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  1. Post-Universal Analytics Sunset: What Should You Have Done? + Common GA4 Challenges 

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    It’s been 15 months (3 months since 360) since Google officially retired Universal Analytics (UA) and moved everything over to Google Analytics 4 (GA4). This transition wasn’t just a simple update—it introduced a completely new tracking code that changed how you collect, analyse, and use your data. For brands reliant on accurate data to drive decisions, a smooth transition has been crucial. 

    If you haven’t fully optimised your GA4 setup or are still encountering issues, here’s what you should have done by now and the common challenges businesses are facing with GA4. 

    What Should You Have Done by Now? 

    1. Migrated & Safeguarded Historical Data 

    One of the first and most crucial steps was to export historical data from UA, as there is no automatic transfer into GA4. By now, you should have: 

    • Exported historical reports and key metrics from UA to ensure you have access to year-on-year comparisons. 
    • Set up a data storage solution, such as Google BigQuery or Looker Studio (formerly Data Studio), to integrate old UA data with your GA4 reports for better continuity. 

    Common Problem: Some businesses overlooked this step, leaving them without access to historical data, making it difficult to measure long-term trends. 

    2. Mapped Goals to GA4 Events 

    GA4 uses an event-based tracking model, replacing UA’s session-based approach. To ensure continuity in your reporting, you should have: 

    • Mapped your UA goals to GA4 events to track key interactions like form submissions, purchases, or button clicks. 
    • Implemented Enhanced Measurement Events that allow GA4 to automatically track actions like scroll depth, video views, and outbound clicks. 

    Common Problem: Many businesses are still relying on GA4’s default events, which often aren’t detailed enough for the specific tracking needs of each business. 

    3. Updated the DataLayer & Google Tag Manager (GTM) 

    GA4 requires a new structure for tracking information via the dataLayer and GTM tags. By now, you should have: 

    • Reviewed and updated your dataLayer to meet GA4’s schema, ensuring that key interactions are being tracked and reported accurately. 
    • Refined your GTM tags to work within GA4’s event-based model, especially for eCommerce tracking, where the setup in GA4 is notably different from UA. 

    Common Problem: Brands that haven’t adjusted their dataLayer or GTM setup are experiencing gaps in data, particularly around eCommerce transactions and user journeys. 

    4. Set Up Cross-Domain Tracking 

    GA4 makes it easier to track users across different domains compared to UA. If your site has a separate checkout process or uses subdomains, you should have: 

    • Implemented cross-domain tracking to prevent session duplication and to ensure user journeys are accurately reported across domains. 

    Common Problem: Misconfigured cross-domain tracking results in fragmented data, where user sessions are split across domains, leading to inaccurate attribution. 

    5. Built Custom Audiences for Marketing 

    GA4’s advanced audience-building features, powered by machine learning, enable highly personalised marketing campaigns. By now, you should have: 

    • Created custom audiences based on user behaviours, like those who abandoned carts or made a purchase. 
    • Used predictive metrics such as purchase probability or churn probability to enhance your remarketing strategies. 

    Common Problem: Many businesses are underutilising GA4’s audience-building tools, missing out on advanced targeting opportunities that could drive better marketing performance. 

    Common Challenges Brands Are Facing 

    Despite the benefits GA4 offers, the transition hasn’t been without its difficulties. Here are some of the most common challenges businesses are facing: 

    1. Complex Event Tracking 

    GA4’s flexibility in event tracking also comes with added complexity. Many businesses struggle with: 

    • Setting up custom events, which are necessary for tracking specific user actions beyond the default settings. 
    • Understanding parameter limits, with GA4 capping the number of parameters you can use per event. For more complex sites, this requires careful planning to avoid missing important data. 

    2. Attribution Model Changes 

    GA4 introduces a shift to a data-driven attribution model, replacing UA’s last-click default. While more accurate, it has created challenges for some businesses: 

    • Data discrepancies: Businesses used to UA’s last-click attribution may find their GA4 reports showing different conversion paths and crediting different channels. 
    • Reporting complexity: GA4’s attribution reports can be harder to navigate for teams that relied on simpler UA reporting. 

    3. Sampling & Data Limitations 

    In an effort to preserve user privacy, GA4 uses data thresholds, which can lead to: 

    • Sampled data in larger datasets, reducing accuracy in reports. 
    • Suppressed data for smaller websites, where anonymisation rules limit the granularity of reports, especially in segments like age, gender, or interest. 

    4. Integrating GA4 with Other Tools 

    Many brands rely on a wider marketing technology (MarTech) stack that includes CRM systems, advertising platforms, and email marketing tools. The new data model in GA4 has made some integrations more difficult: 

    • Data flow issues: Integrating GA4 with platforms like CRM systems or Google Ads requires more advanced configuration due to the event-based structure. 
    • Loss of key reports: Some reports and metrics from UA, such as bounce rate, don’t exist in GA4 in the same way, causing friction for teams used to the old reporting structure. 

    5. Data freshness and processing time 

    There is a much longer processing time for data to appear in your GA4 account. GA4’s new data collection methodology introduces a significant delay. 

