Most stores track either three numbers or three hundred. Three misses the leaks. Three hundred is a dashboard nobody opens, the exact disease the automated reporting piece diagnoses. The right set of ecommerce KPIs is twelve numbers, split by the cadence at which they can actually change, which covers a small ecommerce business properly.
This sits under the GA4 pillar and supplies the metrics the budget piece governs with.
These move fast and have same-week fixes.
| KPI | Definition | Watching for |
|---|---|---|
| Revenue vs plan | Platform revenue against your own monthly target, paced | Drift early enough to act |
| Sessions by channel | Traffic split from analytics | A channel quietly dying |
| Conversion rate by device | Orders over sessions, mobile and desktop separately | A broken checkout or theme regression |
| Blended ad spend pacing | Total spend across platforms vs budget | Runaway campaigns |
These reveal whether the machine is working, not just spinning.
| KPI | Definition | Watching for |
|---|---|---|
| MER | Total revenue over total ad spend | The governing efficiency number, per the budget piece |
| Contribution margin after ad spend | Revenue minus product, shipping, fees and ads | Whether growth is profitable or performative |
| New vs returning revenue split | From platform customer reports | Over-dependence on either acquisition or the base |
| Email and SMS revenue share | Attributed owned-channel revenue over total | The retention engine's pulse |
Contribution margin after ad spend is the one most stores skip and the one that settles every argument. Revenue can grow while this number shrinks, and that pattern is the "rented growth" the ecommerce growth piece warns about.
Slow numbers. Checking them weekly is noise; ignoring them for a year is how strategy drifts.
| KPI | Definition | Watching for |
|---|---|---|
| Repeat purchase rate | Share of customers with 2+ orders in the window | The retention trend underneath everything |
| Lifetime value by cohort | Per the lifetime value piece, cohorted by first-purchase month | Whether newer customers are worth what older ones were |
| Customer acquisition cost, fully loaded | All acquisition spend over new customers | The CAC-to-LTV relationship that sets the spend ceiling |
| Average order value trend | Revenue over orders, trended | Mix shifts, discounting creep |
A worked operating pattern: tier 1 lands in a Monday morning summary, automated, three minutes to read. Tier 2 is a one-page monthly review with last month and the trailing six months side by side. Tier 3 is a quarterly session where the numbers get discussed, not just read. The format matters less than the contract: every number has a cadence, an owner and a threshold that triggers a conversation. A metric without a threshold is scenery.
Two definition rules that prevent most dashboard arguments: revenue always means the same thing (pick gross or net of refunds and never switch silently), and every ratio's numerator and denominator come from the same source system.
If forced to five: revenue vs plan, conversion rate by device, MER, contribution margin after ad spend, and repeat purchase rate. The full twelve add early-warning coverage.
ROAS is per-platform and based on each platform's self-attributed conversions. MER is total revenue over total spend from sources platforms can't inflate. ROAS steers campaigns; MER governs the budget.
At the speed each metric can change: operating numbers weekly, health numbers monthly, strategy numbers quarterly. Checking slow numbers fast produces noise, not insight.
Qwrki runs the reporting layer for small ecommerce operators, so the twelve numbers land on the right cadence with an owner and a threshold attached to each one. We wire tier 1 into an automated Monday summary, keep the monthly review to one page, and hold the quarterly numbers where strategy actually changes. Book a call and we'll map your store onto the three-tier stack.
A practical method for setting a paid media budget: work back from contribution margin, size spend for learning, and govern with MER instead of platform ROAS.
The GA4 ecommerce events that actually matter, the setup checklist, and why GA4 never matches Shopify. A practical guide for store owners.
First click, last click, data-driven: every attribution model is wrong differently. A practical measurement stack for small ecommerce that still makes good decisions.
