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Think about it — they're one of the few things still in existence today that only gets better with age. Like fine wine, classic cars and the right pair of jeans, loyalty programs age well — with the right maintenance and strategy.
However, without the proper predictive model, your loyalty program could die on the vine. Ensure that you're assessing your program correctly by evaluating these four metrics.
Breakage is the percentage of outstanding points that will ultimately go unredeemed. It's the first thing our clients ask us about because they want to make sure they aren't at risk of an unwelcome surprise. It's on the tip of everyone's tongue; no one wants to be responsible for a massive and unexpected point redemption.
This is why every loyalty program's breakage should be constantly and accurately assessed. Having a reliable breakage estimate will provide insight into the program's liability. It's also necessary for financial reporting. You won't be able to close your quarterly books without knowing an accurate breakage estimate.
However, breakage alone doesn't paint a full picture of the health of a loyalty program. For example, if you were to eliminate expiration dates on points, your breakage would go down with more points being redeemed. But your Customer Lifetime Value would likely go up because, with more points in members' accounts, you have an incentive mechanism to increase member engagement.
The goal of any loyalty program manager should be to increase Customer Lifetime Value, or CLV. CLV represents the dollars a particular program member has spent to date plus the expected future profit. It can be difficult to correctly assess; some members may have spent a large amount initially, but are becoming slowly less and less active. These members could still be placed in the "top tiers" of the loyalty program because of their initial spend, but aren't worth their program title designation in future dollars.
On the other hand, a member in a "lower tier" of your loyalty program, who may have spent a minimal amount initially, could be worth more than the "top tier" member. It's important to keep in mind that 80% of your loyalty program's profit comes 20% of its members. The member in the lower tier could be predicted to spend a great deal with your program and have a high Customer Lifetime Value.
This is why CLV can be so great for allocating your acquisition spend. Investments by acquisition channel should be based on the CLV that channel returns, rather than just the associated acquisition cost.
Customer Future Value, or CFV, is a member's expected future revenue subtracted by the member's expected future cost, including the cost of future redemptions. CFV can be a solid focus for programs as it doesn't allow past behavior to sway opinions of future behavior. CFV is derived from a multitude of different data-points and is the key to the future strategy and spending of any successful loyalty program.
Loyalty programs that incentivize customers with high CFV are those that are the most profitable (just think of Amazon Prime). It's important to note that these members with high CFV could be hiding in the "lowest tier" of your loyalty program. Predictive models identify these members using all types of data-points allowing you to best incentivize these members to ensure their highest participation in your program.
Customer Potential Value, or CPV, is very similar to CFV, in that it involves future value. The key here is the potential. CPV represents the increase in CFV that could be driven by a small change in member engagement. Identifying members with the highest CPV will allow you to incentivize them accordingly and increase their future profit above your current expectations.
For example, if you were to send 1,000 free points to every member of your loyalty program, some members would do nothing, equating their CPV to zero. Some would redeem those free points and take no other action, making their CPV less zero. However, some would be incentivized to increase their engagement with the program making their CPV greater than zero. Understanding how to calculate CPV and identifying the members in your program with the highest amounts of it and then providing them with incentive (e.g., 1,000 free points) will increase your program's profit substantially.
When you have an accurate breakage assessment and identified members with high CLV, CFV and CPV, your loyalty program will start to become immensely profitable. You'll be able to specifically target individual and high-value members offering them what they want before they ask for it.
Unfortunately, a spreadsheet and a few equations won't tell you everything you need to know about breakage, CLV, CFV and CPV. However, a predictive model will. Predictive models like KYROS has built respond to a wide array of predictors that are in-depth at the individual member level. KYROS' intuitive dashboard provides analysis of member behavior, including member activity, redemption history, and earning patterns so that your loyalty program can succeed.
So give yourself the tools necessary to compound the profits of your loyalty program and enjoy its profitable longevity.
Founder and managing partner of KYROS Insights. I'm an analytics nerd and recovering actuary. I use machine learning to help loyalty programs predict member behavior so they can identify their future best customers, and recognize and reward them today.