Customer Churn

The purpose of this dashboard is to identify trends (positive and negative) in Customer Churn. -  specifically, if a business is either gaining or losing customers faster.  When Churn is examined as a trend, a business can assess the effectiveness and efficiency of marketing methods. To drill into marketing channels and specific campaigns, use the filters.

Churn is the number of customers who canceled their relationship (subscription) within a designated date range. These customers have “churned.”  Said another way, Churn Rate is simply the percentage of lost customers compared to total customers at the beginning of the date range.

  • The higher the churn, the more customers lost.
  • The higher the Net Churn, the more customers gained.

Customer Churn = Customers Lost ÷ Customers at Start Date

The Customer Churn measure can provide an insight into several operational and/or marketing activities:

  • How clear is the offer
  • How effectively is customer service handling customers
  • How quickly is the business growing or shrinking from a pure customer quantity perspective - are customers being acquired quickly enough
  • etc

 Additionally, there is a second Churn measure to understand when considering Customer Churn - Net Churn.

Net Churn Rate, which goes further, takes into consideration customers gained within the period being analyzed - not just customers lost.  

Net Churn = (Customers at End Date - Customers at Start Date) ÷ Customers at Start Date

 If a business's Net Churn is increasing, it will be gaining more customer's than it is losing; its customer base will be growing.  Said another way, positive Net Churn increases a customer base.  Negative Net Churn indicates that the customer base is reducing.

Additionally, the rate at which customers are churning is vital to the Customer Lifetime Value (CLTV) measure since the longer a customer is retained, the higher the CLTV. Since CLTV is one of the more important factors, indicating the highest cost a company should pay to acquire new customers, one can understand that Customer Churn is a vital indicator of probable success.

To help improve understanding, we have created some standard language.

 Ending Unique Customers  =  EUC
 Starting Unique Customers  =  SUC
 Lost Unique Customers  =  LUC
 EUC - SUC  =  Net Change

Using the above, the formulas used to calculate Customer Churn Rate and Net Churn are:

  • Customer Churn Rate equals  LUC / SUC
  • Net Churn Rate equals  Net Change / SUC

The Customer Churn dashboard also provides key measures specific to helping fine-tune marketing efforts such as eCPA (effective Cost Per Acquisition) and MER (Media Efficiency Ratio). Use these two measures to help adjust the CPA and to determine how specific marketing channels (i.e. email marketing, display advertising, organic search, etc) compare from both an eCPA and MER perspective.

Potential Actions

  1. Consider the impact to Customer Churn Rate that can be achieved by making modifications to campaign and/or operational procedures (i.e. modify customer service scripts on how cancellation calls are handled, alter fulfillment procedures to decrease time in home (how long it takes a package to get to the customer), modify internal refund protocol to inspire a larger percentage of partial refunds and save sales, etc).
  2. Perform deep channel evaluation of campaign traffic (i.e. affiliate, paid search, email marketing, etc.) to improve the efficiency of new customer acquisition - measured through the eCPA and MER measures.

  • Data presented in this dashboard is based on "Transaction Date" unless otherwise noted. Transaction Date is the date that the order was placed without an association between the Re-bill and Recurring transactions (Cycles 1…X) and the Initial transaction (Cycle 0) that initiated the order.

  • All orders marked as "test" within the platform are automatically removed from the Analytics data.

You may find the following Help Center articles relevant to Analytics helpful.

  1. Analytics Overview
  2. Glossary of Measures
  3. Glossary of Terms
  4. How to use Filters
  5. Analytics Vs. Reports - Data Calculation Methodology
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