    • Data Inconsistencies:  These fluctuations can lead to misinterpretation of results, causing wasted investments and inaccurate business insights. with businesses potentially waiting up to 48 hours for accurate data to appear in their accounts 
    • Variable Traffic Source Categorization: Traffic sources in GA4 can be retroactively categorized up to 12 days after initial data appears. This variability adds another layer of uncertainty, complicating real-time analysis and the ability to respond swiftly to marketing performance. 

    Conclusion: Optimising Your GA4 Setup 

    By now, businesses should have made significant progress in optimising their GA4 setup. If you haven’t: 

    • Audit your current setup to make sure you’re tracking all key events, goals, and user interactions. 
    • Refine your dataLayer and GTM tags to ensure they align with GA4’s requirements. 
    • Check your reports for accuracy and make sure data discrepancies are resolved by reviewing cross-domain tracking, attribution models, and audience configurations. 

    The shift to GA4 offers tremendous potential for deeper insights and more accurate data—if configured correctly. If you’re still facing challenges or unsure if your setup is performing at its best, Fabric Analytics is here to help. We specialise in GA4 audits and custom configurations, ensuring your business gets the most out of its analytics and reporting. 

  2. Why Using a GA3 dataLayer in GA4 Will Lead to Tracking and Ad Optimisation Issues

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    Since the transition to Google Analytics 4 (GA4), many businesses may still be relying on legacy GA3 (Universal Analytics) configurations for their dataLayer. While this might seem like a quick fix, using a GA3-configured dataLayer in GA4 can lead to tracking issues that ultimately affect data accuracy and ad optimisation. In this post, we’ll explore why using your old GA3 dataLayer can hinder your progress and how Fabric Analytics can guide you through a seamless transition to GA4, including a free GA4 audit to help you get started.

    Key Differences Between GA3 and GA4 dataLayers

    Although GA3 and GA4 both utilise a dataLayer for tracking user behaviour, the structures are vastly different. GA4 brings an advanced event-driven tracking model that offers a more nuanced understanding of user behaviour across devices and platforms. Here are some key differences between the two:

    1. Event-Based Tracking Model
      GA3 relied on predefined hit types like pageviews and transactions, whereas GA4 is entirely event-driven. This flexible model allows for custom event tracking, making it possible to collect more detailed insights into user interactions. A GA3 dataLayer, however, isn’t built to accommodate this flexibility, leading to missed or incorrect data capture.
    2. Custom Parameters
      GA4 utilises custom parameters for more granular tracking of user interactions, while GA3 primarily used event categories, actions, and labels. If you continue using a GA3 dataLayer, you may lose vital tracking capabilities, resulting in inaccurate reporting.
    3. User-Centric Tracking
      GA4 shifts the focus from session-based tracking to user-centric tracking, enabling better analysis of individual users’ journeys across devices. GA3’s dataLayer, however, doesn’t have this capability, leading to fragmented and inconsistent data.

    Common Issues When Using a GA3 dataLayer in GA4

    Failing to adapt your GA3 dataLayer to GA4 standards can cause several problems that compromise the quality of your data and impact ad optimisation:

    1. Incomplete Data Collection
      GA4 expects a specific event structure that differs from GA3. If your dataLayer isn’t updated, you risk not capturing important interactions like purchases, leading to missed revenue and skewed reports.
    2. Incorrect Event Attribution
      GA4 tracks events with greater detail through custom parameters, and using a GA3 dataLayer can result in misattributed events. This misalignment affects your understanding of user behaviour and impairs decision-making.
    3. Inconsistent Cross-Device Tracking
      GA4 excels in tracking users across multiple devices and sessions. A GA3 dataLayer can’t support this capability, which can result in incomplete user journeys and lower-quality insights.

    Impact on Ad Optimisation

    In addition to data tracking issues, a misconfigured dataLayer can disrupt your ad optimisation efforts:

    1. Reduced Audience Targeting Accuracy
      GA4 relies on precise event tracking for audience segmentation. If your dataLayer isn’t properly configured, your ad targeting will suffer, leading to increased acquisition costs and lower returns on ad spend (ROAS).
    2. Inaccurate Conversion Data
      Incorrect event tracking skews conversion reporting, causing you to misallocate budget. Over-investing in underperforming channels or under-investing in high-performing ones can significantly reduce campaign efficiency.
    3. Skewed Attribution Models
      GA4’s advanced attribution models, like data-driven attribution, require accurate event data. If your dataLayer is not tracking events properly, attribution credit may be assigned incorrectly, leading to poor insights and inefficient budget allocation.

