Free Google Analytics (GA4) Audit
- Only takes 90 seconds
- Checks over 70 common data errors
- Customized to your site's goals
- With how-to-fix videos
- Did we say it's FREE?
Things Our Tool Will Check
| Insight Category | Test Name | Focus | Description |
|---|---|---|---|
| Attribution | 59 Tests | Accuracy/Capability | These tests assess how well you can identify where your visitors came from. Strong attribution empowers smarter decisions about where and how to optimize your marketing spend. |
| Attribution | (not set) medium | Accuracy | 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. |
| Attribution | (not set) source | Accuracy | Flags cases where sessions with a (not set) traffic source show up in GA4, which indicates a loss of attribution clarity and hinders accurate reporting on acquisition and campaign performance. |
| Attribution | Ad Platform Click IDs Stored with User Records in CRM / Database / Ecom Backend | Capability | 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. |
| Attribution | Ads Platform Cost Data in Warehouse | Capability | This test verifies that ad platform cost data is consistently imported into your data warehouse to enable accurate ROAS, CPA, and marketing efficiency analysis. |
| Attribution | Affiliate Attribution for All 'irclickid' | Accuracy | This test ensures that traffic containing the 'irclickid' parameter is correctly attributed as affiliate in GA4, preventing misclassification and ensuring accurate partner performance reporting. |
| Attribution | All Campaign Names Are Human Readable | Capability | This test checks that all GA4 campaign names are human-readable, making performance analysis easier and reports clearer for both technical and non-technical stakeholders. |
| Attribution | All Campaign Names Set for CPC | Accuracy | Ensures all paid CPC traffic includes consistent campaign naming to maintain attribution integrity. |
| Attribution | Using Best Practices for Ad Platform Campaign Names | Capability | This test verifies that campaign names from paid platforms follow consistent, descriptive naming conventions to support clear reporting and cross-channel performance analysis. |
| Attribution | Using Best Practices for UTM Campaign, Matching Ad Platform | Accuracy | This test checks that `utm_campaign` values follow consistent, meaningful naming conventions to enable clear reporting by initiative and accurate long-term performance analysis. |
| Attribution | Bing/Microsoft Attribution for All 'msclkid' | Accuracy | Checks that Bing/Microsoft attribution for all 'msclkid' is properly implemented or monitored. |
| Attribution | Campaign Ids Are Set for All CPC | Accuracy | 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. |
| Attribution | Campaign Names Are Not Shared Across Source/Mediums | Accuracy | This test detects if the same campaign name is used across multiple sources or mediums, which can distort channel-level reporting and hinder accurate performance comparisons. |
| Attribution | Match Between Clicks in Facebook/Meta/Instagram to Analytics Sessions | Accuracy | 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. |
| Attribution | Match Between Clicks in Google Ads to Analytics Sessions | Accuracy | This test compares Google Ads clicks with GA4 sessions to spot discrepancies that may stem from missing `gclid` tags, auto-tagging issues, or tracking delays—leading to unreliable attribution. |
| Attribution | Match Between Clicks in LinkedIn to Analytics Sessions | Accuracy | 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. |
| Attribution | Match Between Clicks in Bing/Microsoft Ads to Analytics Sessions | Accuracy | This test compares Microsoft Ads clicks with GA4 sessions to uncover attribution issues like missing UTMs, stripped `msclkid`, or tracking delays that lead to inaccurate performance reporting. |
| Attribution | Match Between Clicks in Reddit to Analytics Sessions | Accuracy | 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. |
| Attribution | Match Between Clicks in Twitter/X to Analytics Sessions | Accuracy | This test compares Twitter Ads clicks with GA4 sessions to detect attribution issues caused by missing UTMs, redirect stripping, in-app browser limitations, or delayed GA4 tag firing. |
| Attribution | Customized Channel Grouping | Capability | Checks that customized channel grouping is properly configured. |
| Attribution | Direct Traffic Segments with Irregularly High Conversion Rates | Accuracy | This test identifies high-converting direct traffic segments, which may indicate broken attribution and the loss of true traffic source data. |
| Attribution | Duplicate Parameters in Page URLs | Accuracy | 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. |
| Attribution | Attribution Model Set to Best-Practice Setting | Accuracy | This test verifies that the GA4 property uses a deliberate, business-aligned attribution model to ensure accurate channel crediting and consistent performance reporting across platforms. |
