GA4 audit
Property settings, data streams, events, key events, internal traffic, data retention and consent, checked against what your backend records.
Analytics · Google Analytics 4
Goodish is a GA4 consultancy for marketing and product teams that have Google Analytics 4 installed but don't trust it. We audit the property, fix or rebuild the setup through Google Tag Manager, design the event architecture and e-commerce tracking, connect the BigQuery export, build the reports your team actually opens, and train the people who use them.

Usually the same few things: events that fire twice or not at all, payment providers and subdomains showing up as referral traffic, key events that count newsletter signups as conversions, and e-commerce values that never match the shop. None of these show up as errors in GA4; they show up as decisions made on wrong numbers.
We find them in an audit, fix them in the tag setup (most often through Google Tag Manager), and check the corrected numbers against your backend before calling the job done.
Around the questions the business asks, not around everything that can be clicked. A good event plan names a small set of actions that matter, such as a sign-up, a demo request, a trial activation or a purchase, gives each the parameters needed to segment it, and marks only the ones that create value as key events.
That plan is written down before anything is built. It becomes the shared language between marketing, product and developers, and it is what the ad platforms end up learning from.
When the questions move inside the product. GA4 tells you what happened on the website and where visitors came from; product analytics in Mixpanel or PostHog follows what people do after they sign up. Our analytics service connects the two, and the BigQuery export joins GA4 data with the CRM when reports need both.
For TMT Finance, $4,200 of ad spend had produced two conversions. We integrated product analytics, mapped the application journey and fixed the friction it revealed before relaunching Google Ads; cost per lead fell from $2,140 to $48.74, and the setup now tracks 90+ data points across GTM and GA4.
Property settings, data streams, events, key events, internal traffic, data retention and consent, checked against what your backend records.
A new property set up properly, or a migrated one repaired: duplicate events, self-referrals, missing cross-domain tracking, broken attribution.
A written plan of events, parameters and custom dimensions, with key events defined by what matters to the business, implemented through Google Tag Manager.
Google's recommended e-commerce events from product view to purchase, with transaction IDs and values that reconcile with the shop.
Funnel and path explorations, audiences for advertising, and Looker Studio dashboards per team.
Raw event data in BigQuery for questions the GA4 interface cannot answer, longer history and joins with CRM or product data.
Sessions for the people who use the reports, and documentation of every event and what it means.
Real clients, real numbers, straight from our client reports.
TMT Finance Financial media & funding, United Kingdom · 2023 → today
−97%
cost per lead
Product analytics and UX forensics first, an onboarding flow redesigned on that data, and only then Google Ads relaunched with smart bidding fed by the new conversion data.
Onboarding software for financial advisors · 2020
Research and design guidelines, a fast WordPress site the team publishes to themselves, and tracking that joins the website (Google Tag Manager and Google Analytics) to in-app analytics in Mixpanel.
Working with Goodish was great. They fixed a goal tracking / data integrity issue that had several other experts stumped. I wouldn’t hesitate to work with them again in the future.
We open GA4, Google Tag Manager and the ad accounts, compare the numbers with your backend, and write down where they break and why.
The event plan implemented and tested, key events and e-commerce tracking corrected, and BigQuery connected where it earns its place.
Explorations and Looker Studio dashboards per team, a training session, and a written record of everything tracked.
Scoped per setup: a single tag and a full monitoring system are very different jobs, so we quote after the free audit.
FAQ
Makes Google Analytics 4 answer the questions the business actually asks. That means auditing what is collected, fixing the implementation, designing events and key events, setting up e-commerce and BigQuery where needed, and training the team to read the reports.
Because each system counts differently: different attribution models and windows, consent choices, ad blockers, and often duplicated or missing events in the setup itself. An audit separates the expected differences from the errors, and we write down the reason for each one that remains.
Yes. We start with an audit of what is there, keep what is correct, fix what is not, and document every change so that historical data stays comparable wherever possible.
No, but we recommend it. Implementing GA4 through Google Tag Manager keeps events, triggers and other platforms' tags in one place, with preview testing and version history.
GA4 can send its raw event data to BigQuery, Google's data warehouse. It is worth it when you need history beyond GA4's retention, joins with CRM or product data, or analysis the GA4 interface cannot do. BigQuery is billed by Google separately, so we size it before switching it on.
The first audit is free. Fixes, full implementations and monitoring systems are quoted on scope after it, once we know what is broken.
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