Free Google Analytics Audit

Detects sessions where the traffic medium is (not set) in GA4, indicating broken attribution due to missing or stripped UTM parameters or auto-tagging failures.

This test checks whether ad platform click IDs are stored with user records, which is essential for accurate attribution, offline conversion tracking, and campaign-level ROAS analysis.

This test ensures that traffic containing the 'irclickid' parameter is correctly attributed as affiliate in GA4, preventing misclassification and ensuring accurate partner performance reporting.

Ensures all paid CPC traffic includes consistent campaign naming to maintain attribution integrity.

This test checks that utm_campaign values follow consistent, meaningful naming conventions to enable clear reporting by initiative and accurate long-term performance analysis.

This test ensures that all CPC traffic includes a campaign ID, enabling accurate data joins between GA4 and ad platforms for full-funnel reporting and ROI analysis.

This test compares Facebook Ads clicks to GA4 sessions to identify tracking gaps caused by issues like stripped UTMs, privacy settings, or slow-loading pages.

This test compares LinkedIn Ads clicks with GA4 sessions to identify mismatches caused by missing UTMs, redirects, slow-loading pages, or in-app browser tracking limitations.

This test compares Reddit Ads clicks with GA4 sessions to identify attribution gaps caused by limited tracking support, missing UTMs, or in-app browser and redirect issues.

Checks that customized channel grouping is properly configured.

This test checks for duplicate query parameters in GA4 page URLs, which can clutter reports, inflate metrics, and lead to tracking inconsistencies and cardinality issues.

This test checks whether the GA4 client ID is captured in your CRM at record creation, enabling full-funnel attribution, offline conversion tracking, and web-to-CRM journey analysis.

Verifies that Google Ads is properly linked to Google Analytics.

Checks for a healthy ratio of direct traffic to your website.

This test verifies that all paid LinkedIn traffic is properly tagged and attributed in GA4, preventing misclassification and ensuring accurate campaign performance and ROI tracking.

This test checks if GA4 is correctly attributing first-touch sessions to SMS traffic, ensuring SMS campaigns are properly credited in acquisition and performance reporting.

This test detects the use of meta refresh or JavaScript-based redirects that can block GA4 from firing, strip UTMs, and disrupt accurate traffic attribution and session tracking.

Verifies that no payment processors show up as referrals.

This test ensures that traffic with the srsltid parameter is properly attributed to Organic Shopping in GA4, preventing misclassification and helping accurately assess the value of organic product listings.

This test detects whether UTM parameters and click IDs are being stripped during redirects, which can cause GA4 to misattribute sessions and inflate direct traffic metrics.

Verifies that paid search traffic is not erroneously being recorded as organic traffic.

This test ensures that sessions with Snapchat's scCid parameter are correctly attributed to Snapchat Ads in GA4, preventing misclassification and ensuring accurate campaign performance tracking.

This test verifies that traffic with TikTok's ttclid parameter is correctly attributed in GA4 to avoid misclassification and ensure accurate tracking of TikTok Ads performance.

This test ensures that all campaign links across every channel are tagged with UTM parameters, preventing attribution loss and enabling accurate tracking of marketing performance in GA4.

This test verifies that the utm_campaign value in GA4 matches the actual Facebook Ads campaign name to ensure consistent cross-platform reporting and accurate performance analysis.

This test verifies that utm_campaign values in GA4 align with campaign names in Twitter Ads, ensuring accurate attribution and consistent reporting of Twitter campaign performance.

This test compares GA4 and Google Ads conversion counts to identify discrepancies caused by tracking, tagging, or event mapping issues that impact ad performance reporting.

This test compares GA4 and Microsoft Ads conversions to identify major discrepancies caused by tagging issues, tracking failures, or attribution model differences that impact campaign performance insights.

This test compares GA4 and Twitter Ads conversions to identify discrepancies caused by tracking limitations, attribution gaps, or missing UTMs that can lead to underreporting Twitter ad performance.

This test verifies that sessions with Twitter's twclid parameter are correctly attributed in GA4, preventing misclassification and ensuring accurate Twitter Ads performance tracking.

This test detects sessions in GA4 with a (not set) hostname, which typically signals misconfigured tracking, spammy hits, or failures in tag firing that compromise data quality.

This test checks for (not set) values in the GA4 "User Type" dimension, which can signal tracking or identity resolution issues that obscure insights into new vs. returning user behavior.

This test ensures that GA4 event data is being exported to BigQuery daily, as missing tables can indicate broken exports and lead to reporting gaps or failed data workflows.

This test checks whether GA4 uses an allow-list for query parameters to prevent noisy, irrelevant, or sensitive values from inflating cardinality and cluttering reports.

This test evaluates whether GA4 has an optimal number of custom metrics in use, ensuring meaningful quantitative tracking without overloading the property or limiting future flexibility.

This test detects duplicate events within the same session or pageview in GA4, which can inflate metrics and distort performance analysis.

This test ensures that key conversion events are properly defined in GA4, enabling accurate performance tracking, ad optimization, and reporting on meaningful user actions.

This test ensures that the GTM container loads on every page, as missing GTM on key pages can lead to incomplete GA4 tracking and inaccurate analytics data.