    How Fabric Analytics Can Help

    At Fabric Analytics, we specialise in helping businesses transition their dataLayer setups from GA3 to GA4, ensuring that tracking is accurate and fully optimised for your needs. Here’s how we can assist:

    1. Free GA4 Audit
      As a starting point, we offer a free GA4 audit to review your current tracking setup and highlight potential issues. This audit includes an analysis of your dataLayer configuration, event tracking, and GA4 readiness, ensuring you have a clear understanding of where improvements are needed.
    2. dataLayer Rebuild
      Once we’ve completed the audit, our team will work with you to rebuild your dataLayer from the ground up for GA4. We’ll ensure it aligns with GA4’s event-based tracking model and is configured to track the most relevant interactions for your business.
    3. Bespoke GA4 Configuration
      Every business has unique goals, and we make sure your dataLayer is tailored to fit them. Whether you need enhanced ecommerce tracking, cross-platform analytics, or custom event tracking, we’ll configure GA4 to capture the insights that matter most to you.
    4. Thorough Testing and QA
      Before full deployment, we run parallel tracking between GA3 and GA4 to identify discrepancies and fine-tune your setup. Our comprehensive QA process ensures events are firing correctly and data is being accurately recorded.
    5. Ongoing Support
      Once your GA4 setup is in place, we provide ongoing support to monitor performance and make adjustments as needed. We help ensure your dataLayer continues to evolve as your business grows, providing accurate insights for future decision-making.

    Conclusion

    Using a GA3 dataLayer in GA4 creates significant risks for data accuracy, reporting, and ad optimisation. With GA4’s event-driven, user-centric model, updating your dataLayer is essential to ensure you capture the right data for smarter decision-making. At Fabric Analytics, we offer a free GA4 audit to help you assess your current setup and guide you through a seamless transition to GA4.

    Get in touch today to learn more about how we can help you future-proof your tracking and optimise your ad performance with GA4.

  3. Elevate Your CRO with Expert A/B Testing for Complex Web Frameworks

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    In the fast-paced world of digital marketing, Conversion Rate Optimisation (CRO) is a key driver of success. A/B testing is a critical component of CRO, enabling businesses to optimise their websites by comparing different versions and identifying what works best. However, the complexities of modern web technologies require a more sophisticated approach to A/B testing—one that goes beyond basic tools and taps into deep technical expertise.

    At Fabric Analytics, we specialise in conducting advanced A/B tests, particularly on websites built with complex JavaScript frameworks like React, Angular, and Vue.js. Our expert team doesn’t just rely on WYSIWYG (What You See Is What You Get) tools. Instead, we leverage our deep understanding of web development, ensuring that our tests are both accurate and actionable.

    The Complexity of Modern A/B Testing

    Websites built with advanced JavaScript frameworks pose unique challenges for A/B testing. These frameworks, which power many modern websites, create dynamic, interactive experiences that are far more complex than traditional static sites. As a result, testing these sites requires a deep technical understanding of how they work.

    Some of the challenges include:

    • Component Re-renders: Dynamic components may not behave consistently under simple testing tools, leading to unreliable data.
    • State Management: Handling state changes within single-page applications (SPAs) is complex and demands precise testing techniques.
    • Performance Concerns: Poorly executed tests can lead to performance issues, distorting test results and negatively impacting user experience.

    These challenges mean that basic A/B testing tools often aren’t enough. You need expert developers who understand the intricacies of your site’s architecture—and that’s where Fabric Analytics comes in.

    Our Advanced Approach: Leveraging Mutation Observers

    One of the key techniques we use to manage the complexities of modern web frameworks is the implementation of Mutation Observers. Mutation Observers are a powerful tool that allows us to monitor changes to the DOM (Document Object Model) in real-time, which is particularly important for sites built with frameworks like React, Angular, and Vue.js.

    Here’s how we use Mutation Observers to enhance our A/B testing:

    1. Tracking State Changes: Mutation Observers enable us to detect and respond to changes in the application state, which is critical for accurately measuring user interactions on SPAs. This ensures that our tests reflect the true behaviour of your users, even as the underlying state of the application evolves dynamically.
    2. Monitoring Component Re-renders: In frameworks like React and Angular, components can re-render based on user actions or state changes. Mutation Observers allow us to monitor these re-renders in real-time, ensuring that our tests account for these dynamic changes and apply modifications precisely when and where they’re needed.
    3. Ensuring Data Integrity: By using Mutation Observers, we can ensure that the data we collect during tests is accurate and reflects the current state of the application. This level of precision is essential for making informed decisions that will positively impact your conversion rates.

    Why Choose Fabric Analytics?

    At Fabric Analytics, we don’t just conduct A/B tests; we solve complex problems. Our team’s expertise in advanced web technologies, combined with our use of sophisticated techniques like Mutation Observers, ensures that your tests are both reliable and impactful.

    We provide:

    • Custom Implementation: Tailored testing solutions that fit the unique needs of your website, bypassing the limitations of generic tools.
    • In-depth Technical Expertise: A team that understands the complexities of modern web frameworks and knows how to work within them.
    • Advanced Testing Scenarios: The ability to handle complex user flows and interactions, delivering insights that drive real results.
    • Scalable Solutions: Testing approaches that can grow and evolve with your site, ensuring long-term success.
    • Accurate Data and Analysis: In-depth analysis that transforms raw data into actionable insights.

