BUSINESS SITUATION
Our client, who is a leading financial intelligence provider, wanted us to identify cross-sell/upsell opportunities among its customers and increase revenue growth.
SGA APPROACH
- Analyzed the historical data of existing customers related to their revenue, spend, firmographics etc.
- Identified the threshold ($40K) to cluster the customer as low spender and high spenders
- Trained a classification model looking at the high spenders and applied the model on low spenders to identify potential opportunities
- We identified 3400 potential customers whose ACV (Annual Contract Value) was less than 35K (low spenders) and had high growth potential
- Performed SHAP and LIME modelling to identify key factors for each of the 3400-customers contributing to the classification model, which created confidence to the modelling output
- Trained ML-based model to identify the association rules between existing products and recommended products that could be used for cross-selling for each customer.
ENGAGEMENT
We built a customer segmentation model to analyze historical data of the client's existing customers based on revenue generation and identified the customers with low ACV using a classification model that was trained on historical data.
BENEFITS AND OUTCOMES
Out of the 3,400 identified customers, 849 added a 30%+ revenue growth.
KEY TAKEAWAYS
- We helped our client’s sales team to narrow down customer calls and increase conversion rates.
- This solution not only identified the target customers but also helped the sales team with the recommended products to achieve the target.
