Case study

Unlocking Revenue Potential: How SG Analytics Empowers a Client to Maximize Profits with Data Science-Driven Cross-Sell & Upsell Strategies

SG Analytics Case Study Data Analytics


Our client, who is a leading financial intelligence provider, wanted us to identify cross-sell/upsell opportunities among its customers and increase revenue growth.


  • 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.


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.


Out of the 3,400 identified customers, 849 added a 30%+ revenue growth.


  • 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.

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