    When you choose Fabric Analytics, you’re choosing a partner who understands the intricacies of modern web development and is equipped to tackle the challenges of advanced A/B testing. We help you go beyond surface-level optimisations, providing the insights and expertise you need to truly elevate your CRO program.

    —

    Ready to elevate your CRO program with sophisticated A/B testing? Contact us today to learn how Fabric Analytics can help you achieve your goals.

  4. Google’s New Tools: Refining First-Party Data Strategies and Their Impact on GA4

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    Google’s recent updates—Tag Diagnostics and a streamlined Consent Management Setup—aim to bolster first-party data strategies across Google Ads, Google Analytics (GA4), and Google Tag Manager (GTM). While these tools bring significant improvements, there are some nuances and challenges to consider, especially for those who have been working with Tag Diagnostics for a while and are familiar with the complexities of setting up Consent Mode. Let’s explore these tools’ practical implications and how they affect your GA4 implementation.

    Tag Diagnostics: A Mixed Bag of Benefits and Limitations

    Tag Diagnostics isn’t entirely new; many users have been familiar with it for several weeks or even months, particularly those who first encountered it in Google Tag Manager (GTM) before seeing it in GA4. The tool’s primary function is to flag potential issues in your tagging setup, such as missing tags or misconfigured events. However, while the concept is solid, the execution hasn’t been flawless.

    • Accuracy Issues: One common experience with Tag Diagnostics is its occasional inaccuracy. For example, it might flag certain pages as missing GTM, only for users to find that GTM is indeed present when they manually check. These false positives can be frustrating and may lead to unnecessary troubleshooting, which is a drawback for businesses relying on precise data to inform their strategies.
    • Ongoing Value: Despite these imperfections, Tag Diagnostics still offers value by providing a centralised view of your tagging health. For GA4 users, it can serve as a helpful tool to ensure that most tagging issues are caught early, even if it occasionally requires manual verification. As Google continues to refine this tool, we can expect improvements in its accuracy and reliability.


    Consent Management Setup: Streamlining a Critical Process

    The new Consent Management Setup is a welcome addition, especially for businesses that need to navigate the complex landscape of data privacy regulations like GDPR and CCPA. While many companies have developed robust processes for setting up Consent Mode, this tool aims to make the process even more accessible and less technically demanding.

    • Easing the Setup Process: Even for those with established processes, having a more integrated and user-friendly setup within GA4 and GTM is beneficial. The streamlined approach reduces the complexity of deploying consent banners and managing consent mode, which can save time and reduce the likelihood of errors.
    • Limited CMP Integration: A notable limitation is the current integration with only three Consent Management Platforms (CMPs): Cookiebot by Usercentrics, iubenda, and Usercentrics. While these are among the more popular CMPs, the narrow selection might be disappointing for businesses using other platforms. However, since you’ve worked with all three CMPs, this integration should fit seamlessly into your existing workflows. There’s hope that Google will expand this list over time, offering greater flexibility and choice for businesses.


    The Impact on GA4 Implementation

    For GA4 users, these tools are important steps forward, though they come with caveats:

    1. Enhanced, But Imperfect, Data Accuracy:
      • Tag Diagnostics plays a crucial role in maintaining the integrity of your GA4 data, even if it sometimes requires manual checks to confirm its alerts. The tool can help you catch most issues before they affect your data quality, which is essential for making accurate, data-driven decisions.
    2. Simplified Compliance, with Room to Grow:
      • The Consent Management Setup should make it easier to maintain compliance with privacy regulations, reducing the technical burden on your team. While the current CMP options are limited, they include some of the most widely used platforms, which should cover the needs of many businesses. For GA4 users, this means you can implement and manage consent more efficiently, ensuring that your data collection remains both compliant and effective.
    3. Looking Ahead:
      • As Google continues to refine these tools, it’s likely that we’ll see improvements in accuracy for Tag Diagnostics and an expanded list of CMP integrations for Consent Management Setup. Staying up to date with these developments will be key to maximising the benefits for your GA4 setup.


    Google’s new tools, while promising, are not without their challenges. Tag Diagnostics offers a useful, if occasionally imperfect, way to ensure your tagging is accurate across GA4 and GTM. Meanwhile, the Consent Management Setup simplifies the complex task of managing user consent, though its utility is somewhat limited by the current number of integrated CMPs.

    For businesses already working within GA4, these tools provide valuable enhancements, even if they require some manual oversight or adaptation. As Google refines these features, the hope is that they will become even more robust, offering greater accuracy and flexibility in managing first-party data strategies.

  5. Checkout Extensibility upgrade – July 2024

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    Executive Summary:

    Shopify are deprecating the checkout.liquid theme file for the Information, Shipping and Payment pages on 13th August 2024 (with other areas to follow in August 2025)

    Existing customisations and integrated checkout tracking on these pages will no longer function after this date. This will not impact how shopify works, but any additional third party tracking and how that data is collected will be affected. When a user rejects marketing or analytics cookies, Shopify will not fire any tracking in the checkout, whether it sets cookies or not. This has serious impacts on any required tracking or tools such as Google Ads that use cookieless pings to model key metrics back into the tool.

