, we have developed advanced predictive algorithms that, based on historical data and purchasing patterns, allowed us to group and segment your customers according to different variables.

Once all this information was extracted, we created AI models that would allow us to achieve the proposed objectives: a clustering model by sectors and similarity in historical patterns of purchases, a demand classification model according to its behavior in terms of time and purchase volume, and a forecasting model for users based on their purchasing behavior.

By correctly grouping customers and being able to predict their purchasing behavior, we had achieved the goal of creating a final model that allowed us to find the optimal frequency with which Würth should contact its customers. Based on this information, communication and/or visit plans were developed according to the physical capacity and availability of each salesperson, using advanced Optimization tools.

The impact of this project was truly significant, as not only did we find the optimal frequency of contact, but during the modeling process we were able to gather very valuable insights for the company that allowed them to better understand how their business was performing. Additionally, through collaborative work with their analytics team, we were able to train the client in the solution so that once the project was completed, Würth could use it independently.