How we measure retention
Retention results are meaningful only when the metric, baseline, cohort, time window and limitations are clear. Loiale evaluates repeat behaviour, cohort LTV, contribution margin and incremental impact in context; attribution alone is not proof of causality.
Most retention reporting measures the channel, not the customer. We measure the customer: what a cohort does over time, and what changed after we changed something.
The primary frame: cohorts, not campaigns
A cohort is every customer who made a first purchase in the same period. We track what that group does at 30, 60, 90, 180 and 365 days. Campaign-level revenue is an input, never the headline.
The metrics we hold ourselves to
| Metric | Definition we use | Why it is here |
|---|---|---|
| Repeat purchase rate | Share of a cohort with two or more orders by day N | The cleanest signal that retention work is landing |
| Cohort retention rate | Share of a cohort still purchasing or active at day N | Shows whether customers stay in the relationship |
| Customer LTV | Expected contribution margin per acquired customer over a fixed horizon, discounted when appropriate | The long-term value of the customer, not the channel |
| Revenue per recipient | Revenue per message or contact, but only as a diagnostic, not a target | Keeps efficiency visible without making it the goal |
| Contribution margin | Revenue minus variable costs including COGS, rewards and payment fees | Prevents growth that looks good but destroys margin |
| Time to second order | Median days between first and second order | Moves earlier than LTV does |
| Contribution per lifecycle moment | Revenue attributable to a specific moment, measured against a holdout where one is possible | Keeps the loop honest about which moment did the work |
| Program economics | Cost of rewards and margin impact against incremental behaviour | Loyalty has to pay for itself |
Attribution: what we will and will not say
- Where a holdout is possible, we run one and report against it.
- Where a holdout is not possible, we say so and report the change as directional.
- We do not report platform-attributed revenue as incremental revenue.
- We do not report a lift we cannot reproduce in the client's own data.
Reporting cadence
Weekly: experiment read-outs. Monthly: cohort trajectory and business review. Quarterly: a meta-review of which categories of change actually moved the curve.
Benchmarks
We do not publish retention benchmarks we have not collected under a disclosed method.
SOURCE REQUIRED · Any benchmark figures on this page require a documented dataset and methodology before publication. See the benchmarks methodology page.
Request a measurement review
We build and run lifecycle, loyalty and customer-data systems inside your existing stack. Tool-agnostic. Outcome-owned.
Request a call