| Attribution | GA4 Client ID Stored with Records Created in CRM / Ecommerce Backend / etc. | Capability | 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. |
| Attribution | GCLIDs on internal links | Accuracy | This test detects improper use of GCLIDs on internal links, which can fragment sessions, distort attribution, and inflate conversion credit for Google Ads. |
| Attribution | Google Ads Linked to Google Analytics | Capability | Verifies that Google Ads is properly linked to Google Analytics. |
| Attribution | Google Attribution for All Paid Google Links | Accuracy | Checks for appropriate attribution for all paid google links. |
| Attribution | Healthy Ratio of Direct Traffic | Accuracy | Checks for a healthy ratio of direct traffic to your website. |
| Attribution | Healthy Ratio of Other/Unassigned | Accuracy | This test ensures your GA4 property has a low and stable percentage of “Other” or “Unassigned” traffic, as high levels typically signal broken UTMs, misclassified channels, or incomplete attribution. |
| Attribution | LinkedIn Attribution for All Paid LinkedIn Links | Accuracy | 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. |
| Attribution | First-Touch Attribution to Email | Accuracy | This test flags unusually high volumes of users with “Email” as their first source in GA4, which often indicates missing UTM tags and results in misattributed acquisition data. |
| Attribution | First-Touch Attribution to SMS/td> | Accuracy | 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. |
| Attribution | Meta Attribution for All Paid Meta Links | Accuracy | This test verifies that paid Meta traffic is correctly attributed in GA4, as missing UTMs or stripped `fbclid` can lead to misclassification and underreported campaign performance. |
| Attribution | Meta or JS redirects | Accuracy | 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. |
| Attribution | New, Direct Visits to Subpages | Accuracy | This test identifies new users whose first session is direct traffic to subpages—often a sign of missing UTMs, stripped referrer data, or tracking misconfigurations affecting attribution. |
| Attribution | No Payment Processors as Referrals | Accuracy | Verifies that no payment processors show up as referrals. |
| Attribution | No Self Referrals | Accuracy | Checks and flags self referrals. |
| Attribution | Organic Shopping Attribution for All 'srsltid' | Accuracy | 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. |
| Attribution | Production Data is Free of Developer/Testing Traffic | Accuracy | This test checks that GA4 production data is free from internal, developer, or test traffic, which can inflate performance metrics and distort reporting accuracy. |
| Attribution | Query Parameter Stripping Over Redirects | Accuracy | 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. |
| Attribution | Reddit Attribution for All 'rdt_cid' | Accuracy | This test verifies that traffic with Reddit’s `rdt_cid` parameter is correctly attributed in GA4 to avoid misclassification and ensure accurate reporting of Reddit Ads performance. |
| Attribution | Paid Search Traffic Not In Organic Channel | Accuracy | Verifies that paid search traffic is not erroneously being recorded as organic traffic. |
| Attribution | Sign In Domains as Referral Sources | Accuracy | This test detects if third-party login domains are showing as referral sources in GA4, which indicates attribution loss due to session resets during authentication redirects. |
| Attribution | Snapchat Attribution for All 'ScCid' | Accuracy | 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. |
| Attribution | Source Mismatch to Referrer | Accuracy | This test detects mismatches between GA4’s source/medium and the actual referrer, indicating issues like broken UTMs or misconfigured redirects that distort attribution and performance reporting. |
| Attribution | Tiktok Attribution for All 'ttclid' | Accuracy | 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. |
| Attribution | UTMs on All Emails | Accuracy | This test checks that email traffic is consistently tagged with UTM parameters to ensure accurate attribution and prevent email sessions from being misclassified in GA4. |
| Attribution | UTMs on All Possible Links | Accuracy | 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. |
| Attribution | UTMs on Internal Links | Accuracy | This test detects the use of UTM parameters on internal links, which can break session continuity in GA4 and lead to inaccurate attribution, inflated sessions, and misleading funnel data. |
| Attribution | Web Analytics Campaign Name Matches Facebook Ads Campaign Name | Accuracy | 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. |
