When you run a loyalty pilot, the toughest part isn’t building the program — it’s convincing stakeholders it’s working. I’ve been on both sides of that conversation: pitching pilots to sceptical founders, and later asking for proof when I was responsible for marketing budgets. Over the years I’ve narrowed what really moves the needle down to eight metrics you can present clearly, with calculations, context and realistic benchmarks.
Why a short, focused checklist wins
Stakeholders don’t want a spreadsheet full of vanity metrics. They want a concise set of indicators that tie the pilot to revenue, behaviour change and repeatability. A tight checklist lets you tell a story: we launched a targeted pilot, we saw measurable behaviour shifts, and here’s the expected financial outcome if we scale. Below are the eight metrics I always include and how to measure them so decision-makers can say “yes” (or at least “let’s iterate”).
The eight metrics to prove your loyalty pilot
- Activation rate — Are customers joining and using the program?
- Engaged member repeat purchase rate — Are members buying more often than non-members?
- Incremental revenue (per member) — What extra revenue is the program driving?
- Retention / churn improvement — Is the pilot keeping customers longer?
- Average order value (AOV) uplift — Are members spending more per transaction?
- Redemption rate and cost-to-redeem — Are rewards being used, and at what cost?
- Net Promoter Score (NPS) or CSAT delta — Is satisfaction improving?
- Payback period and ROI — How long until the pilot pays for itself?
How I define and calculate each metric
| Metric | What it shows | Simple formula | Typical SME benchmark |
|---|---|---|---|
| Activation rate | Ease + attractiveness of joining | Members signed up / eligible customers reached | 10–30% in 3 months (varies by channel) |
| Engaged repeat purchase rate | Behavioural change among members | Members with >=2 purchases in period / total members | 20–40% in 6 months |
| Incremental revenue per member | Direct financial gain attributable to the program | (Revenue from members - baseline revenue from comparable cohort) / number of members | £10–£50 per member first year (sector-dependent) |
| Retention / churn improvement | Longer customer lifetime | Retention rate (pilot) - retention rate (control) | +5–15 percentage points |
| AOV uplift | Higher spend per order | (AOV members - AOV non-members) / AOV non-members | +3–12% |
| Redemption rate & cost-to-redeem | Reward economics and perceived value | Redemptions / issued rewards; cost = average reward value + fulfilment | Redemption 15–40% (depends on reward) |
| NPS / CSAT delta | Brand sentiment shift | NPS (members) - NPS (non-members) | +3–10 points |
| Payback period & ROI | Financial viability of scaling | Incremental gross margin / cost of running program | Payback within 6–18 months |
Measurement tips I use on every pilot
- Use a control group. If you can’t run a randomized test, match on recency, frequency and monetary value (RFM) to create a comparable cohort. Without a control you’re guessing at incrementality.
- Set tracking and tags before launch. Implement membership flags, order source tags and campaign UTM parameters so every transaction maps back to member status and marketing touchpoints.
- Decide your reporting window up front. Loyalty effects take time. For most SMEs a 3–6 month window is useful for engagement and AOV; use 12 months for retention and CLV modelling where possible.
- Pre-register primary and secondary metrics. Declare the single metric you’ll use to recommend scaling (I usually pick incremental revenue per member or payback period).
- Watch sample size and significance. Report confidence intervals or p-values for changes. Small sample sizes can be misleading; flag them clearly.
How to present these metrics to stakeholders
Make your stakeholder report a one-pager followed by a short appendix. I structure mine like this:
- Headline: single sentence conclusion (“Pilot delivered £X incremental revenue and 8pp retention uplift; recommended to scale to 50k customers”).
- Key metric table: the eight metrics, current value, control value and delta (colour-coded simple green/amber/red).
- Financial summary: incremental revenue, program cost, and projected payback at 3 scale scenarios (conservative / realistic / aggressive).
- Risks & mitigations: e.g. supply constraints on rewards, potential cannibalisation, data quality issues.
- Recommended next step: scale, iterate or stop — with clear A/B tests or experiment changes for the next phase.
Common questions I get and short answers
- Q: What if redemption costs are high? A: Break down cost-to-redeem and test lower-cost but high-perceived-value rewards (exclusive access, early product drops, partner offers).
- Q: How long before we can trust retention data? A: Use early leading indicators (engagement, repeat purchase rate) for initial decisions; reserve full retention conclusions for 12 months.
- Q: What if AOV increases but visits drop? A: Segment by frequency vs value. If fewer visits but higher AOV still yields higher margin per customer, that can be acceptable — but understand long-term churn risk.
Practical benchmarks to aim for in an SME pilot
Benchmarks depend on sector, price point and acquisition channel. When I advise SMEs I recommend setting realistic thresholds before you start. As a rule of thumb for a three-to-six month pilot:
- Activation: 10–30% of targeted customers
- Repeat purchase rate among members: 20–40%
- AOV uplift: 3–12%
- Redemption rate: 15–40% (keep an eye on cost-to-redeem)
- Payback: under 18 months for most consumer retail pilots
Those numbers are not targets in isolation — they should map to an acceptable ROI when you combine incremental revenue, margin and program cost. In many pilots I’ve run, the decision to scale came down to whether the payback period fit the business’s cash and growth objectives.
If you want, I can draft the one-page stakeholder report template I use, with the eight-metric table pre-filled and the financial projection grid. I often share that with founders to accelerate decisions and avoid wasted pilots that never get judged properly.
