How to validate a loyalty mechanic before you build it

Most loyalty programmes don't fail because of technical problems. They fail because the underlying mechanics were never tested. You build a points system, launch it, and discover three months later that nobody knows why they're earning points or what they're supposed to do with them.

At Livewall, we see this pattern often. Brands invest time and budget in the technology before they've answered the fundamental questions: what behaviour do you want to reward? Is the reward compelling enough to actually change that behaviour? Do people understand it quickly enough to participate?

Validating your loyalty program design doesn't have to take months. You can surface the most critical risks in a few weeks, before writing a single line of code.

Step 1: Define the target behaviour precisely

Vague objectives are the first failure mode. 'Increase customer engagement' is not a behavioural objective. 'Move customers who purchase once per quarter to purchasing twice per quarter' is.

Be specific about:

• Which behaviour do you want to see more of?
• How often do your best customers already do this?
• What is the commercial value of that behaviour change?

If you can't answer these questions, you don't need a programme yet. You need data research first. Look at your CRM and find the customers who already exhibit the most valuable behaviour. That's your reference group and your design benchmark.

Step 2: Test the reward value

A point is not a reward. Points are a promise of a reward. The question is whether that promise is strong enough to change behaviour.

Most teams misjudge the motivational strength of their rewards. They think like accountants: a 5% discount is a 5% discount. But customers don't think that way. A 5% discount on every purchase carries less psychological pull than a visible progress bar working toward a free product.

A practical validation method: run a simple A/B test in your email marketing before building the programme. Send half your customers an offer with a direct discount. Send the other half an offer with points accumulating toward the same reward. Measure click-through and conversion. The result will tell you more about the motivational power of your reward structure than any workshop.

When we worked with Decathlon on their loyalty campaign, testing different mechanics against their member base before finalising the structure gave us direct signals about which rewards actually activated behaviour change.

Step 3: Measure comprehension, not just intent

A mechanic is only valid if people understand it. This sounds obvious, but it's almost always skipped.

The standard user test measures intent: 'Would you participate in this?' That's a useless question. People say yes to things they never do. What you want to measure is comprehension: 'Explain to me what you just saw. How do you earn points? What can you do with them?'

If five out of ten test participants can't explain the mechanic correctly after a first exposure to your concept, your programme is too complex. Simplify first, then re-validate.

You don't need code for this. A paper prototype or a Figma mockup is enough. Five to eight interviews with people from your target audience are sufficient to surface the most significant comprehension failures before you've spent a euro on development.

Step 4: Simulate the economics

Before building anything, run the unit economics. This is where most programmes break down, not at launch but six months later when margin pressure becomes visible.

The core calculation is straightforward. Ask yourself three questions:

What does it cost to produce one behaviour change? If a customer gets a free product after every ten purchases, calculate exactly what that costs you and what incremental revenue that tenth purchase needs to justify.

What is the liability rate for your highest-value customers? Your most loyal customers accumulate points fastest. They also cost you the most. Make sure the programme is economically sound specifically for this group.

What is the break-even point? How much behaviour change do you need for the programme to become profitable? If that number is unrealistically high, redesign the programme before you build it.

For Proximus+ World, the economic model was embedded in the design phase of the programme. That distinction, building the economics into the mechanics rather than bolting them on afterwards, was what made the programme structurally viable.

Step 5: Test the return loop

A loyalty programme that activates people once is not a loyalty programme. It's a promotion. The difference is in return frequency.

Before you build, ask yourself: how often does the programme give people a reason to come back, even when they're not buying? If the answer is 'only after a purchase', you have a rewards programme but not a loyalty programme.

Test return mechanics separately. A simple email sequence or temporary microsite is enough. Measure what percentage of participants return actively after five, fourteen, and thirty days. If the retention curve drops off sharply after week one, solve that problem before building further.

This is exactly what we do as standard in gamified loyalty projects at Livewall. The return loop is the hardest part to get right, and also the most important. A well-designed return mechanic is the difference between a programme that compounds over time and one that needs constant campaign support to stay alive.

The validation checklist

Before you build a loyalty mechanic, you should be able to answer all of the following.

1. Which specific behaviour do you want to change, and how will you measure it?
2. Is the reward value strong enough to motivate that behaviour, demonstrated through an actual test?
3. Do people understand the mechanic after a single exposure?
4. Are the unit economics sustainable for both low-activity and high-activity participants?
5. How often does the programme give people a reason to return without making a purchase?

If you have a concrete answer to each point, you're building from evidence rather than assumption. If you don't, you have more validation work to do.

At Livewall, we help brands answer these questions before the build starts. It sometimes costs a few extra weeks upfront. It always saves more time and money later.