    It’s imperative you review your setup ASAP

    What is the announcement?

    August 13, 2024 is the deadline to upgrade from checkout.liquid to Checkout Extensibility for the Information, Shipping, and Payment pages. Checkout.liquid is deprecated and has not been updated with new functionality since 2021. With ever changing regulations worldwide, including the introduction of card industry rules under PCI DSS v4, checkout.liquid is less secure than Checkout Extensibility, and they will discontinue its support.

    Checkout extensibility overview

    Future of ecommerce overview  

    Why is checkout.liquid being deprecated?

    Customising the Shopify checkout via checkout.liquid is typically complex and time-intensive, requiring advanced coding knowledge. Checkout.liquid customisations are often impacted by upgrades and, in some cases, result in poor checkout performance and a substandard buyer experience. They can also be problematic for security reasons.

    One other additional factor to this change was in August 2022, when a conflict with Google Tag Manager in the theme code caused a 12 hour Shopify checkout global outage.

    Shopify has been seeking to ensure checkout stability and performance whilst enabling the meaningful addition of new capabilities and functionality. As such, it has invested in Checkout Extensibility, a suite of apps and tools that make it easier to customise the Shopify checkout and build bespoke checkout experiences. Checkout Extensibility is secure, code-free, app-based, upgrade-safe and higher-converting. It also integrates with Shop Pay, which means, for the first time ever, express checkout can be customised.

    Crucially, Checkout Extensibility replaces the need for checkout.liquid.

    How will checkout extensibility impact your tracking?

    Despite Shopify positioning this as ‘no change’ to how tracking will work it severely impacts your ability to pass data into all media tracking e.g Google Ads, Meta and GA4)

    The guidance and the Shopify interface says that your pixels (where tracking scripts sit in Checkout Extensibility) will always run. (see below screen grab).

    However, this is incorrect as your tracking script will not run if a user rejects either marketing or analytics cookies. Blocking any tracking when a user rejects these cookies prevents technology such as cookieless pings, these are used by Google tools to model key metrics when a user opts out of cookies. This is a global issue and will continue to impact tracking for all people who’ve upgraded to checkout extensibility.

    Why are shopify doing this with tracking?

    It is unknown why they aren’t allowing any cookieless tracking to fire from their platform. However, Shopify is moving to Checkout Extensibility for several reasons:

    Enhanced Security: The new framework is designed with better security features to protect both merchants and customers.

    Scalability: Checkout Extensibility allows for a more scalable solution, accommodating growing businesses and increased traffic more effectively.

    Improved Customization: The new system offers more robust and flexible customization options, enabling developers to create more sophisticated and tailored checkout experiences.

    Future-Proofing: By adopting modern technology standards, Shopify aims to future-proof its platform, ensuring it remains relevant and capable of supporting new features and improvements.

    What Does It Mean for You?

    You will need to review the following:

    Action Required: You need to migrate your checkout customizations from checkout.liquid to the new Checkout Extensibility framework before the August 13, 2024 deadline.

    Learning Curve: There will be a learning curve as you familiarize yourself with the new framework and its capabilities.

    Opportunities for Improvement: The new system provides opportunities to enhance and innovate your checkout process, potentially improving customer experience and conversion rates.

    Support and Resources: Shopify will likely offer support and resources to assist with the transition, including documentation, tutorials, and possibly migration tools.

    You’ll also need to QA your existing marketing tags to ensure everything works as expected.

    What to do next?

    • Audit how your tags are implemented on checkout extensibility
    • Review turning off the privacy API and using an alternative solution to continue to use cookieless pings for Google Marketing Platform
    • Review using OneTrust (or similar) alongside GTM to ensure this works as expected

    If you’re unsure of your current status or how to complete these steps feel free to email data@fabric-analytics.com and we can help.

    How can Fabric help?

    At Fabric Analytics we can provide different levels of support to ensure you’re fully ready for these new changes.

    As we work on a transparent hourly based model, reach out to us and we can support with any of your needs.

    If you need support reviewing your third party tracking from a custom checkout.liquid instance to Checkout Extensibility, please contact us to find out more about how our team of Experts can help you.

    As one of the most experienced tracking and data agencies in the ecosystem, with a first-class team of experts and developers, we are perfectly positioned to consult on your bespoke requirements and implement these.

    Developer Resources

    Here are a list of Shopify web URLs that verify the details about the transition from checkout.liquid to Checkout Extensibility:

    1. Shopify Developer Documentation: Checkout Extensibility
    2. Shopify Community: Checkout Extensibility Announcement
    3. Shopify Help Center: Migrating from checkout.liquid
    4. Shopify Plus Blog: Secure and Scalable Checkout
    5. Shopify Developers Blog: Customizing Checkout

    These URLs provide verification and further details about the transition, including the reasons behind it, the impacts of missing the deadline, and the benefits of the new Checkout Extensibility framework.

