One of the advantages of identifying loyalty & incentive program customer tiers is the ability to identify (and reward) your best customers, and incent your lower performing customers to buy more. But there’s also the potential to identify movement between tiers. Understanding purchase trends, including up-trenders and down-trenders, can provide an early warning system for customer defection.
The Trend Analysis design is fairly straightforward … it looks at the percent of customers increased or decreased their spending in the current time period vs. the previous time period. Or, in loyalty program terms, it identifies how many members moved between member tiers and how many left the program.
Let’s say, for example, that a loyalty program retains 82% of members this year vs. last year. Assuming 1,000 members, that means that the program lost 180 members. Where did they do? How many were highest vs. lowest value members? With a Trend Analysis, we may find that only 5% of members in the highest tier (Platinum) left the program, while 64% in the lowest tier (Silver) left the program. This is what we would expect – Platinum Tier members spend more and have the lowest defection rate, while Silver Tier members spend the least and have the highest defection rate.
But the analysis can reveal the movement of members between tiers. For example, it is valuable to learn what happened to our prior year Platinum members. Assume that 78% of Platinum member remained Platinum, but 12% fell to the next tier down (Gold) and 5% fell to the Silver tier. We may expect to see this behavior year-over-year, but if the downtrend accelerates, a more fundamental problem may exist.
Similarly, we may want to learn about member behavior in other tiers. It can be useful to understand the percent of Gold members who up-trended to Platinum, the percent that declined to Gold and Silver, and the percent that defected.
Initial Trend Analysis can establish a baseline for each tier. For example, we may learn that 78% of Platinum Tier members stay Platinum period-over-period, compared to 51% of Gold Tier members who remain Gold, and just 29% of Silver Tier members. Significant changes to the baseline may signify fundamental issues that need to be addressed.
Loyalty program managers can use this information to provide promotional incentives to targeted members that are spending less or at risk of defection, in addition to gauging the overall health of the program. Further analysis using surveys and other tools can be used to better understand the specific reasons for changes in member behavior. It would be incredibly valuable to understand why 5% of Platinum members left the program, whether due to voluntary or involuntary reasons such as lifestyle changes.
Trend Analysis can be done in shorter time periods, for example quarter over quarter, which can be particularly valuable when a competitor makes changes that impact member loyalty. Trend Analysis can also look at the behavior over time of new vs. existing members and other segments.
Contact Vanson to discuss how you can leverage loyalty & incentive program data analytics.
