Not managing your churn is like running backwards on a treadmill blindfolded while lighting $100 bills on fire… eventually you might reach your goal weight, but you look like an idiot and waste a lot of money in the process.” – Lincoln Murphy, Sixteen Ventures

It’s now 2015 and the digital marketplace is crowded no matter what field, industry, sector or silo you are operating in. With a crowded market comes noise and an ever-increasing cost of customer acquisition. Since it’s more expensive than ever to attract new users, it is mission-critical that CEOs give upmost priority to reducing customer churn and maximizing the lifetime value of their customers.

First things first, a definition: Your churn rate is the amount of customers, users or subscribers that leave your service or drop your product within a specific period of time. The opposing name for this is “retention rate” – the amount of customers, users or subscribers that stick with you in a given period of time. We want to minimize churn, which can also be stated as maximizing our retention rate.

Next, here’s how we calculate our churn rate:

# of customers lost / # of customers we started with = our churn rate

Churn Rate Calculator

For example, on January 1st, 2015 we had 100 customers and 5 of them left by January 31st, 2015. Our customer churn rate for January was 5%. Not bad, right?  WRONG! A 5% monthly churn rate equals 46% annual churn rate! This level of churn will lead to your board of directors firing you as the CEO or worse, it will bankrupt your company.

This is an oversimplified example to drive the point home. Churn can be tracked by the number of customers lost, the monetary value of the business you are losing, or the percent of recurring revenue going out the door each month. Furthermore, your specific calculations will consider many other factors specific to your industry and business model, not to mention offsetting metrics like expansion revenue.

Regardless of how your calculate your churn, tracking your retention metrics is a requirement for success. It’s usually far less expensive (and easier) to retain your current customers than it is to go find new ones.

Now that we’ve covered the importance of tracking your churn rate, now you need to identify what actions will result in an overall lower churn rate, right? WRONG! Focusing all of your energy reducing your churn rate is NOT the main goal because not all customers are equal. The truth is some customers are simply more expendable than others.

If you make “reducing churn” your overall goal, you’re taking a blanket approach to a very complex, nonlinear problem. Right now, you’re probably approaching your customer attrition strategy something like this:

solve customer churn

  1. Ranking your users based on the likelihood they are going to leave.
  2. Then, offering incentives and discounts to core users who appear at the top of your ranking. 

The problem with this retention strategy is that it’s not effective in maximizing bottom-line profit because it ignores the overall profitability of your customers, broken down by segment.

As competition grows and the fight for new business becomes increasingly fierce, it is imperative that you measure the net profitability of your customer churn reduction efforts. In order to maximize profits through customer retention, not only must you track the probability of users leaving you, but also how much those individual users spend with you, the likelihood they will even respond to an offer, and the costs associated with your retention strategy.

In broad strokes, we’re using the 80/20 principle: 80% of your profits are generated by 20% of your users. Breaking it down a bit further, we realize we must answer the following questions:

  1. Who are our most valuable customers?
  2. Where do they sit on the “likely to leave us” scale?
  3. How likely are they to respond to an incentivized offer to stay?
  4. How much will it cost us to execute an effective incentive program?

By segmenting our customers into groups of profitability, readiness to leave, and their likelihood of a positive response to our promotion to stay, we can create a predictive model to customer churn. Identifying these segments will help us determine the optimal balance of who to target, what to offer them and how much we should spend to keep them. 

If a high value customer appears to be ready to leave us, but the cost of our retention offer is high and likelihood of a positive response to our efforts is low – we shouldn’t bother sending it. While we don’t want to lose high-value customers, targeting too many of them with an expensive retention campaign will become too expensive to have a positive net impact. 

This predictive method to reducing customer churn is not perfect and it will take some trial and error to customize it to your specific market and business model. However, this approach will lead to an increased focus on what matters most to your business (and to your investors): the bottom line.