01
Signals from two sources
Orders say what sold. GA4 says how people moved. Each signal names its source.
CRO signals from orders and GA4
Spot where products, landing pages and checkout lose people, using orders from the store and sessions from GA4. Keep the hypotheses and experiments in one list.
Floating cards and figures are examples on sample data, not a customer account.
1The proof
Every number comes with its receipt.
Sample data, fictional brand. This is how CRO shows a figure: the value, where it came from, the formula behind it and when it was last updated.
Checkout step 2Drop-off above usualSource and formulaGA4Updatedlast 14 days
Product page AAdd to cart below store averageSource and formulaShopify and GA4Updatedsee source
HypothesisShow delivery date earlierSource and formulaNot tested yetUpdatedsee source
Rule: every number shows its source, formula and update time. A missing source reads "not measured", never 0.
2Part of Measure
CRO: what it does.
One of four areas of the product, sharing the same client record, roles and log.
02
Hypotheses, not verdicts
A drop at checkout becomes a hypothesis to test. The tool never claims a cause automatically.
03
Experiment list
Track what you tried, when, and what changed afterwards, next to the change log.
Works with
3 platforms, read-only first
Connections start read-only. Writing is switched on per account, only after you grant the rights.
At a glance
Stated up front
- things it does
- 3
- steps start to finish
- 4
- platform connections
- 3
- limits stated
- 2
3The data path
How the data moves. Source to screen.
Lines draw as you scroll. Platforms on the left are read-only first, CRO sits on the one client record, and each output keeps its receipt.
ShopifyBuiltWooCommercePlannedGoogle Analytics 4BuiltROASfinityCRO
Signals from two sources
Hypotheses, not verdicts
Experiment list
Sources are read first, the numbers are stored once per client, and every output shows its source, formula and update time.
How the work moves in Measure
The same four moves apply to every module in this area.
- 1 ReadConnected sourcesOrders, spend and results come from the store and ad platforms, read-only first.
- 2 ComputeFixed formulasMER, CAC and the rest are defined once, in the open, the same for every client.
- 3 ShowSource on every numberEach figure carries its source, formula and the time it was updated.
- 4 FlagNot measured, never zeroWhen data is missing the screen says so, instead of showing a made-up value.
4The routine
How it works, step by step.
From first connection to the number a client sees.
- 1
Read orders and sessions
Store and GA4 data for the same period and timezone.
Step 1Read orders and sessionsexample - 2
Find the leaks
Compare products, pages and funnel steps against history.
Step 2Find the leaksexample - 3
Write a hypothesis
Name the change, the page and the metric to watch.
Step 3Write a hypothesisexample - 4
Follow up
Review the result with a comparison period and season in mind.
Step 4Follow upexample
5In use
Built for businesses like these. Example scenes.
Photos are stock images that show the kind of business this is built for. They are examples, not customers.
Stock photos and example labels, not customers.
6In practice
Common mistakes, and a short checklist.
General practice for this kind of work, not a claim about any one tool.
Ending a test when it first looks good
Early leads often reverse as more visitors arrive. Set the sample size and the end date before the test starts, and keep to them.
Changing several things at once
When a page changes in five places, no single change can be credited. Test one clear idea per variant, or accept that the result is a package and say so.
Optimizing a step and ignoring the path
A higher add-to-cart rate means little if checkout completion falls. Track the whole path from the landing page to the paid order.
A short checklist
Your ticks stay in this browser only.
7Honest limits
What it will not claim, and what it works with.
What it will not claim
- GA4 reports have quotas, sampling and thresholds, and results can differ from the store.
- No automatic claim of causality. A change followed by an improvement is an observation.
Works with
Connections are read-only first and go live only after the platform access is approved.
Built: the connector exists in the product and goes live per account once access is granted. Planned: not built yet.
Used instead of
No single tool replaces this module; it connects work that is usually split across several.
8Related modules
Same room, next door.
Modules that share this client record, these roles and this log.
MeasureReportsClient, channel, campaign and product reports where every figure shows its source, formula and update time.Read more→MeasureSignalsAlerts for inactive accounts, rejected ads, CPM and CPA jumps, weak spend, broken URLs and stale connectors.Read more→MeasureAI insightsChecks for drops, anomalies, frequency and missing new creatives, explained with numbers you can verify.Read more→
9Guides
Learn more. Short guides.
Short guides on the numbers and routines behind this module.
GuideHow to calculate break-even ROAS for an ecommerce clientBreak-even ROAS is the line between an ad that loses money and one that pays for itself. It takes three inputs and one division.6 min read→GuideMER vs ROAS: which number an agency should reportPlatform ROAS tells you how an ad platform scores itself. MER tells you how the business did. A client review needs both, clearly labelled.6 min read→
10FAQ
Questions about cro.
Does it run A/B tests?
It tracks hypotheses and experiments and reads their outcome from store and GA4 data. It does not replace a dedicated testing tool.
Why can GA4 and the store disagree?
They measure differently. The store is the source for real orders and GA4 is a separate view of behaviour, and both are shown with their source.
Can I work without GA4?
Yes. Store signals work on their own, and missing GA4 data is shown as not measured.
Run the next client review from one screen.
We open one agency at a time, with your own accounts connected read-only first.