Churn analysis in eCommerce

The cost of acquiring a new customer is by far higher then the cost of retaining an existing customer. Analytics can help you know in advance which customers are going to churn and why.
It is important to analyse your customer data to identify which customers are most likely to switch to a competitor and why, so that you can implement a targeted and cost-effective retention campaign in a timely fashion.
Once your churning customers have been identified you can act proactively and take action on this business to prevent their leave.

Companies can’t afford to lose hard-won customers, but in truth some customers are more important to keep than others

 

What is Churn or Defection Rate

Your churn rate is the amount of customers or subscribers who cut ties with your service or company during a given time period. These customers have “churned.”

Depending on your business, churn rate can be calculated in many different ways, including:

  • Number of customers lost
  • Percent of customers lost
  • Value of recurring business lost
  • Percent of recurring value lost

All this formulas must be referenced to a “moment” in time or “period”. For example, we can calculate customer churn as the number of clients lost at the end of the current month, divided by the number of clients at the start of the month.

Tracking customer churn is important because of the benefits for your business:

  • Marketing costs are expensive; you need to keep customers to make your money back.
  • You need to know your customer churn rate so you can calculate your customer lifetime value (clv).
  • Your churn rate has a direct impact on the ability to grow your company.
  • Tracking changes in churn rate lets you identify if what you’re doing is improving customer churn or having a negative impact.

Churn Rate has traditionally been used by businesses relying on recurring revenue models, more specifically in contract based business relations (banks, utilities, insurance, etc.). Many of today’s leading ecommerce companies are also adopting the metric.

For subscription businesses, a low churn rate can be the difference between life and death.

 

Identifying ‘at risk’ customers

Predicting and preventing customer churn should be a top priority, but most companies struggle to identify the reasons for churn.

Churn can’t be analyzed without a 360º view of your customers, including sales, contract information, usage patterns, and demographic profiles. Multi-scale customer segmentation capabilities help identify distinct sub-groups of customers inclined to churn and characterize their preferences and situation. We also can calculate clv.

By more precisely defining customer segments to examine the reasons for churn, you will be in a better position to put steps in place to increase customer retention.

Identifying customers at risk of churn for ecommerce is not easy, but doable, and well worth the effort. The key difference for non-subscription-based ecommerce companies is that they need to clearly define what constitutes a churn event. For example, if a company knows that most of their customers who will make a repeat purchase do so within 90 days, they may choose to mark any customer who has not made a purchase in that time period as being “churned.”

We propose a method to target customers that potentially boosts a company’s profits in a big way, 3 digits percents on average when compared to standard retention targeting effort. The solution does not involve offering incentives, such as discounts, to all individuals identified as likely to defect. The tricky part comes in figuring out exactly who should be targeted to maximize profit. We take into account the complete value of the customers (clv) you are trying to retain.

Our method leads to better predictions where it matters most for a company’s profit by allowing companies to target their most valuable customers while reducing the cost of the incentives.

Keeping under control your churn rate will help ensure the long-term growth and health of your business.

Rodolfo Lomascolo, October 2016