It’s not enough to simply have a loyalty program.
After launch, optimization is the key to the long-term success of your loyalty program. One of the greatest benefits of having a program is collecting a significant amount of first-party customer data that can be used to accomplish this.
Refining and optimizing your loyalty program over time is done through mining customer data and listening to your members effectively.
What do they like about your loyalty program? What are their pain points? How can you tweak your program to address members’ concerns?
Here are three ways to leverage member data to optimize your loyalty program.
1. Use Member Segmentation to Improve Your Loyalty Program Performance
There are various ways members can be segmented using program data to improve program performance.
Action Completion: Segment members who have yet to complete a brand–valued action and target them with a reminder and/or bonus offer to complete a specific program action.
For example, if you’d like members to complete a monthly poll, you may want to think about sending them a reminder through push notification and reward them with additional points to complete the desired action.
Member Status: Whether a program has tiers or not, segmenting by member types such as inactive, recently lapsed, high earning, high purchasers, and more can help to better target communications to reach members with the right message at the right time.
For lapsed users, typically there is a three-part sequence to reactivate.
Your first email communication is a reminder to come back and let them know that you’ve missed them. Your second email gets a bit more aggressive by offering up a bonus code to drive re-activation. And your third email warns of point expiration if they don’t engage with the program (if the program has a point expiration strategy in place).
For high purchasers/VIPs, you may want to send a surprise and delight communication to thank them for their loyalty and give them an unexpected perk – digital content, low-value reward, entry into an exclusive sweepstakes, etc.
For highly engaged members, you may want to encourage referrals by having a contest offering an incentive for the member that drives the newest enrollments over a given period.
Point Balance: Drive point burn and member engagement through targeted communications to members based on current point balances and highlight rewards within reach to drive incremental purchase/engagement and redemptions.
This can be as simple as a reminder that they have almost enough points to reach a reward threshold or get a free product.
All these segments can be analysed and optimized to drive additional engagement in your loyalty program.
2. Leverage Media Optimization to Enhance Your Loyalty Program
Is media attracting the right members into the program based on demographics?
If not, pull a targeted list of your highest performing customers within the target audience to create a look–a–like model to drive more of the target audience likely to convert into the program.
Media includes any awareness drivers you use to promote your loyalty program.
Are your members completing actions as expected based on initial program projections?
Are action completions by members meeting benchmarks? If specific actions are underperforming, point values can be updated to increase action completion. Targeted communications can also be used to drive action completion.
Let’s say your brand expects 25% of program members to complete a preference survey gaining valuable data for the brand, but you’re only seeing 20% of members completing the survey.
When actions are underperforming, you can either shift the point economy to offer more points for that action to increase the value to members or send out a targeted communication to members that didn’t complete the survey to help drive that conversion.
3. Optimize Your Loyalty Program Rewards
From the perspective of a consumer, the most important part of your loyalty program (and why they signed up) is for valuable rewards. But what if your members don’t find them as valuable as you thought they would?
Are loyalty program members redeeming rewards at your projected rates?
What reward types are underperforming vs. overperforming? While catalog rewards shouldn’t be changed out too frequently, the catalog should evolve to lean into consumer interests and preferences.
Reward catalogs can offer retailer gift cards, cash rewards (Visa, Mastercard, Venmo, etc.), branded gear, and more.
By analyzing redemption data for different reward types and different values, you can better understand member reward preferences and phase out underperforming rewards (low redemptions) and add incremental rewards in high-performing reward categories (high redemptions).
For example, you may see that electronics are performing very well, but that clothing items aren’t being redeemed at a high volume. Over time, you can phase out the clothing items when inventory is depleted and add incremental electronic items.
Another opportunity to better understand member preferences is to create a third–party data append using all members or specific valuable member segments.
These appends not only provide 360–degree views of members’ psychographics and demographics but can also be used to create look-a-like models for future targeted media spend.
You can take email lists from loyalty programs and do a third-party data append to create rich profile views of members. The email list can include all program members, or a targeted high-performing group.
The append provides aggregate level data on members’ age, marital status, education, kids, household information, car preferences, political affiliation, charitable interests, hobbies, purchase interests, music preferences, travel preferences, and more.
This data can be used to help inform your future program themes and prizing, but it can also be used to develop a media model. The model is a look-a-like (LOL) model developed using a segment of the brand’s choice from their program – this could be all members, those most engaged, or those that have made a purchase.
Once the LOL model is created to specifically target consumers most likely to participate in your brand’s loyalty program, you can send the model to the brand’s preferred media channels for their media agencies to leverage in future buys.
Optimize Your Member Data to Refine Your Loyalty Program
It’s clear that a “set it and forget it” approach to your loyalty program won’t produce positive results in the long run.
The key to future member growth, engagement, and revenue will be offering a more complete loyalty program that covers all a brand’s customers – traditional points programs, premium tiers for top customers, and all forms of engagement programs in between.
Optimization can’t occur without acquiring actionable customer data and understanding it. Getting the data is the first major step to program optimization. Find out what your members like, what they don’t like, and what doesn’t make sense to them.
You can drive impactful results from even the slightest of changes to your loyalty program. Adapting to the needs of your customers makes it easier to keep track of your program goals and creates sustainable trust among your members.
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ebbo helps brands achieve their customer loyalty goals with full-service, end-to-end solutions and also creates original educational content straight from the experts to help loyalty marketers stay on the cutting edge of customer engagement.