  6. Consent Mode v2 – what does it mean for you?

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    Executive Summary:

    Google has unveiled a significant update, emphasising the need for strict compliance among website owners who use Google Marketing Products. This encompasses a range of tools such as Google Ads, GA4, Floodlights, and various other Google tags.

    This change is particularly crucial for businesses that engage with users in the European Economic Area (EEA) & United Kingdom, as adherence to these new guidelines will become mandatory for effective retargeting and audience development within these regions starting 7th March 2024.

    Taking action on these updates is critical; inaction will lead to a considerable reduction in data collection, efficacy of utilising Google’s marketing tools for media buying, audience targeting, and retargeting within the European Economic Area and United Kingdom.

    Starting 7th March 2024, inaction will significantly disrupt conversion tracking, audience building and remarketing.

    What is the announcement?

    Google announced the launch of Consent Mode v2, a significant update to its web and app advertising framework. This new version is designed to ensure compliance with the latest privacy regulations and address users’ expectations regarding online privacy. Consent Mode v2 introduces enhanced features for managing user consent, particularly in relation to Google’s advertising and analytics services.

    Consent Mode overview

    Content Mode technical documentation

    What is Consent Mode?

    Consent mode is a mechanism introduced by Google for Tag management platforms to work alongside CMP’s (cookie management platforms) or gtags to respect a user’s privacy.

    It’s a method that ensures the consent signals you gather are automatically conveyed to Google’s web and app advertising networks. As a result, Google’s tags change their behaviour to accommodate these preferences.

    Google uses this data to enable conversion modelling to recover lost conversions.

    This allows marketers to boost the quality of bidding algorithms and measurement capabilities.

    What is new with Consent Mode v2?

    Consent Mode v2 adds two additional parameters: ad_user_data and ad_personalization,

    which are Google-specific and dedicated for audience building and remarketing use cases.

    Without these two additional characteristics, it will be impossible to develop targeted

    audiences, perform personalised advertising on Google Ads or measure performance in

    the EEA and United Kingdom.

    There are 2 versions of consent mode:

    • “Advanced Consent Mode” covers cookieless pings. Even if consent is not granted, data is sent to Google.
    • “Basic Consent Mode” blocks tags from firing altogether when relevant consent is not granted.

    You will need to send the relevant consent signals if GA4 data is being used to feed Ads audiences through the GA4/Ads integration.

    Google Consent Mode v2 is fully operational. If it is not implemented, the negative effects for advertisers will appear from 7th March 2024.

    What does this mean for you?

    Without Consent Mode v2, no data about new EEA users will be captured by your advertising platforms (Google Ads, GA4, etc.) after March 2024. This will affect measurement and reporting in this region, along with your audience lists and remarketing disabling the ability to run personalised advertising.

    Your bidding algorithms will run based on inaccurate and incomplete data, and your budget will be spent much less effectively.

    For example, if you’re running a Maximise Conversions campaign with a target CPA, it is important that conversions are measured as accurately as possible for the algorithm to function and bid effectively. When fewer conversions are registered (without Consent Mode v2), the strategy will under-evaluate some opportunities, leading to inaccurate bidding and budgets being used in less profitable ways.

    Below is a visual representation of the impact of implementing different consent mode versions:

    Which version of Consent Mode v2 should I implement?

    1. Recommended: for full ads / audience / remarketing capabilities, you need to use “Advanced Consent Mode” with all four parameters in place.
    2. If you want to block tags from firing when consent is not granted and still make something out of Ads, you need to use “Basic Consent Mode”.
    3. You may also decline to utilise consent mode entirely, in which case Ads will be restricted – no conversion or audience features would be available. GA4 will continue to function normally; the Ads integration will be constrained.

    How do I implement Consent Mode v2?

    The first step is to have a consent banner on your website that respects user choices. The

    easiest way to get started with this is to choose a Google Certified CMP partner. Fabric Analytics preferred CMP is onetrust

    Once you have a compliant consent banner in place, Consent Mode v2 can be implemented.

    Update your tagging infrastructure in your tag management system to reflect the Google

    Consent v2 requirements. Fabric Analytics can offer consent mode implementations and all

    the support and documentation needed for you to start measuring effectively.

    What to do next?

    • Audit how your tags are implemented on your website (e.g. GTM, Hard Coded)
    • If required, setup a CMP on your website (e.g. Cookie Bot)
    • If required, setup your tag management system to reflect the Google Consent v2
    • requirements

    Developer Resources

    • App
    • Offline
      • For manual data uploads (not via API/SDK), a Term of Services consent attestation opt-in will be required (and will launch in the product UI in early Q1 2024).

  7. Unveiling the Big Mystery: Google BigQuery and its Fantabulous Benefits!

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    Howdy, data enthusiasts! Today, we’re going to embark on a thrilling journey into the land of Google BigQuery, where data reigns supreme and insights flow like a chocolate fountain at Willy Wonka’s factory. Get ready to have your minds blown as we unravel the mysteries of this bewitching analytics tool and discover its glorious benefits!

    What on Earth is Google BigQuery?

