For loyalty program accounting and finance professionals, it's key to know that you're accurately measuring customer loyalty. To do it right, you’re going to need to understand four healthy loyalty program concepts:
- Predictive customer lifetime value (CLV) is essential
- Customer potential value (CPV) can increase CLV
- Retention is better measured in dollars
- Prevent customer lapse or inactivity before it's too late
Without robust tools, the measurement of customer loyalty and retention can be difficult — and nearly impossible to predict. Let’s begin with understanding how predictive Customer Lifetime Value will give you a better sense of the state of your company’s loyalty program.
Why Predicting CLV is Key
Customer Lifetime Value is the central data point that paints a clearer picture of program performance on the member level. It's important to understand the complexities of CLV.
You should adopt a model that not only tracks members' historical behavior and spend, but how much they will ultimately spend. Think about it — if 20% of the customers in your loyalty program are responsible for 80% of its future profit, then identifying this 20% is vitally important to the health of the program. It will help you understand which members stabilize the liability of your program.
If you have reason to believe that any member of this highly profitable group could potentially become inactive, immediate action should be taken. These are your loyalty program heroes — it’s cost-effective in the long term to spend money trying to further incentivize high-value members.
CPV | Customer Potential Value and its Influence
Let’s step back and assess the loyalty program as a whole:
You will have members that are extremely profitable, members that are moderately profitable but either less frequently active or active in small dollar amounts, and members in danger of lapsing or becoming inactive. Some of these moderately profitable and potentially inactive members could actually have a high Customer Potential Value or CPV.
CPV is seen in healthy loyalty programs as a tool for boosting CLV (Customer Lifetime Value). It identifies members who may not be very profitable today, but have large upside potential to become extremely profitable. These members should be given a financial nudge in the right direction. This strategic decision will maximize ROI in your program long-term.
Also, this practice will help with your loyalty program’s retention rate.
Retention | What to Focus On
Retention in loyalty programs is measured differently than in other customer models. Unlike a contract-based customer (think annual cell phone plans or your Netflix subscription), it’s not always clear whether or not a member has churned.
A good way to measure retention in the case of loyalty programs is to gauge a member's activity within the last 12–18 months. The term specific member here is key. As previously mentioned, a healthy loyalty program takes special care of the 20% of members that provide the program 80% of its profit. Measuring which specific members are a part of this group can help you decide those most important to retain. Not all members at risk of lapse are essential to your program. It is important to focus your retention efforts on members with the most money at risk.
By measuring the loyalty program's health based on the retention of dollars instead of people, its value can be much more accurately assessed. Adopting a model for measurement of customer loyalty and retention will also prove beneficial when it comes to the program’s liability remaining stable — the last thing you want is quarter-to-quarter unpredictability in your program.
Predicting (and Preventing) Customer Lapse
Once a customer has been inactive for 12-18 months it’s generally too late to retain their business.
Stabilize your company’s loyalty program by enlisting a model that predicts customer inactivity. It's essential to the strength of your program that you take preventative measures when a customer shows signs of future inactivity. High value members should be directly addressed when they show warning signs of lapse.
How can you tell if a member is about to lapse and become ultimately inactive in your program? You should look to your predictive CLV model here. If you notice a high value member’s CLV has begun to drop, this could be an indication that they are at risk for lapse. Member lapse and inactivity are ultimately preventable — your program just has to be using the correct tools to identify and prioritize these high-value members.
The Bottom Line
Adopt a model that helps make measurement of customer loyalty and retention easy. Protect your program’s value and maintain its stability by adopting a predictive model. Learn more about loyalty strategy here.