The Light Bulb Moment: Customer Churn

By Team Session AI on March 6, 2021

The customer drop-off and how to prevent it  

Customer churn, also known as customer attrition,  is a vital metric for companies to monitor. It is fairly simple to understand and calculate, unlike many other business metrics that companies must track. Essentially, we can think about customer churn as the proportion of people who, after opening a company’s site, scroll for a bit and then close the window. On a deeper level, customer churn may also refer to the proportion of people who build a relationship with a company, and then they take their business elsewhere. Whether their reasons are dissatisfaction or disengagement, the fact remains that they disconnect, and customers dropping off is unquestionably a negative thing (unless you’re the competition).  

The goal is to keep customer churn as low as possible; you want to keep your customers loyal to you.

How is customer churn calculated?

 A simple way to calculate customer churn, as demonstrated by a HubSpot article, is by determining the percentage of customers lost during a certain time period.

That same article outlines a few different ways a company can calculate customer churn, depending on its needs: the number of customers lost, the value of recurring business lost, or the percentage of recurring value lost. However, calculating this number—through any given lens—helps your company little, unless you can figure out how to push the number down. Though 0% may not be an entirely achievable number, keeping your number as close as possible to it is desirable. Hence, the question arises: how?

Why is customer churn important?

In a study done by McKinsey about applying personalization to the energy industry, one company found that “intervening quickly with a personalized approach to [customers with an 85% probability of canceling their contracts] reduced churn by 15 percentage points compared with a control group” (1). Even in the energy industry, where customer relationships aren’t the first thing that comes to mind in terms of priorities, personalization goes a long way in terms of reducing customer churn. Applying this logic to retail, where cultivating customer relationships is paramount, the effects of personalization in reducing customer churn are just as significant, if not more so. 

The psychology behind this is simple: Customers are less likely to churn if they feel cared for. 

How to reduce customer churn?

Usually, there are detectable signs that a consumer is on-the-fence; if we analyze trends of consumer behavior, we can pick out patterns that lead us to the inevitable drop-off. Armed with this knowledge, the way to transform the inevitable into the preventable is through predictive engagement. If we can detect customers’ dissatisfaction or disengagement in real-time and pinpoint precisely their points of indecision, we can offer them just what they need and convince them to stay. Show them that what they are looking at is right for them.

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