Audit this store's retention and report what the data says. Diagnose only — do not design a loyalty program, and do not recommend one unless the evidence points there. MEASURE 1. Purchasers = customers with at least one order. Repeat = customers with two or more. second-purchase rate = repeat / purchasers. 2. Report the total customer-record count NEXT TO the purchaser count. Most stores hold far more records than buyers (email captures, account signups). Dividing by total records understates the rate several-fold and aims the whole strategy at the wrong problem. 3. Use the order's PROCESSED date for every window, sort and interval. The created date is when the row was written; on any migrated or imported store the two diverge and a year of trading collapses into however long the import took, silently. 4. Sanity-check before reporting: a stricter percentile must have a HIGHER threshold, so the top-4% spend figure cannot be below the top-15% figure. If it is, the query is wrong. Report reorder gaps in DAYS, not weeks — a flow fires on a day. 5. Also collect: orders per purchaser; time to second order as p25 / median / p75; AOV split into first orders vs repeat orders; share of revenue from repeat orders; trailing-12-month spend per purchaser at the top 15% and top 4%; share of orders carrying a discount, split first vs repeat; top products and whether bundles carry more basket than single items. THREE CHECKS THAT CONSTRAIN WHAT YOU MAY RECOMMEND - Email/SMS consent among PURCHASERS — divide by purchasers, not by total records. The denominator rule applies to every rate in the report, not only the repeat rate. If most purchasers are not subscribed, the first job is consent capture and any flow you propose reaches almost nobody. - Whether a loyalty or subscription app is already installed and what it is actually doing — how many members, what has actually been issued, whether rules are switched on. Proposing a program the merchant already runs destroys credibility. - Whether any selling plan exists. On a catalog with a monthly consumption cycle, the absence of a subscription mechanism is itself a headline finding, not a footnote. TWO TESTS BEFORE YOU CONCLUDE Cadence vs basket. A tight repeat gap says "subscription". But check how often a second order contains a product from the first. Tight cadence with low same-product repeat means customers keep a rhythm while rotating items — that is a FLEXIBLE subscription, not subscribe-and-save on a hero SKU. Reporting only the cadence leads to the opposite build. Artifact vs behaviour. If most records never purchased, the naive reading is an activation problem. Test it before saying it: compare the spread of customer creation dates against the spread of order dates — a real store accumulates both together. Check whether non-purchasers differ systematically from buyers (all created the same week, or better email consent than buyers). If they do, they are an import artifact and must be excluded from every rate, not called a dormant audience. VERDICT Name the ONE constraint that binds, and say which of these the evidence supports: - First-order conversion or traffic — acquisition, not retention - Basket too small to fund anything — AOV, bundles, thresholds - Product repeats but buyers stop after order one — lifecycle timing, aimed at the window just BEFORE the median gap - Predictable replenishment — subscription - Organic repeat and margin already exist — then, and only then, loyalty - Nothing yet — say so Loyalty is not the default answer. If repeat behaviour is already healthy without a program, say that plainly and name what would actually move the number. STOP IF THE DATA CANNOT ANSWER If no customer has a second order, then repeat rate, time-to-second, repeat AOV and any at-risk or lapsed segment are structurally unfillable. Report what you did measure, say the dataset cannot support a verdict and what is missing, and stop. A long report whose headline metric is 0% reads as authoritative while saying nothing. OUTPUT - Verdict: the binding constraint, in one sentence - Evidence table: metric, value, window, and where it came from - Three to five findings, each a sentence a merchant could act on - Segments with real counts: one-time within the reorder window, one-time past it, active repeaters, at-risk, lapsed, subscription-shaped (three or more orders at a stable gap) - What you could not measure, and what would change the answer Never invent margin, ad spend, CAC, reorder cadence or industry benchmarks. Ask for margin and ad spend if the recommendation needs sizing; if unavailable, label the recommendation unsized rather than guessing. Keep measured figures separate from anything modelled. Close by naming the next step the verdict implies — the flow to build, the subscription to offer, the program setting to fix — so the merchant knows what to do, not just what is true.