    Imagine a vast repository of data, teeming with information from every corner of the digital universe. Now, take that colossal data warehouse, sprinkle some magic Google dust on it, and voila! You’ve got yourself Google BigQuery, the quintessential data analytics platform.

    Google BigQuery is a cloud-based, serverless data warehousing and analytics solution that lets you store, analyze, and glean insights from mind-bogglingly enormous datasets. It’s like having a supercomputer at your fingertips, eagerly waiting to crunch numbers and reveal hidden patterns. It’s the ultimate geek’s paradise!

    Benefits Galore – Prepare to Be Amazed!

    Lightning-Fast Queries: Have you ever waited for a slow query to finish, only to fall asleep and dream about bunnies? Well, BigQuery is here to save the day! With its supercharged processing power and distributed architecture, queries run faster than a cheetah on rollerblades. Say goodbye to impatience and hello to instantaneous results!

    No Infrastructure Hassles: Picture a world without worrying about servers, provisioning, or software updates. Sounds like a utopian paradise, right? BigQuery makes it a reality! It’s a serverless wonderland where you can focus solely on data analysis while Google takes care of the infrastructure behind the scenes. So sit back, relax, and let BigQuery do the heavy lifting.

    Scalability with a Capital ‘S’: Need to process a gazillion rows of data? No problemo! BigQuery can effortlessly handle petabytes of information, making it ideal for businesses with insatiable appetites for data. As your needs grow, BigQuery expands magically, like a bottomless bag of popcorn at the movies.

    Cost-Effective Data Storage: We all love a good bargain, and BigQuery delivers on that front too. With its storage model based on consumption, you only pay for the data you store. No need to worry about upfront costs or excess baggage. It’s like shopping for data warehousing on a 90% off sale—simply marvelous!

    Seamless Integration with Other Google Services: If you’re a fan of the Google ecosystem (and who isn’t?), BigQuery is your golden ticket. It plays harmoniously with other Google services like Google Cloud Storage, Data Studio, and even AI and machine learning tools. It’s like assembling the Avengers of data analytics—all your favorite tools working together for the greater good!

    So there you have it, dear readers—a whimsical tour through the enchanting land of Google BigQuery. With its blazing speed, scalability, cost efficiency, seamless integration, SQL magic, and advanced analytics capabilities, BigQuery is a formidable ally in your quest for data-driven enlightenment.

    Advanced Analytics: BigQuery is not just about querying—it’s a treasure trove of analytical prowess. With its built-in machine learning capabilities, you can level up your analysis game with predictive modeling, anomaly detection, and clustering. It’s like having a crystal ball that can reveal hidden patterns and insights from your data.

    So put on your analytical hats, grab your magnifying glasses, and embark on a data adventure with BigQuery. Embrace the quirks.

  8. The first 100 days of Fabric Analytics: Joy, Fear & an expense account MIA

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    It’s been 100 days since we opened our doors at Fabric Analytics and, to paraphrase the old saying, “Time flies when you’re relentlessly upgrading analytics implementations for some of the highest performing teams in commerce.”

    The first 100 days is a period that’s been fetishished in recent times amongst the glossy ‘airport paperback’ genre of personal and professional development, but with our first trading quarter now behind us, it seems like an appropriate moment to take stock of how it’s all going. In the absence of a boss, I’m conducting my own self-review and sharing it with you, dear readers. So, let’s dive in and explore the journey of these initial months; what have been the big hitters?

    Personal attention gets better outcomes.
    One of the aspects I love most about running Fabric Analytics is the ability to provide personal attention to each client account. We have a team of seasoned professionals, with an average of more than 10 years of experience, who bring a wealth of knowledge and expertise. Our clients have often been underserved in the past, and we are determined to deliver a level of service that ensures they capture the full value they deserve.

    It’s rewarding to do things better.
    Vince Lombardi, the renowned American football coach, once said, “The quality of a person’s life is in direct proportion to their commitment to excellence, regardless of their chosen field of endeavor.” This quote resonates deeply with me as I navigate the challenges of managing a fledgling business in a category where ‘good enough’ is often the benchmark. While it can be intimidating to bear the responsibility of meeting the high expectations our clients have of us at Fabric, the opportunity to really move things forwards for their business brings a tremendous sense of purpose and energy to our work. I am driven to make a lasting impact and uphold the highest standards of excellence in our industry and I’ve been heartened by the hugely positive response to our work so far.

    Your support network makes you.
    Running a new business is not a solo endeavor! I am fortunate to have huge support from outside Fabric with family and friends. Their belief in me and what we are building have been invaluable. Building a thriving business requires a strong support system, and I am grateful to have it in abundance.

    Business admin is in equal parts tedious and fascinating.
    From payroll and pensions to office rental and dealing with HMRC, there’s been quite a learning curve! Whilst close to two hours on the phone to HMRC one week chasing a VAT gremlin wasn’t an obvious highlight, each task adds to the breadth of knowledge required to run a successful agency. While it can be overwhelming at times, I’m embracing these challenges as opportunities for growth and improvement.