| Attribution | Web Analytics Campaign Name Matches Reddit Ads Campaign Name | Accuracy | This test ensures that `utm_campaign` values in GA4 match the campaign names used in Reddit Ads, enabling accurate attribution and consistent performance reporting across both platforms. |
| Attribution | Web Analytics Campaign Name Matches Twitter Ads Campaign Name | Accuracy | 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. |
| Attribution | Analytics conversions attributed to Facebook/Meta/Instagram match Facebook/Meta/Instagram platform conversions | Accuracy | This test compares GA4 and Facebook Ads conversion data to identify significant discrepancies caused by tracking issues, missing `fbclid`, or blocked GA4 events. |
| Attribution | Web Analytics Conversions for Google Ads Match Google Ads Conversions | Automated | 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. |
| Attribution | Analytics conversions attributed to LinkedIn match LinkedIn platform conversions | Accuracy | This test compares GA4 and LinkedIn Ads conversions to detect significant discrepancies caused by tagging issues, tracking limitations, or attribution mismatches across platforms. |
| Attribution | Analytics conversions attributed to Microsoft Ads match Microsoft Ads platform conversions | Accuracy | 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. |
| Attribution | Analytics conversions attributed to Reddit Ads match Reddit Ads platform conversions | Accuracy | This test compares GA4 and Reddit Ads conversions to detect significant mismatches caused by tracking gaps, missing UTMs, or attribution differences that can lead to undervaluing Reddit’s performance. |
| Attribution | Analytics conversions attributed to Twitter/X Ads Match Twitter/X Ads platform conversions | Accuracy | 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. |
| Attribution | Analytics conversion counts match backend (CRM/Ecommerce/Booking) | Accuracy | This test compares GA4 conversion and revenue data with backend systems to detect tracking issues, missed events, or duplicate conversions that can distort performance insights. |
| Attribution | X / Twitter Attribution for All 'twclid' | Accuracy | This test verifies that sessions with Twitter’s `twclid` parameter are correctly attributed in GA4, preventing misclassification and ensuring accurate Twitter Ads performance tracking. |
| Behavior | 33 Tests | Accuracy/Capability | These tests assess how well you track what visitors do once they arrive on your site. Accurate behavioral data helps you understand user engagement and optimize the onsite experience. |
| Behavior | (not set) Hostname | Accuracy | 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. |
| Behavior | (not set) Landing Pages | Capability | This test identifies sessions with a `(not set)` landing page in GA4, indicating tracking delays or errors that disrupt attribution, entry-point analysis, and funnel accuracy. |
| Behavior | (not set) user type | Accuracy | 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. |
| Behavior | Backend/CRM Data in Warehouse | Capability | This test verifies that backend or CRM data is available in your data warehouse and joinable with GA4, enabling full-funnel reporting and marketing-to-revenue attribution. |
| Behavior | BigQuery Tables Fresh in Last 24 Hours | Accuracy | 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. |
| Behavior | Capturing First-Party User ID or Email | Capability | This test verifies that a first-party User ID is being captured in GA4, enabling accurate cross-device tracking, user stitching, and advanced audience and LTV analysis. |
| Behavior | Cleaned page paths / allow-list of query parameters | Capability | 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. |
| Behavior | Custom Dimensions Implemented to Match Business Questions | Capability | This test assesses whether your GA4 property has an appropriate number of custom dimensions in use, balancing flexibility and performance to support meaningful, tailored analysis. |
| Behavior | Custom Metrics Implemented to Match Business Questions | Capability | 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. |
| Behavior | Customer Journeys Defined and In-Use | Capability | This test verifies that customer journeys are clearly defined and leveraged in GA4 reporting, enabling more strategic analysis, attribution, and optimization across the full funnel. |
| Behavior | Duplicate Events | Accuracy | This test detects duplicate events within the same session or pageview in GA4, which can inflate metrics and distort performance analysis. |
| Behavior | Duplicate Pageviews | Accuracy | This test identifies cases where multiple `page_view` events are triggered from a single pageview, which can distort engagement metrics such as bounce rate and average engagement time. |
| Behavior | GA4 Conversions / Key Events Defined | Capability | This test ensures that key conversion events are properly defined in GA4, enabling accurate performance tracking, ad optimization, and reporting on meaningful user actions. |
