Balancing the Buyer Equation: Understanding Customer Churn Rate
Customer acquisition grows your business; customer retention drives long-term success. Not surprisingly, companies are willing to spend time and money converting new customers to increase total sales. But as noted in the Harvard Business Review (HBR), the obvious costs of acquisition outpace those of retention by up to 25 times, depending on market forces and competition.
When it comes to retention, the potential for "customer churn" — which is the failure to retain customers over time — has a direct impact on retention rates. Churn rates vary across industries, with media providers and professional services losing 16 percent of customers on average while hospitality companies often struggle to reach 60 percent retention.
Balancing the buyer equation demands consistency across acquisition and retention. Here's what you need to know about defining — and calculating — the key variables of customer churn.
Defining Churn: The Basics
Churn is defined as "the attrition of an individual customer, either from the repeat purchase of a good or service, or the failure to re-purchase anything from a specific vendor."
Churn manifests itself in many ways, such as:
- Subscription cancellation
- Account closure
- Defection to competitors
- Decision to no longer purchase specific products
Despite the potential for lost revenue and increased re-acquisition costs, just over 30 percent of C-suite executives have reliable data around churn rates — making it difficult to develop strategies that effectively reduce churn.
Calculating Churn: The Mathematics
Repeat customers spend more money — up to 300 percent more than one-time buyers. Combined with the Pareto Principle, which states that 80 percent of sales come from 20 percent of customers, reducing churn becomes one of the most effective ways to boost growth and stabilize sales over time.
You don't have to be a numbers wizard to do the math. Calculating churn is straightforward: Divide the number of customers lost during a specific time period by the total number of customers during the beginning of that period. For example, if you have 100 customers initially and 20 of those leave during your set time frame, you have a churn rate of 20 percent.
Quantifying Churn: The Specifics
While the calculations are straightforward, quantifying churn as it happens is more complex. What's more, service providers and product retailers each face unique challenges in determining churn rates.
For service-based businesses, identifying churn seems simple enough: If customers choose not to renew their service agreement, they've churned. Of course, that's not the whole story. Consumers may opt-out of renewing services at any time during their contract, but companies won't know until the term expires. As a result, it's critical for providers to regularly gauge consumer satisfaction during the service period and take action prior to renewal.
Product retailers are faced with far less predictable spending patterns. Sudden drops in customer purchasing may not be tied to churn, but instead linked to health issues, vacations or other life events. Quantifying churn requires frameworks that specify common re-buying periods and average sales volumes to provide a general framework for churn metrics.
While the indicators of "churn-over" vary across service- and product-based businesses, the underlying cause is universal: Customer satisfaction. As noted in a Business 2 Community report, although 80 percent of companies believe their service is superior, just 8 percent of customers agree. What's more, most buyers won't give you a chance to bridge the service gap — 96 percent won't complain, and 91 percent will simply leave.
Understanding Churn: The Data First Approach
Definitions lay the groundwork, calculations deliver general churn rates and quantification helps determine the impact of business models on customer satisfaction. Collectively, these steps provide the "what" in customer churn by helping companies identify the actions customers and companies are taking — or not taking— that lead to reduced sales and lost retention.
Absent for most businesses, however, is "why". Understanding why consumers choose to leave lets companies target repeat consumers specifically and reduce total churn. This means figuring out if customers are leaving because another service offers better value, or because your product quality has suffered after changes in production.
Unlike "what," "why" demands specifics: Vague insights delivered by typical spreadsheets and business intelligence methods deliver vague outcomes — generalized approaches that help retain some customers, even as others leave without a word.
Here, a data-first approach is essential: Analytics tools capable of quantifying the impact of initiatives such as flash sales, coupons or direct customer outreach let companies understand where they're losing customers and identify which strategies deliver the best returns. For example, spreadsheets might suggest a link between coupon use and repeat purchases. Quantifiable data analysis, meanwhile, delivers coupon usage data over defined time periods for total sales, providing specific insight to drive specific action.
Balancing the Buyer Equation
We all know that some churn-over just happens. While it's impossible to completely eliminate churn, the value of retention far outweighs the effort of acquisition, meaning the shortest path to sustained growth is capturing — and keeping — consumer interest.
Balance the buyer equation by defining terms, calculating basic churn and quantifying what it means for your business. Then, refine your answer — go beyond "what" and understand "why" — with a data first approach to churn rate and customer satisfaction.
Getting started can be challenging, but Keyence is experienced in data-first strategies and data analysis, and is ready to help you get your projects off the ground. To learn more about how our AI, Ki can help, download the 3 Key Features Digital Brochure.
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