Troubleshooting guide to measuring traffic properly (GA4 basics)

Troubleshooting guide to measuring traffic properly (GA4 basics)

Measuring site traffic in GA4 often feels straightforward until the numbers do not match expectations, and a troubleshooting approach becomes essential. This guide lays out practical checks and fixes you can apply when sessions, users, or conversions look wrong. I focus on foundational items you can verify quickly without advanced analytics knowledge, and I avoid tools that require additional investment. Follow the steps in order and keep notes of changes so you can track which adjustment resolves the issue.

Start by spotting common symptoms: sudden drops or spikes in sessions, a mismatch between realtime reports and last 48 hours, missing conversions, or unusually high bounce rates that don’t align with page behaviour. Narrowing the symptom down early saves time because the root causes often cluster around tagging, configuration, or data processing settings. If you see a consistent offset—such as a persistent 10 to 20 percent shortfall—consider measurement gaps like missing tags or blocked scripts before changing attribution or reporting windows.

Run this quick checklist to eliminate the usual suspects before deep diving into configuration details.

• Confirm the correct Measurement ID is applied on pages and in any tag manager implementations.
• Use GA4 Realtime and DebugView to verify events fire when you trigger them locally.
• Check that cookie consent tools are not blocking analytics scripts unintentionally.
• Verify that internal traffic filters are set accurately and not excluding legitimate visits.
• Ensure that any experimental filters or data streams were not modified recently.

If tags or scripts are the problem, the DebugView in GA4 and a browser console are your best friends. Open an incognito window, disable extensions that might block analytics, and watch events land in DebugView while you navigate the site. If events do not appear, confirm the tag container is published and that the Measurement ID in the tag or gtag snippet matches the property you are inspecting. For sites using Google Tag Manager, check that triggers are firing and that tags are not paused or blocked by trigger exceptions.

Data processing settings and filters cause many subtle issues. An incorrectly defined internal traffic rule can remove legitimate sessions, while aggressive IP exclusion or custom filters can distort reports. GA4’s bot filtering checkbox is useful but not perfect, and server-side tagging introduces a different set of questions about which traffic is attributed to your property. Review data retention settings and time zone configuration because mismatches here create confusion when comparing daily totals across tools or platforms.

Events and conversions are a common area of discrepancy, especially after a migration from Universal Analytics. Ensure required parameters for conversion events are present and that you have marked the correct events as conversions in the GA4 interface. Remember that GA4 treats events as the primary data model, so missing parameters or inconsistent event names lead to gaps in conversion reporting. Where possible, standardise event naming and centralise tag logic in a tag manager to reduce drift between pages and campaigns.

Attribution, sampling and reporting delays are final things to check when numbers look off. GA4 may apply attribution models that assign conversions across touchpoints in ways that differ from legacy systems. Data export to BigQuery helps when you need raw, unsampled records for reconciliation but consider it only after fixing tagging and configuration. Keep in mind that consent settings, page redirects or ad-blockers can prevent hits from reaching GA4 and that network errors or content security policies may block scripts intermittently. For ongoing learning and related posts on measurement and growth, see the collection on SEO & Growth at Build & Automate. For more builds and experiments, visit my main RC projects page.