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Improving client retention with AI


Python, scikit-learn, LightGBM, Streamlit

Our client, a leading player in the telecommunications industry, grappled with a prevalent issue: their expansive customer base was reaching saturation. This saturation, while indicating their market strength, posed a significant challenge. They wanted a way to make their marketing efforts more cost-effective by focusing their efforts and budget on customer’s that have a high probability of converting. The goal was clear – boost cross-selling by making marketing initiatives sharper and more tailored but it’s not always that easy. Cross-selling is a vast area and solutions come and go.

To tackle this, we turned to data, curating a unique two-step AI model. First, we pre-processed the available information, filtering out the noise to ensure our model could discern genuine customer interests. Then, using advanced algorithms, we predicted cross-selling opportunities with a striking degree of accuracy. But data on its own isn't actionable. That's why we encapsulated our findings in an intuitive dashboard. Sales representatives could, at a glance, identify which products were potential fits for each customer, leading to tangible results in cross-selling success.

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