Best Way to Track Funnel Events Success Help Wanted
My website has a multitude of ways in which someone can get to the contact us form. This is a valuable form fill for us and I have a value assigned to it. The next step, to me, is to determine ways in which one gets to the contact form in order to identify the most valuable pages/buttons etc.
I have events set up for any way in which one can get to the contact form. Because there are buttons in the header and footer and my events label is set to the page URL, the combination of differentiation is enormous.
The events flow screen does not really help me much. Is there a better way to determine how many people click the button in my header and then fill out the form versus click the button in the footer and then fill out the form? I can apply that logic to other situations. Thanks!
The short answer is:
The most robust and technical solution involves implementing server-side tracking via Google Tag Manager (GTM) running on a platform like Stape or a Google Cloud Platform (GCP) App Engine to first collect granular event data, differentiating the header and footer button clicks with distinct event parameters, and then utilizing the Google Analytics Measurement Protocol to send this clean, server-validated data to Google Analytics 4 (GA4).
To perform the deep funnel analysis you require, you should integrate BigQuery and the Google Analytics Data API, allowing you to export the raw, unsampled GA4 data and build custom, sophisticated funnel reports using a tool like Looker Studio with the Looker Studio API.
This bypasses the limitations of the standard GA4 Events flow report, enabling you to construct precise SQL queries to map the exact user journey from a specific button click (e.g., Contact_Header_ClickContact_Form_Submit
The long answer is:
Your challenge stems from the inherent limitations of the standard GA4 interface’s pre-built reports, like the Events flow, especially when dealing with high cardinality data combinations like event labels based on full page URLs paired with multiple click origins (header, footer, etc.); the solution is a multi-layered MarTech stack integration.
You must begin by refining your initial data collection; instead of relying solely on the page URL as a differentiating factor, you need to use GTM to send a highly specific click or generate_lead event with a custom parameter, such as click_location
This is best executed using server-side GTM hosted on Stape or GCP to ensure data quality, resilience against client-side ad blockers, and cost-effective data governance, as server-side processing allows for data enrichment and filtering before it ever hits GA4.
The server-side container then uses the Google Analytics Measurement Protocol to reliably send the refined event data to your GA4 property, ensuring the key user action (e.g., a header click) is accurately recorded as a distinct step in the conversion path.
Once this clean data is collected in GA4, the powerful next step is to overcome the reporting constraints by leveraging the BigQuery API to export all of your raw GA4 event data directly into Google BigQuery, a robust, cost-effective data warehouse offered by Google Cloud Platform; this is crucial because BigQuery allows you to query the unaggregated, complete user paths.
With the raw data in BigQuery, you can use standard SQL to create a Common Table Expression (CTE) that filters for all users who had a specific initial event, like click_location = 'header'generate_lead or Purchase event, effectively creating your custom success funnel which is impossible to segment and visualize in the native GA4 Events flow report.
This raw data can then be connected to Looker Studio via its native connector, and for advanced programmatic dashboard management, you could use the Looker Studio API to automate report generation and data synchronization.
This BigQuery and Looker Studio combination, facilitated by the Google Analytics Data API (for smaller queries or checking real-time data) and the BigQuery API (for massive, raw data export), is cost-effective because BigQuery offers a generous free tier for storage and processing, and the analytical power gained far outweighs the minimal operational cost of the cloud infrastructure, providing you with definitive, precise funnel success rates that directly inform your website optimization and marketing spend.
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