This Framework provides a structured approach to validate your Google Analytics implementation, which is crucial for ensuring data quality, maximizing the investment of your marketing spend, and driving informed decision-making across the organization.

Each Framework aligns with ObservePoint capabilities, but it will also include recommended processes, documents, and policies that we recommend an organization consider in their pursuit of excellence.

This Framework is organized into the following Policies:

Each policy contains individual Checks.

For each Check, we will include links to pre-built reports in the ObservePoint Platform and an implementation & remediation guide.

Each check will be accompanied with an icon.

The ✅ icon represents a Check is out of the box available by just running an Audit.

The 🛠️ ✅ icons represent a Check that requires additional configuration.

In addition to checks, there are recommended documents (📄) and processes (⚖️) we encourage you to maintain as they are part of an effective governance program.

Before diving into specifics of each policy, we want to provide our recommendation around scope and frequency of validating your Google Analytics implementation.

If you find that you are having trouble determining how many pages exist on a domain, ask your Success Manager or our Support Team and ask about running a Site Census scan.

If you have additional question regarding our recommendation, contact our team.

This policy represents checks that pertain to the health of the Google Analytics Tag behavior.

When an Google Analytics tag does not return a "Success" (200) status code, it means you the tag was incorrectly implemented and data was not collected which can lead to lack of overall trust in Google Analytics reporting for an organization.

Report in ObservePoint: Pages with Broken Google Analytics Tags

Implementation & Remediation Guide: Link (coming soon)

Similar to the check above, console errors associated with Google Analytics requests mean that the tag was incorrectly implemented and data was not collected which can lead to lack of overall trust in Google Analytics reporting for an organization.

Report in ObservePoint: Pages with Google Analytics Browser Console Errors

Implementation & Remediation Guide: Link (coming soon)

Console warnings associated with Google Analytics requests mean that the tag could be implemented incorrectly. The Warning message will provide more context.

Report in ObservePoint: Pages with Google Analytics Browser Console Warnings

Implementation & Remediation Guide: Link (coming soon)

Google Analytics tags should not tag longer than 500 ms to load. This ensure that impact on page performance is mitigated and data loss is avoided.

Report in ObservePoint: Pages with Google Analytics load times over 500 ms

Implementation & Remediation Guide: Link (coming soon)

This policy represents checks that pertain to how the Google Analytics Tag is implemented for measurement of different events.

All pages should have Google Analytics tags implemented on them to ensure the entire customer journey is accurately reflected in Google Analytics reporting.

Report in ObservePoint: Pages missing Google Analytics

Implementation & Remediation Guide: Link (coming soon)

When Google Analytics data is sent to the wrong Google Analytics account, it can render some reports completely useless. It's critical that when you set up test report suites in lower environments, those test measurement ids do not end up on production pages.

Report in ObservePoint: Measurement Ids for each Domain

Implementation & Remediation Guide: Link (coming soon)

Correct data capture is critical for segmentation and general analysis in Google Analytics reporting. Incorrect event mapping or loss of event attributes will leave you misinformed and lead to reduced conversion event context.

Report in ObservePoint: See Guide Below

Implementation & Remediation Guide: Link (coming soon)

When Google Analytics tags are duplicated, event data is inflated. The result is pages may appear to be converting at 50% of their actual conversion rate and some pages may appear to be have 100% more traffic than reality. This dramatically impacts the perceived customer journey and gives false readings on performance of campaigns.

Report in ObservePoint: Pages with Duplicate Google Analytics Tags

Implementation & Remediation Guide: Link (coming soon)

Precise Google Analytics tag timing is essential because firing too early or too late results in data discrepancies, such as "Unspecified" variables, inflated conversion rates, and broken session attribution. Misaligned firing also poses significant risks to privacy compliance and can lead to under-reporting if tags fail to sync correctly with consent frameworks or page redirects. Furthermore, optimized tag execution ensures data integrity without compromising site performance or losing "hits" due to high latency and rapid user navigation.

Report in ObservePoint: Pages with Google Analytics Tags firing after Largest Contentful Paint

Implementation & Remediation Guide: Link (coming soon)

To ensure reliable transport and data integrity, Google Analytics payloads must use URL-safe, ASCII-compatible characters to prevent browsers, proxies, or middleboxes from corrupting or blocking malformed requests. Maintaining strict character standards is vital for downstream identity stitching in Adobe Experience Platform (AEP), as non-standard encoding causes exact-string-match failures that lead to fragmented or duplicate profiles in the Unified Profile Service.