This test identifies landing pages with unusually high bounce rates (low engagement rates) in GA4, which may point to issues like slow load times, misaligned content, or tracking errors.

This test flags unrealistically high engagement rates in GA4, often caused by misconfigured events or overly broad engagement triggers that inflate interaction data.

This test flags unusually low conversion rates in GA4, which may indicate tracking issues like missing tags, unmarked conversion events, or misaligned trigger conditions.

This test checks whether login events are tracked in GA4, enabling segmentation, funnel analysis, and re-engagement insights based on known user behavior.

This test ensures that item-level revenue matches total purchase revenue in GA4, as discrepancies often indicate tracking errors that can distort product performance and financial reporting.

This test verifies that GA4 properly tracks internal site search events, providing essential insights into user intent, content gaps, and opportunities for site optimization.

This test checks if GA4 page paths consistently use or omit trailing slashes to prevent duplicate entries and ensure accurate page analytics.

This test identifies excessively high GA4 engagement rates, highlighting potential issues with engagement definitions, event tracking, or traffic configuration.

This test checks if GA4 page paths or URLs incorrectly include dynamic or unique identifiers, which can cause data fragmentation, privacy risks, and reporting issues.

This test verifies whether GA4 add_to_cart events include proper product details, preventing incomplete ecommerce reporting and preserving accurate insights into product performance.

This test ensures add_shipping_info events in GA4 contain complete and accurate product metadata, preserving reliable funnel analysis, product-level attribution, and checkout insights.

This test verifies that GA4 purchase events include complete product metadata, ensuring accurate revenue attribution, product-level reporting, and reliable ecommerce analytics.

This test verifies that begin_checkout events in GA4 include complete product metadata, ensuring accurate checkout analysis, product-level attribution, and actionable insights into checkout behavior.

This test ensures that GA4 correctly captures add_payment_info events, enabling accurate checkout funnel analysis, drop-off insights, and payment preference tracking.

This test verifies that add_to_cart events are properly tracked in GA4, providing insights into cart engagement, funnel performance, and product interest.

This test checks for duplicate transaction_id submissions in GA4, preventing revenue double-counting and ensuring accurate conversion and financial reporting.

This test identifies unusually high cart-to-checkout rates, which may signal misconfigured events, premature checkout triggers, or missing data, leading to misleading funnel performance insights.

This test identifies unusually high "detail to cart" rates, which may signal duplicate or misfiring events, improper timing, or automation issues, leading to misleading insights and skewed ecommerce data.

This test identifies unexpectedly low cart-to-checkout rates, which may indicate technical issues, broken checkout buttons, or tracking problems, resulting in lost purchase intent and missed revenue opportunities.

This test identifies when more payment_info events are recorded than begin_checkout events in GA4, indicating misfiring, duplicate events, or improper tag configuration, which distorts funnel reporting and drop-off analysis.

This test checks for more select_item events than view_item_list events in GA4, indicating missing or broken tracking, misfiring events, or improper setup, which leads to inaccurate funnel analysis and weak product performance insights.

This test ensures that view_item events occur more frequently than select_item events in GA4, indicating proper tracking of product page views, while highlighting potential issues with select_item tracking or non-list product page navigation.

This test ensures that each product name (item_name) in GA4 is consistently associated with a single product ID (item_id), preventing fragmented reporting, duplicated product data, and misleading insights.

This test ensures that remove_from_cart events are firing correctly in GA4, providing insights into cart abandonment, product-level friction, and user purchase intent.

This test identifies if purchase events are firing immediately upon landing, which may indicate duplicate events, misfired tracking, or improper implementation, leading to inflated conversion rates and disrupted funnel analysis.

This test ensures that view_item events are consistently firing in GA4, providing insights into product interest, funnel progression, and merchandising performance.

Checks if GA4 Audiences have been created to enable retargeting or personalization.

Verifies whether recurring dashboards or reports are being generated for stakeholders.

This test ensures that your GA4 implementation complies with cookie consent regulations, preventing legal risks and maintaining user trust.

This test ensures that event and parameter names in GA4 stay within limits to prevent data loss, reporting issues, and tracking failures due to quota ceilings.

This test ensures that your GA4 property is connected to BigQuery, enabling advanced queries, scalable analysis, and access to raw, unsampled event data.

This test ensures that your organization has a defined and repeatable QA process for tracking changes, preventing broken, duplicate, or misfiring events and maintaining trust in analytics.

This test assesses the percentage of site traffic blocking GA4 tracking, helping you interpret metrics accurately and decide if supplemental tracking methods are needed.

This test ensures that GA4 events consistently include standard parameters, providing context for analysis, enabling effective reporting, and ensuring smooth debugging and validation.

This test verifies the uniqueness and consistency of GA4 Client IDs, preventing inflated user counts, inaccurate session attribution, and broken conversion tracking.

This test ensures that an automated tag QA solution is in place, helping detect broken, missing, or duplicate tracking tags to maintain data accuracy and trust in analytics.

This test ensures that testing and staging environments are properly separated from production GA4 data to prevent inflated metrics, polluted data, and skewed reports.