How to Reduce Customer Churn by Half in 120 Days


  • The best way to reduce customer churn is to prevent it from happening in the first place.
  • A shift from a static report that predicts which customers will defect to an interactive and predictive model that shows not just who, but why those customers are churning, with measurability, surfaces the root causes that can be resolved before they create customer attrition.
  • It's a shift in reporting from delivering bad news too late, to delivering an operating model to prevent bad news.
Johnny Grow Revenue Growth Consulting

A Predictive Model to Reduce Turnover by half in 120 days

The ability to improve customer retention delivers significant and sustained revenue growth.

Some folks believe the ability to accurately predict which customers are flight risks can improve retention. Our experience with clients shows that's not really true. By the time customers show up on a churn forecast they have incurred frustrations that have accumulated and festered for quarters or years. Offering apologies or assurances at this point is generally too little too late.

Knowing which customers will defect and being able to retain them are two different things.

A better approach is to build a prediction model that identifies the factors that contribute to attrition, measures each factor's impact to attrition and provides prescriptive methods to fix them before customers appear on a flight risk report.  This allows companies to be proactive and fix the problem before it happens.

CRM software systems such as Salesforce and Microsoft Dynamics 365 offer rudimentary but extensible customer attrition forecasts. They provide a starting point but are largely built on generic variables (i.e., firmographic data) and need to be supplemented with more precise data points, such as Customer Lifetime Value (CLV), Customer Satisfaction (CSAT), Net Promoter Score (NPS), Account Engagement Score (AES), customer sentiment, account health score, and RFM (Recency Frequency Monetary score) to deliver more accurate predictions.

The CRM reports also don't advise why customers defect, how to reduce turnover or show the upside financial impact of improving or resolving any individual cause of defection.

To shift from a reactive report to a proactive program, Johnny Grow extends the default CRM churn report. We start with the basic data and enrich it with the causes of loss, the methods to reduce attrition, and the KPIs that most impact revenue. These additional data points create an interactive model that shows how to reduce customer loss.

Below is a dashboard screen shot of one interactive model.

Pro Forma Customer Churn Interactive Model

The additional data included in the above dashboard empowers companies to improve customer retention by extending the default CRM software black box static report to an interactive model. This model shifts attrition prediction from a report built on lagging indicators to a prescriptive way to prevent attrition.

Knowing why customers defect is much more powerful than knowing which customers will exit as it allows companies to prevent attrition before it happens.

Develop an Early Warning System That Works

We've been implementing customer service technologies and CRM software for over three decades, so we've experimented with several ways to produce attrition models that work. Our learning has left us with a framework that works every time. Below is the Johnny Grow 7-step framework to create customer churn predictive models.

Customer Churn Prevention Framework

See the Customer Churn predictive model that advises not just which customers will defect, but the factors that drive attrition. That data allows companies to fix the root causes of attrition and prevent it from happening.

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Note that the above framework is designed to prevent, not just predict, customer attrition. That's an underlying difference that shifts the overarching goal.

  1. Identify why customers defect. First, you need to know specifically and measurably why customers leave their suppliers. Most companies think they know but they are only partially right. And the part they don't know goes unresolved and continues unabated. They also fail to recognize that imprecise remediations can have a negative impact on company profits. Different customer segments leave for different reasons, so short-term fixes that apply to the broadest spectrum of customers can result in failing to satisfy or even losing the highest value customers.

Another common challenge is failing to recognize the causes of customer churn change as customers and your business evolve over time. There are likely reasons customers left your company last year that are not the same as why they are leaving this year. Understanding why customers defect requires continuous measurement.

  1. Find out what customers want. If you want to reduce the number of customers that leave you need to know what customers want in order to stay. The best way to do this is to implement a Voice of the Customer (VOC) program. VOC data can identify and prioritize what customers most want. The table in the above model titled Retention Services are services that customers requested as part of a VOC program.
  2. Show financial impact. No customer service or retention improvement method is sustainable if it can't show a profit to the company. It's essential to identify and measure the most important key performance indicators (KPIs) that drive business outcomes and company profitability. If your KPIs are not demonstrating clear and direct monetization than they are not the top KPIs. For most companies, the top KPIs will include, but not be limited to, customer satisfaction (CSAT) and customer lifetime value (CLV).
Customer Satisfaction (CSAT) Predictive Analytics
  1. Include leading indicators. Most customer attrition forecast reports are built entirely on lagging indicators. These factors make up a minority of the Johnny Grow model. For more accurate results, we use several leading indicators such as Account Health Score, Account Engagement Score and Customer Satisfaction score.
  2. Create the interactive model. Once you have the prior data points, you can create a predictive model to identify and measure which customer services levers deliver the biggest financial upside and are thereby sustainable. You can also eliminate programs or services that consume time and money but deliver little or no financial impact.
  3. Display insights in a real-time dashboard. Visualization promotes action. The Customer Retention dashboard delivers at a glance previews of the most impactful information and allows drill-down for supporting content.
  4. Use best practices. We accelerate time to value and de-risk programs when we apply evidence-based best practices for customer service or customer retention improvements. Our evidence-based best practices are born from research and firsthand experience, codified into prescriptive guidance, and designed to replicate the processes used by the Best-in-Class leaders (i.e., the top 15 percent). No need to reinvent the wheel.