Arresting Churn through Machine Learning for Digital business

Project Overview

A high churn rate of 60% was seen by the client’s small and medium business (SMB) customer base, which operates a lead generation business in the local services sector. Indium Software was chosen to examine historical transaction data and customer data in order to ascertain the causes of churn, the traits of churners, the buying cycle phase of churners, and elements that could assist in preventing churn.

About Client

The client is a leader in the $200B local services market in India and for NRIs in the USA, Canada, UK, and UAE. Their platform is designed to help users minimize the time spent on finding the right local service provider, reduce service costs, and minimize the hassle of dealing with service providers. With a user base of 25 million and 5 million businesses serving them each month across various local service categories and geographies, the client has established a strong presence in the industry.

Business Challenges

  • The client operates a lead generation service in the local services space and has been experiencing a high churn rate among its Small and Medium Businesses (SMB) customer base.
  • The sole point of contact the client had with its SMB customers was through a business app. However, a significant number of customers had not yet started engaging with the app.
  • As a result, approximately 60% of customers churned out of the system. The client sought to address this issue by gaining insights into the characteristics of these churners.