A marketing decision is only as reliable as the data behind it. In GA4, that means an explicit measurement plan: which events exist, which ones count as conversions, which parameters travel with each one, and how it all connects to the business's real funnel.
The GA4 event model
GA4 dropped category/action/label and now works with events and parameters. There are automatically collected events, recommended events (with standardized names), and custom events. Whenever a recommended event fits your case, use the official name. It unlocks ready-made reports.
A 4-step measurement plan
- List the business actions that matter, from micro to macro conversion.
- Name each event in snake_case and document its parameters.
- Decide which events count as conversions. Few, and only the ones that generate revenue.
- Validate in DebugView before publishing the container.
| Event | When it fires | Useful parameters |
|---|---|---|
| generate_lead | form submission | form_id, estimated value |
| contact_whatsapp | click on the WhatsApp button | source, page |
| view_item | product view | item_id, price |
| add_to_cart | item added to cart | item_id, quantity |
| begin_checkout | checkout started | value, items |
| purchase | order approved | transaction_id, value, currency |
From event to funnel
With the right events in place, you can build the funnel exploration in GA4 and see exactly how visitors move between stages, the same read described in sales funnel stages and used to calculate the store's conversion rate.
Data quality
- Filter out internal and development traffic.
- Set up a list of unwanted referrals (payment gateways).
- Standardize UTMs across every campaign: lowercase, no accents.
- Use server-side measurement when signal loss is significant.
- Document every change with a date: without that, historical comparisons lie.
From data to decision
A report nobody uses is not measurement, it is decoration. Set up a weekly dashboard with five numbers: qualified sessions, conversion by stage, cost per conversion, revenue, and average ticket. From there, generate hypotheses for the CRO cycle and validate them with A/B testing.
GA4 implementation checklist
- Measurement plan documented and versioned.
- Event names standardized in snake_case.
- Conversions limited to revenue actions.
- The value parameter filled in on business events.
- Internal traffic filtered out.
- UTMs standardized across every campaign.
- DebugView validation before each publish.
Conclusion
A well-implemented GA4 is not an analytics project: it is the foundation for knowing where to invest. Without it, every optimization becomes opinion, and opinion does not scale revenue.
Frequently asked questions about ga4 events and conversions
How do I create a conversion in GA4?
Create or identify the event that matches the business action, then mark it as a key event (conversion) in the data settings. Validate it in DebugView first to make sure it fires correctly.
How many events should I mark as conversions?
Only a few. Limit it to actions that represent revenue or real purchase intent, such as a form submission, a qualified WhatsApp click, checkout initiation, and a completed purchase.
What is the difference between an event and a conversion in GA4?
Every piece of data GA4 collects is an event. A conversion is the event you flag as a business outcome, which changes reporting, attribution, and campaign optimization.
Why don't GA4's numbers match the ad platform's numbers?
Attribution models, conversion windows, and signal loss from consent settings differ across platforms. Use GA4 to read trends and your own transactional data as the source of truth for revenue.
Do I need Google Tag Manager to use GA4?
It is not required, but it helps a lot. GTM centralizes tag firing, versions changes, and lets you test events without touching the site's code for every adjustment.
About the author
Kauára Bertoluci
Partner and Head of Strategy & Growth, KCLOCK
Marketing, tracking, and CRO strategist. Leads positioning, funnels, paid media, and measurement across KCLOCK's projects.
- #analytics
- #data
- #measurement
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