| Behavior | GA4 Tracking Firing on All Pages | Accuracy | This test checks that the GA4 base tracking code fires on every site page to ensure complete data capture for sessions, events, and conversions across the user journey. |
| Behavior | Google Tag Manager on All Pages | Accuracy | 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. |
| Behavior | Have Content Groupings | Capability | This test verifies that content groupings are set up in GA4, enabling analysis of user behavior by content type rather than just by individual page URLs. |
| Behavior | Irregularly High Bounce Rate Landing Pages | Accuracy | 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. |
| Behavior | Irregularly High Conversion Rate | Accuracy | This test detects unusually high conversion rates that may be caused by duplicate events, misconfigured tags, or inflated tracking, leading to distorted performance metrics. |
| Behavior | Irregularly High Engagement Rates | Accuracy | This test flags unrealistically high engagement rates in GA4, often caused by misconfigured events or overly broad engagement triggers that inflate interaction data. |
| Behavior | Irregularly Low Bounce Rate Landing Pages | Accuracy | This test identifies landing pages with abnormally low bounce rates, often signaling tracking issues like duplicate events or auto-triggered engagement that distort content performance insights. |
| Behavior | Irregularly Low Conversion Rate | Accuracy | This test flags unusually low conversion rates in GA4, which may indicate tracking issues like missing tags, unmarked conversion events, or misaligned trigger conditions. |
| Behavior | Irregularly Low Engagement Rates | Accuracy | This test detects unusually low engagement rates in GA4, which may result from poor user experience or broken tracking that fails to register valid user interactions. |
| Behavior | 'login' Events Are Tracking | Capability | This test checks whether login events are tracked in GA4, enabling segmentation, funnel analysis, and re-engagement insights based on known user behavior. |
| Behavior | Malicious/Bot/Non-Human Traffic | Accuracy | This test detects bot or non-human traffic in GA4, which can distort engagement metrics and inflate performance data if not properly filtered out. |
| Behavior | Match Between Item Revenue and Purchase Revenue | Accuracy | 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. |
| Behavior | 'purchase' Events Are Tracking | Capability | This test verifies that the purchase event in GA4 fires correctly, ensuring accurate tracking of transactions and revenue attribution. |
| Behavior | 'search' Events Are Tracking | Capability | This test verifies that GA4 properly tracks internal site search events, providing essential insights into user intent, content gaps, and opportunities for site optimization. |
| Behavior | 'sign_up' Events Are Tracking | Capability | This test confirms accurate tracking of the `sign_up` event in GA4, essential for analyzing user engagement, conversion attribution, and marketing performance. |
| Behavior | Standardize Trailing Slashes on Page Paths | Capability | This test checks if GA4 page paths consistently use or omit trailing slashes to prevent duplicate entries and ensure accurate page analytics. |
| Behavior | Thank you pages without an event | Accuracy | This test verifies that "Thank You" or confirmation pages correctly trigger GA4 conversion events, ensuring accurate tracking of successful user actions and preventing underreporting. |
| Behavior | Too High Engagement Rate to Be Useful | Capability | This test identifies excessively high GA4 engagement rates, highlighting potential issues with engagement definitions, event tracking, or traffic configuration. |
| Behavior | Tracking At Least Some Custom Events | Capability | This test assesses if a GA4 property tracks custom events, which capture essential business-specific user actions beyond standard or recommended events. |
| Behavior | Unique IDs in Pages | Capability | 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. |
| Ecommerce | 34 Tests | Accuracy/Capability | These tests evaluate the accuracy and completeness of your ecommerce tracking. High-quality purchase data is essential for measuring performance and unlocking meaningful revenue insights. |
| Ecommerce | (not set) Item at `add_to_cart` | Accuracy | This test verifies whether GA4 `add_to_cart` events include proper product details, preventing incomplete ecommerce reporting and preserving accurate insights into product performance. |
| Ecommerce | (not set) Item at 'add_payment_info' | Accuracy | This test verifies if `add_payment_info` events in GA4 include complete product metadata, preventing reporting gaps and ensuring accurate analysis of checkout behavior and product performance. |
