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How this guide was prepared. Last updated October 2026. It draws on Brandmovers' experience running loyalty programs and offers, including the distributor program cited below, described as its case page reports it. The rule on "free" offers was checked against the FTC's guide. Examples are illustrations, not benchmarks. This is general information, not legal advice. |
A loyalty offer test compares how members respond to different versions of an offer, and to no offer at all, by randomly assigning eligible members to each group. The no-offer holdout shows whether an offer changed behavior or only rewarded purchases members would have made anyway.
Bonus points, discounts and other offers are among the most used tools in a loyalty program, and among the most expensive. An offer that looks successful because many members redeemed it may have cost margin on purchases that would have happened without it. Testing offers properly answers a narrower and more useful question: which offer changes what members do, by how much, and at what cost. This guide covers why to test, what to test, how to design a valid test, what to measure, how to read results and roll out, and the rules that apply to the offers themselves.
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Offers cost margin, and an untested offer can reward purchases members would have made anyway; testing shows which offers change behavior at a cost the program can sustain.
Without a test, the usual evidence is the redemption count: how many members used the offer. That number cannot separate members who bought because of the offer from members who would have bought regardless. This matters most for lapsing members, some of whom return on their own, so a rise after an offer can look like the offer's effect when nothing is there to compare it against. Frequent offers, tested or not, can also teach members to wait for a deal; a long-running holdout and the full-price purchasing measure below can show whether that is happening. A testing habit turns each offer into evidence for the next one.
Test one variable at a time, such as urgency, frequency, value and type, spend threshold, cross-category incentive, targeting or channel, against a holdout.
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Variable |
Example A vs B |
What it answers |
Main metric |
Watch out for |
|---|---|---|---|---|
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Urgency |
24-hour vs 72-hour redemption window |
Whether a shorter window lifts response |
Incremental purchases during and after the window |
Pulling purchases forward; overuse |
|
Frequency |
Monthly vs quarterly offers |
How often members can receive offers before response falls |
Incremental purchases per member over the period |
Fatigue and unsubscribes |
|
Value and type |
20% off vs $20 cashback; bonus points vs discount |
Which form motivates at the lowest cost |
Incremental margin per member |
Set both versions at a similar cost per member, or the test compares value as well as form; compare net of cost |
|
Spend threshold |
Bonus for spending $50 vs $75 |
Where a threshold moves basket size |
Basket size against the holdout |
Members already above the threshold |
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Cross-category |
Bonus points on a related category |
Whether members try a new category |
New-category purchase rate |
Shifting spend from one category to another |
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Targeting |
Offer to lapsing members vs all members |
Who needs the offer at all |
Incremental response by segment |
Paying members who were already active |
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Channel and message |
Email vs app; different framing |
How best to deliver the offer |
Response by channel |
Members differ by channel |
The guides to redemption rates, average order value and personalized offers for churn cover the goals these tests usually serve.
Write a hypothesis, randomly assign eligible members, include a no-offer holdout, change one variable, run the test across a buying cycle and decide the success measure before launch.
Smaller programs. If the member base cannot fill several groups, test fewer versions at once, usually one offer against a holdout, make the difference between versions larger or run the test longer. A result from groups too small to separate signal from noise is a direction, not a decision.
B2B programs. In a channel program, assign whole accounts rather than individual buyers, since several people at one distributor or dealer may buy through the same account. Account counts are often small and buying cycles long, so the guidance for smaller programs usually applies.
BLOYL™, Brandmovers' enterprise loyalty platform, supports A/B testing against a control group, and its rules engine sets earning and redemption rules by customer segment, purchase channel, time window or behavioral action, so tests and holdouts can be set up inside the program.
Case study (disclosed by Brandmovers). A leading Canadian regional distributor's B2B loyalty program, run on BENGAGED™, Brandmovers' B2B loyalty platform, shows why random assignment matters. "Sales among enrolled customers grew by an average of 25%, while non-enrolled customers saw only a 5% average increase" (distributor case study). Customers were not randomly assigned to enroll, so the gap reflects both the program and differences between the customers who joined and those who did not. Random assignment avoids that problem in an offer test, because members who get the offer and members who do not are chosen by chance rather than by choice.
Measure incremental purchases, spend and margin against the holdout, net of the offer's cost, and check what happens after the offer ends; redemptions only show use.
Illustrative example. A program tests a 72-hour bonus against a 24-hour bonus for lapsing members, with a no-offer holdout. The 24-hour group redeems more often, but over the following eight weeks its purchases fall back to the holdout's level, while the 72-hour group stays ahead of the holdout by more than normal variation. On redemptions alone the 24-hour offer wins; on incremental margin net of each offer's cost, including after the offer ends, the 72-hour offer does. This is an illustration, not a benchmark.
Act on a result only when the difference exceeds normal variation, holds after the offer ends and pays after its cost; then roll out with a holdout in place.
The guide to A/B testing a loyalty program covers testing at the program level, such as pilots before launch.
State each offer's terms, conditions and expiry clearly, follow the FTC's guide for offers described as "free," and keep every test group's terms clear and consistent.
"Free" offers. The FTC's guide says the conditions of a "free" offer "should be set forth clearly and conspicuously at the outset of the offer," and that a "free" offer is understood to be "based upon a regular price for the merchandise or service which must be purchased" (16 CFR 251.1). A bonus item should not be paid for by raising the price of the item that must be bought. The guide also says a single size of a product "should not be advertised with a 'Free' offer in a trade area for more than 6 months in any 12-month period," which matters when testing how often to run "free" offers.
Terms and expiry. Each offer should state what members must do, what they receive and when it ends, and honor those terms for every member who qualifies.
Fairness between groups. Members in different test groups may compare offers. Keep differences within what the program terms allow, and avoid tests that would leave one group worse off than the program's published benefits. Holdout members should still receive every standard program benefit; they miss only the offer being tested.
Competing B2B buyers. Testing different offers on resellers that compete with each other needs care. The FTC explains that a seller "charging competing buyers different prices for the same 'commodity' or discriminating in the provision of 'allowances'" may be violating the Robinson-Patman Act, which requires a seller to "treat all competing customers in a proportionately equal manner" (FTC).
This is general information, not legal advice.
Testing loyalty offers is worth the effort when the test answers the right question: did the offer change what members did, and did it pay? Compare offers against a no-offer holdout, assign members at random, change one variable at a time, measure incremental margin net of cost and what happens after the offer ends, and roll out winners with a holdout still in place.
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Want to test which loyalty offers actually change behavior? Brandmovers runs loyalty programs on BLOYL, with A/B testing against a control group and a rules engine that sets earning and redemption rules by customer segment, purchase channel, time window or behavioral action. Request a demo to talk through your offer testing with the Brandmovers team. |