Data & analytics driven customer retention framework

Jul 25, 2016 • Ravi Mehrotra & Swapnil Srivastava

Managing customer churn is vital to business performance. As is researched and proven, a 5% improvement in customer retention rates increases profitability by 25 to close to 95%, as it is many times more expensive to acquire new customers than it is to retain an existing one. Understanding controllable and uncontrollable drivers of customer churn is essential in order to increase customer engagement, and designing short- and long-term retention strategies. Here are five steps that companies can use to develop their churn strategy:
  1. Define churn: As the first step, companies need to define what churn is, keeping their business in context and the category of customers they wish to retain. This depends a lot on their risk appetite. For instance, a highly risk-averse company would like to be alerted when a customer has not made a transaction in the last one quarter or if the revenue from that customer in the current period is less than 50% of the average value over a specified period. On the contrary, a risk-taking company can have more aggressive thresholds.
  2. Develop a hypothesis map: There are multiple reasons, controllable and uncontrollable, why customers switch. Companies should leverage research (primary or / and secondary) and experiences (business and field) to generate a list of potential churn triggers. While hypothesizing these triggers, companies should factor in their customers’ point of view and use their experience as the base for a hypothesis map. They can use multiple touchpoints and / or relationship stages to define potential churn triggers. For example, companies may plot macroeconomic, product, and customer transaction data, along with experiences and market competition factors. This hypothesis map becomes the basis for predictive models to be developed in the next phase of the project lifecycle.
  3. Build a predictive model: A data-mart that includes quality data should be created so that companies are able to establish a link between various internal and external data elements mentioned above. This data could be further used for segmenting customers based on their spend patterns and other identified drivers. The Modeling technique should be shortlisted after developing a thorough understanding of all the data elements (missing values, outliers, distributions, etc.) and customer purchase behavior. This model will not only help identify customers at-risk of attrition but also the triggers.
  4. Create an action item matrix: Actionable insight is key to a successful analytics project. For this purpose, companies must develop an action item matrix (a framework that brings together the results of the model developed and specific KPIs such as probability of churn and customer lifetime value) to prioritize retention efforts and determine ROI for that effort. The matrix will further help in identifying up-selling and cross-selling opportunities and ensuring adoption of the retention framework.
  5. Implement a retention strategy: A robust retention campaign effectively focuses on churn triggers and enables the development of strategic “retention building blocks” that are targeted for the distinct customer segments of a business. By helping generate higher revenue and ensuring maximum profitability, companies will be able to get high ROI on these campaigns.
Do these 5 steps really work? Let us use hard evidence to answer the question. We put these 5 steps to practice for a dealer network of a global heavy machinery and equipment manufacturer. The client recorded on an average additional sales opportunity of USD 25–45 million per dealer. Learn How!