| Ecommerce | (not set) Item at 'add_shipping_info' | Accuracy | 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. |
| Ecommerce | (not set) item at list view | Accuracy | This test checks if `view_item_list` events in GA4 contain complete product metadata, ensuring accurate tracking of product lists, conversions, and merchandising effectiveness. |
| Ecommerce | (not set) Item at 'purchase' | Accuracy | This test verifies that GA4 `purchase` events include complete product metadata, ensuring accurate revenue attribution, product-level reporting, and reliable ecommerce analytics. |
| Ecommerce | (not set) item at view_item/product detail | Accuracy | This test ensures `view_item` events in GA4 include complete product metadata, maintaining accurate insights into product views, user browsing behavior, and funnel performance. |
| Ecommerce | (not set) items at checkout | Accuracy | 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. |
| Ecommerce | (not set) Transaction ID at purchase | Accuracy | This test verifies that GA4 ecommerce transactions have valid, unique Transaction IDs, preventing duplicate reporting and ensuring accurate revenue attribution. |
| Ecommerce | 'add_payment_info' Events Are Tracking | Capability | This test ensures that GA4 correctly captures `add_payment_info` events, enabling accurate checkout funnel analysis, drop-off insights, and payment preference tracking. |
| Ecommerce | 'add_shipping_info' Events Are Tracking | Capability | This test ensures that `add_shipping_info` events in GA4 are firing correctly, enabling detailed checkout funnel analysis, drop-off tracking, and optimization of the purchase process. |
| Ecommerce | 'add_to_cart' Events Are Tracking | Capability | This test verifies that `add_to_cart` events are properly tracked in GA4, providing insights into cart engagement, funnel performance, and product interest. |
| Ecommerce | 'begin_checkout' Events Are Tracking | Capability | This test ensures that the `begin_checkout` event is correctly implemented in GA4, enabling accurate funnel tracking, checkout optimization, and insights into purchase intent. |
| Ecommerce | Duplicate Transaction Ids | Accuracy | This test checks for duplicate `transaction_id` submissions in GA4, preventing revenue double-counting and ensuring accurate conversion and financial reporting. |
| Ecommerce | Duplicate Transactions: Too Close Together | Accuracy | This test identifies multiple transactions recorded in a short timeframe within the same session or user, which may indicate duplicate events and distort revenue and conversion metrics. |
| Ecommerce | Irregularly High Cart To Checkout Rates | Accuracy | 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. |
| Ecommerce | Irregularly High Checkout To Transaction Rates | Accuracy | This test identifies an abnormally high purchase-to-begin_checkout ratio, which may indicate missing tracking, duplicate events, or server-side errors, leading to misleading funnel metrics and poor optimization insights. |
| Ecommerce | Irregularly High Detail To Cart Rates | Accuracy | 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. |
| Ecommerce | Irregularly Low Add to Cart Rate | Accuracy | This test identifies unusually low "add to cart" rates, which may point to tracking issues, poor user experience, or low product appeal, leading to lost insights and early breakdowns in the ecommerce funnel. |
| Ecommerce | Irregularly Low Cart To Checkout Rates | Accuracy | 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. |
| Ecommerce | Item Variant in Item Name | Accuracy | This test checks whether product variant information is correctly passed via the `item_variant` parameter in GA4, preventing bloated reporting, fragmented metrics, and ensuring cleaner, scalable product analysis. |
| Ecommerce | More 'payment_info' than 'begin_checkout' | Accuracy | 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. |
| Ecommerce | More 'payment_info' than 'shipping_info' | Accuracy | This test checks for more `add_payment_info` events than `add_shipping_info` events in GA4, indicating tracking issues, misfiring events, or improper event sequencing that distorts funnel analysis and user drop-off detection. |
| Ecommerce | More 'select_item' than 'view_item_list' | Accuracy | 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. |
| Ecommerce | More 'shipping_info' than 'begin_checkout' | Accuracy | This test identifies when `add_shipping_info` events outnumber `begin_checkout` events in GA4, suggesting tracking issues, premature event triggers, or server-side errors that distort funnel insights and hinder optimization. |
| Ecommerce | More 'view_item' than 'select_item' | Accuracy | 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. |
| Ecommerce | Product Id is Associated with Only One Name | Accuracy | This test ensures that each product ID (`item_id`) in GA4 is consistently paired with a single product name (`item_name`), preventing reporting issues, inflated product counts, and corrupted performance metrics. |