Report in ObservePoint: Pages with Google Analytics capturing non-ASCII characters

Implementation & Remediation Guide: Link (coming soon)

This policy represents checks that pertain to correct identity recognition and management.

_ga cookies are essential because they ensure consistent visitor recognition and data stitching across Google Analytics reporting. Without these cookies present on every page, identity fragmentation occurs, leading to inaccurate visitor counts, unreliable customer journey analysis, and disjointed user experiences as known visitors are incorrectly treated as anonymous.

Report in ObservePoint: Pages with _ga cookie (Compare with full URL list to find pages missing the cookie)

Implementation & Remediation Guide: Link (coming soon)

This policy represents checks that pertain to correct Data Layer implementation. If you use a custom data layer name, be sure to provide it in our Data Layer settings.

A consistent, site-wide data layer is the "single source of truth" that bridges the gap between your website's raw code and Google Analytics. Without it, your tracking becomes a fragile game of "guesswork" based on unpredictable page elements.

Report in ObservePoint: Pages missing Data Layer

Implementation & Remediation Guide: Link (coming soon)

Validating the mapping between your data layer and Google Analytics is the only way to ensure that the "raw" data on your website is actually being translated into "actionable" insights in your reports. Even if your data layer is perfect, a mapping error can lead to expensive data gaps or permanent corruption of your historical records.

Report in ObservePoint: See Guide Below

Implementation & Remediation Guide: Link (coming soon)

This policy represents checks that pertain to page behavior that support analytics.

Maintaining query parameters through redirects is critical because these parameters are the "DNA" of your marketing attribution. When a server redirect strips these parameters away, Google Analytics loses the connection between the user's click and the resulting site activity.

Report in ObservePoint: Pages that lose query parameters after redirects

Implementation & Remediation Guide: Link (coming soon)

This policy represents checks that pertain to appropriate response to privacy regulations.

Honoring consent is not just a best practice, it is a technical and legal requirement for Google Analytics to operate within the modern digital landscape. When your tags respect user choices, they protect your business from litigation, maintain data integrity, and build consumer trust.

Report in ObservePoint: See Guide Below

Implementation & Remediation Guide: Link (coming soon)

It is critical that Google Analytics tags are configured to avoid collecting Personally Identifiable Information (PII) or Protected Health Information (PHI) because the platform is primarily designed for aggregate behavioral analysis, not as a secure repository for sensitive personal data. Injecting PII/PHI into your analytics hits creates significant legal, financial, and operational liabilities. Google strongly discourages it.

Report in ObservePoint: See Guide Below

Implementation & Remediation Guide: Link (coming soon)

This policy represents recommended documents and processes pertaining to Google Analytics Implementation.

The BRD is the strategic foundation. It is important because it shifts the focus from "what can we track" to "what must we measure." Without a BRD, teams often implement tags that generate "data noise" without answering key business questions. It ensures that stakeholders and developers are aligned on the specific KPIs and business goals before any code is written.

Template: Link (coming soon)

Full Guide: Link (coming soon)

The TSD is the developer’s roadmap. It is important because it translates high-level business needs into technical reality (e.g., CSS selectors, data layer objects, and JavaScript triggers). A solid TSD prevents "guesswork" during implementation, reducing bugs and ensuring that the data layer is structured correctly to be consumed by Google Analytics.

Template: Link (coming soon)

Full Guide: Link (coming soon)

The Measurement Plan is the "Source of Truth" for your data map. It is important because it keeps a permanent record of which customer dimension and event is assigned to which data point. Without a Measurement Plan, analysts have no way of knowing what "cd12" represents, leading to data overwrites, broken reports, and an inability to perform long-term historical analysis.

Template: Link (coming soon)

Full Guide: Link (coming soon)

The Taxonomy Guide is the dictionary for your data. It is important because it defines the naming conventions (e.g., "lowercase only," "use hyphens instead of spaces") for values like campaign names and page categories. Consistent taxonomy ensures that your reports are clean and searchable; without it, your data becomes fragmented (e.g., "Email," "email," and "EMail" appearing as three separate line items).

Template: Link (coming soon)

Full Guide: Link (coming soon)

This policy is the governance firewall for your analytics environment. It is important because it prevents "tag bloat" and data corruption. By rejecting requests that lack a technical spec or a clear business "Why," you ensure that:

This framework is not a comprehensive guide to everything that can or should be done to validate your Google Analytics implementation, but it is a solid foundation.

As ObservePoint unlocks more data and enhances it's platform, we will support more checks to be fully automated. Expect this framework to evolve in time and talk to our Customer Success if you have other checks you want to implement.