How do I boost results with my loyalty program by better tracking my customers’ value?

Loyalty programs are primarily designed to concentrate spending (share of wallet) and lengthen the customer relationship (retention). On average, most of them are successful at achieving these goals to some degree.

Then again, on average most loyalty program results are, well, average. But what else would you expect when objectives are set and results are measured to the average?

This is what we call the Mercury Law of Averages: if you define success in terms of average performance targets -- “On average, we want to bring in X members per month and have them spend $Y per year” for Z years”-- you are very likely to achieve average performance.

Breaking out of this “average” trap requires a strategy shift in enrolling better customers: understand the differences between customers and then use that insight to develop customer strategies based on where they are in the lifecycle and the potential value they represent. Once you have done this segmentation, you can begin to track how customers are moving from one segment to another over time.

For example, here is a simple customer migration report that shows how customers are shifting from segment to segment over time:

2008

2007

Very High

High

Medium

Low

Lapsed

Very High

50%

23%

13%

9%

5%

High

15%

30%

30%

19%

7%

Medium

4%

14%

35%

36%

11%

Low

1%

4%

17%

48%

30%

Lapsed

2%

6%

22%

69%

N/A

Here’s how to read this chart: of those customers who were in the “Very High” value group in 2007, 50 percent stayed in the “Very High” group in 2008, 23 percent slipped to “High”, 13 percent fell to “Medium”, and so on. Conversely, 15 percent moved from “High” to “Very High”.

The percentages provide focus as to where the largest shifts are in terms of the number of customers, but overlaying revenue onto this chart (average annual revenue by segment) will reveal where the large ROI opportunities lie.

For this client, the most obvious place to start was with customers who lapsed in 2008. In total, this group represented over $130 million in potential revenue that was not realized. This information could possibly lead to the development of a new retention strategy or a lapse/recapture program.