| Ecommerce | Product Name is Associated with Only One Id | Accuracy | 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. |
| Ecommerce | 'refund' Events Are Tracking | Capability | This test ensures that refund events are correctly implemented in GA4, allowing accurate revenue adjustments, performance tracking, and insights into refund patterns. |
| Ecommerce | 'remove_from_cart' events are tracking | Capability | 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. |
| Ecommerce | 'select_item' Events Are Tracking | Capability | This test ensures that `select_item` events are properly implemented in GA4, enabling tracking of product list performance, click-through rates, and user engagement with product discovery. |
| Ecommerce | Transactions Happen on the Landing Page | Accuracy | 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. |
| Ecommerce | Transactions with No Revenue | Accuracy | This test identifies transactions in GA4 that are recorded without revenue, helping to avoid inaccurate reporting and misleading ecommerce insights. |
| Ecommerce | 'view_item' Events Are Tracking | Capability | This test ensures that `view_item` events are consistently firing in GA4, providing insights into product interest, funnel progression, and merchandising performance. |
| Ecommerce | 'view_item_list' Events Are Tracking | Capability | This test ensures that `view_item_list` events are firing correctly, providing insights into product list performance, user engagement, and merchandising strategies. |
| Activation | 1 test | Accuracy/Capability | These tests assess your ability to use analytics data to build and activate audiences. When properly configured, your setup enables smarter targeting across ad platforms and marketing channels. |
| Activation | Audiences Are Setup for Import to PPC Campaigns | Capability | Checks if GA4 Audiences have been created to enable retargeting or personalization. |
| Reporting | 2 Tests | Accuracy/Capability | These tests examine the structure and clarity of your reporting setup. Clean, well-organized data ensures better analysis, faster decision-making, and more actionable insights. |
| Reporting | Have Automated Reporting | Capability | Verifies whether recurring dashboards or reports are being generated for stakeholders. |
| Reporting | Have Automated Reporting from Warehouse (Centralized Data) | Capability | This test ensures that automated, centralized reporting is in place, providing scalable, reliable insights by integrating GA4, ad platforms, CRM, and financial data. |
| Settings & Compliance | 18 Tests | Accuracy/Capability | These tests review your foundational GA4 settings and compliance configurations. Getting the basics right—like cookie consent and data retention—helps ensure accurate tracking and legal alignment. |
| Settings & Compliance | Cookie Compliance Implemented Per Regional Requirements | Capability | This test ensures that your GA4 implementation complies with cookie consent regulations, preventing legal risks and maintaining user trust. |
| Settings & Compliance | Cookie Compliance: GA4 Consent Mode | Capability | This test ensures that Google Consent Mode is implemented with GA4, allowing compliance with privacy laws and proper tracking based on user consent. |
| Settings & Compliance | Event Names and Parameter Names That Are Close to Character Limits | Capability | 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. |
| Settings & Compliance | GA4 Data Retention Set to Maximum | Capability | This test ensures that GA4 data retention settings are configured for the maximum period, preventing the loss of historical data needed for long-term analysis. |
| Settings & Compliance | Google Analytics Linked to BigQuery | Capability | This test ensures that your GA4 property is connected to BigQuery, enabling advanced queries, scalable analysis, and access to raw, unsampled event data. |
| Settings & Compliance | Google Search Console Linked to GA4 | Capability | This test ensures that Google Search Console is properly linked to GA4, enhancing reporting with SEO insights and enabling cross-analysis of search performance and on-site engagement. |
| Settings & Compliance | Have a QA Process Defined | Capability | 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. |
| Settings & Compliance | Informational: Any HTTP Links? | Accuracy | This test flags non-secure (HTTP) links on your site, highlighting potential data integrity risks, loss of referrer information, and negative SEO impacts. |
| Settings & Compliance | Percent of Traffic Blocking Tracking | Accuracy | This test assesses the percentage of site traffic blocking GA4 tracking, helping you interpret metrics accurately and decide if supplemental tracking methods are needed. |