    Financial accountability is more of a thrill than it sounds.
    As the MD, I have assumed the responsibility of the financial performance of the agency. This heightened level of accountability has certainly sharpened the mind! Whilst I’ve owned commercial performance for well over a decade, nothing makes you as deliberate in your decision making as being the one ultimately holding the purse strings and answering to stakeholders! There have been moments of nostalgia for the corporate expense account, but it pales in comparison to the thrill of building a financially sustainable business from the ground up.

    Focus on the future, learn from the past.
    The first 100 days have provided a glimpse into the joys and challenges of running a new business. We have made significant strides, but it seems almost indulgent to be dwelling on what’s behind us already, as our optimism and determination to propel our clients forward is just spooling up! Together with my exceptional team we are embracing the future with enthusiasm and determination, but I’m going to make sure we also make time occasionally to pause and look back at what we’ve done so that we’re always learning and we make sure to enjoy the journey.

    I’d like to thank our clients, our team and our partners for making this journey so special so far!

    Forwards!

  9. The Rise of Predictive Analytics: The Future of Business Intelligence

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    Predictive analytics has emerged as one of the most powerful tools in the world of business intelligence. By leveraging large amounts of data and advanced algorithms, predictive analytics enables companies to make informed decisions and anticipate future outcomes with a high degree of accuracy. The rise of predictive analytics has been driven by several factors, including the proliferation of big data, the growth of cloud computing, and the increasing availability of advanced analytics tools.

    The benefits of predictive analytics are many, and they extend to a wide range of industries and applications. For example, in the retail industry, predictive analytics can be used to optimize inventory management, predict customer buying patterns, and personalize marketing campaigns. In the financial sector, predictive analytics can be used to detect fraud, manage risk, and optimize investment strategies. In the healthcare industry, predictive analytics can be used to improve patient outcomes and streamline operational processes.

    The future of business intelligence lies in predictive analytics, and companies that embrace this technology will have a significant competitive advantage. Predictive analytics is no longer the domain of data scientists and mathematicians. With the rise of cloud-based analytics tools, companies of all sizes can now leverage predictive analytics to gain a competitive edge. By leveraging the power of predictive analytics, companies can turn their data into actionable insights and drive growth and innovation.

    In conclusion, the rise of predictive analytics represents a major shift in the world of business intelligence. By harnessing the power of big data and advanced algorithms, companies can now make informed decisions and anticipate future outcomes with unprecedented accuracy. Whether you are a large corporation or a small business, the future of business intelligence lies in predictive analytics. Embrace this technology, and stay ahead of the curve!

  10. Taxonomy / Naming Conventions – fool proof guide

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    Taxonomy / Naming Conventions… not the sexiest topic but one of the most important..

    Taxonomy and governance on marketing data provide structure, consistency, and reliability to your data management and analysis efforts. They enhance data integrity, enable cross-channel insights, improve collaboration, and support efficient decision-making. By implementing these practices, Lotus can leverage the full potential of their marketing data to drive growth and success.

    There are many benefits to a clear taxonomy/naming conventions which include:

    • Consistency and Standardisation
    • Data Integrity and Quality
    • Data Integration and Cross-channel Insights
    • Scalability and Efficiency
    • Collaboration and Communication
    • Futureproofing and Adaptability

    Taxonomy naming conventions are an essential part to global reporting and consistency. We’ve developed a clear process to apply that will allow governance and consistency.

    Stage 1: Define Objectives and Scope

    • Define the objectives of your taxonomy and naming convention. What specific goals do you want to achieve with GA4?
    • Determine the scope of your taxonomy, considering the size and complexity of your business, and the number of entities you need to track.

    Stage 2: Identify Key Dimensions and Metrics

    • Identify the key dimensions and metrics that are relevant to your business. These could include customer segments, product categories, geographic regions, channels, campaigns, or any other data points you want to track.
    • Prioritise the dimensions and metrics based on their importance and relevance to your business goals.

    Stage 3: Establish Naming Conventions

    • Develop a standardised naming convention for each dimension and metric. Ensure that the conventions are consistent, clear, and easily understood by all stakeholders.
    • Consider including prefixes or codes to categorise different types of dimensions or metrics, which can help with organising and filtering data.

    Stage 4: Document and Communicate the Taxonomy

    • Document the finalised taxonomy and naming convention in a comprehensive guide or document. Include definitions, examples, and guidelines to ensure consistent implementation across the organization.
    • Communicate the taxonomy to all relevant stakeholders, including analysts, marketers, and developers. Conduct training sessions if necessary to ensure everyone understands the conventions and their importance.

    Stage 5: Implement and Validate

    • Implement the taxonomy and naming convention in GA4, making sure to follow the established guidelines and conventions.
    • Validate the implementation by monitoring and reviewing the data collected. Ensure that the data is organized and structured correctly and aligns with your predefined objectives and metrics.
    • Continuously review and refine the taxonomy as your business evolves, ensuring it remains relevant and effective.

    Developing a taxonomy and naming convention is an iterative process, and it may require adjustments based on feedback and changing business needs. Regularly revisit and update your taxonomy to keep it aligned with your evolving business requirements.