Ecommerce analytics audit checklist (Free)

Ecommerce analytics audit checklist

The checklist I run through before telling a team which of their numbers to trust. It covers GA4, GTM, server-side tracking, CAPI, consent, attribution, and the places where your platform, ad accounts, and analytics quietly stop agreeing.

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One canonical GA4 property, no orphaned duplicates. Duplicate properties mean every report is partial and nobody knows which one is right. Internal traffic and known bot traffic filtered out. Otherwise your own team's sessions inflate every number. Key events (purchase, lead) defined and marked as conversions correctly. If they're not, your conversion reporting is quietly wrong. Currency and value passed on every transaction, not just some. Missing values understate revenue and break ROAS math. Cross-domain tracking set up if checkout or booking lives on a subdomain. Without it, conversions get attributed to "referral" from your own site. Data retention at maximum and BigQuery export on if you'll ever want raw data. You can't backfill what GA4 already discarded.

Every intended tag fires, and nothing fires twice. Double-firing inflates conversions and wrecks your ROAS math. Triggers scoped correctly — no purchase tag firing on every page. Mis-scoped triggers are the most common source of phantom conversions. No legacy or orphaned tags from old vendors still firing. Dead tags leak data and slow the page. DataLayer pushes happen before the tag reads them. Race conditions silently drop values on a portion of hits. The GTM container is actually published, not just saved in a workspace. Live tools test the published container — an unpublished change does nothing.

Browser and server events deduplicated via a shared event ID. Without it, Meta counts the same purchase twice and CAC looks like a miracle. Server container actually receiving events, not silently dropping them. A misconfigured container fails quietly — no error, just missing data. Meta CAPI match quality (EMQ) healthy, not starved of parameters. Low match quality means you're paying for signal Meta can't use. Google Ads enhanced conversions configured and accepted. Unaccepted conversions don't feed bidding. Consent state passed through to server tags — they don't inherit it. Server tags fire regardless of the browser consent gate unless you replicate it.

Tags genuinely gated on the consent signal, not firing regardless. A consent gate that doesn't gate is both a data problem and a legal one. Consent Mode (or equivalent) wired correctly, denials respected. Misconfigured Consent Mode can drop or model data in ways you didn't intend. No PII leaking into GA4 — emails in URLs, etc. PII in GA4 is a compliance breach and can get the property suspended. Consent state logged so you can prove compliance later. If you can't evidence it, you can't defend it.

Channel grouping reflects how you actually buy media, not GA4 defaults. Default groupings hide paid social inside "social" and misattribute spend. UTM discipline: campaigns tagged consistently across all paid. Inconsistent UTMs scatter one campaign across five rows of reporting. Attribution model understood and matched to how you make decisions. The wrong model rewards the wrong channels. "Direct" not bloated with untagged traffic that's actually paid. Inflated direct hides what your paid spend is really doing.

GA4 purchases reconcile to platform orders within a known margin. If you don't know the gap, you don't know which number to trust. Ad-platform conversions reconcile to GA4 or the backend. When Meta and GA4 disagree, someone's optimizing on a fiction. A single source of truth agreed for the number the board sees. When three systems disagree, decisions get made on whichever number was in the room.

Found more wrong than you expected?

That’s what the audit is for — full checklist run against your stack, fix list in 5 days.

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