| Settings & Compliance | Sensitive Customer Information Stored in Analytics | Capability | This test detects whether PII or sensitive customer data is being sent to GA4, ensuring compliance with Google’s Terms of Service and preventing legal risks. |
| Settings & Compliance | Standard Parameters | Capability | This test ensures that GA4 events consistently include standard parameters, providing context for analysis, enabling effective reporting, and ensuring smooth debugging and validation. |
| Settings & Compliance | Tag Manager Tags Loading with Lowest Reasonable Priority (Optimize Page Load Speeds) | Capability | This test ensures that GTM tags are loaded with the lowest reasonable priority, optimizing page load speeds and improving overall site performance. |
| Settings & Compliance | Uniqueness of Client Id | Accuracy | This test verifies the uniqueness and consistency of GA4 Client IDs, preventing inflated user counts, inaccurate session attribution, and broken conversion tracking. |
| Settings & Compliance | Using a Tag Management System | Capability | This test ensures that a Tag Management System (TMS) like Google Tag Manager is used, providing centralized control, faster updates, and cleaner implementation for tracking scripts. |
| Settings & Compliance | Using Automated Tag QA | Capability | 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. |
| Settings & Compliance | Using Event Create Rules? | Accuracy | This test ensures that Event Create Rules in GA4 are used appropriately to transform events into more meaningful ones without altering the original tag implementation, preventing confusion and inconsistent reporting. |
| Settings & Compliance | Using Testing Environments | Capability | This test ensures that testing and staging environments are properly separated from production GA4 data to prevent inflated metrics, polluted data, and skewed reports. |
| Settings & Compliance | GA4 Data Retention Set to Maximum | Automated | Checks if GA4 is configured to retain user data for the maximum duration of 14 months. |
Get Your Grade in 3 Easy Steps
Authorize Your Account
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Run the Audit
In 90 seconds the audit will evaluate over 70 data collection issues.
Review the Findings
See your scores, organized by category, with clear next steps.
When Your Data Isn't Accurate
- Your team doesn't fully trust your (or their own) decisions
- You waste time backpedaling on your data stories
- Your team will never has the insights needed to make gains
And that means—marketing will rely on gut feel, money will be wasted, and you’ll be the focus of the wrong kind of attention.
No marketing professional should have to live this way.
What Makes This Google Analytics Audit Different?
This Google Analytics Audit tool was built to help our clients, and now we’re making it free for you.
| Feature / Criteria | Our Free Audit Tool | Other Free Tools | Paid Agency Results |
|---|---|---|---|
|
Price |
Free |
Free |
$5k - $20k+ |
|
Time to Results |
90 Seconds |
10-30 minutes or unclear |
Days to weeks |
|
Requires Signup / Sales Call |
No |
Often yes |
Always required |
|
# of Tests |
145, more added every month |
10 - 30 max |
Varies, but not transparent |
|
Immediate Access to Better Reports |
Yes |
No |
No |
|
Covers Google Analytics & BigQuery / Warehouse |
Yes |
Rarely |
Sometimes |
|
Includes Ecommerce Checks |
Yes |
Limited |
Yes |
|
Attribution & Behavior Checks |
Deep |
Shallow or missing |
Typically included |
|
Actionable Recommendations |
Yes, step-by-step fixes |
Often too generic to implement |
Yes, but typically high-level |
|
Score or Grading System |
Yes |
No |
Sometimes |
|
Accuracy vs. Capability Framework |
Yes |
No |
Rarely |
|
Shareable Report |
Yes |
Sometimes |
Usually |
|
Strategy / Consulting Access |
Optional Add-On |
No |
Yes |
|
Ongoing Monitoring |
Yes |
No |
Sometimes (paid retainer) |
|
Built by Analytics Experts |
Yes |
Unclear |
Yes |
|
Transparent Methodology |
Publicly exposed |
Often vague |
Rarely |
FAQs
Is the Google Analytics Audit really free?
Yep! And none of that “hide 80% of the results” nonsense.
Maybe you’ll consider working with us for fixes, strategic consulting, or our GA4addON tools.
What does adMind get out of this?
The chance to share some good ideas.
Maybe you’ll consider working with our team for fixes, marketing strategy, or one of our GA4addON tools.
Do you have tools to make Google Analytics better?
Yes!
- A no-code way to get all the value out of your raw data. Reports included.
- Performance monitoring for the whole marketing stack. Nothing flies under your radar again.
What do I do if I get 'needs manual review' results?
That can happen. There are many things that we can’t check with the Google Analytics API.
One of our consultants would love to help you dig in further.
How many times can I run a free audit?
As many times as you want for as many Google Analytics properties as you want.
