Case Study: Local Services Market reduces churn with Indium Software’s ML-powered churn analysis

Churn Analysis through ML for a fastest growing Indian Digital business

Local Services Market, a leader in India’s $200B local services market and for NRIs in the US, Canada, UK, and UAE, was facing high churn among its SMB customer base—around 60%—despite running a lead generation service. Since the only customer touchpoint was a business app that many users had not yet adopted, the company struggled to understand which businesses were seeing value from the platform and which were at risk of leaving.

Indium Software analyzed raw customer campaign data and used R and Python to structure it for machine learning classification models, including Decision Trees, CART, and Random Forest. Indium Software identified high-risk churn cohorts and the factors driving churn, such as lead deliveries, paid amount, and time elapsed, with the highest churn risk occurring in the first six months. Based on these insights, the client launched a Customer Happiness Team to target risky accounts and reduced churn by 10% within six months, improving renewals and customer lifetime value.