Prediction of Next Best Product

Challenge

Leveraging the existing customer base to expand business across various product lines is often managed by the field sales force in the traditional insurance sector. Employees frequently prioritize customers heavily based on experience rather than data-driven or objective criteria. Our client, an international insurance company, faced the challenge of calculating the affinities of all existing customers in the main product lines to provide targeted prioritizations for their sales force.

Approach

Using all available customer and product data, we collaborated with our client to develop a machine learning model that predicts customer affinities in relation to five main product lines. The model is based on information from various core systems, such as inventory, CRM, and mutation data, which are weighted by the model to generate the most accurate forecast possible. After creation, the model was implemented into a database to regularly score the entire customer base and provide the results.

Result

The information available in the database is visualized in an interactive dashboard accessible to employees. They can now use various filters to selectively target customer groups and segments and view individual customer affinities within the selection. This empowers them to initiate targeted sales and acquisition measures.