How to Save Your Historical Google Analytics Data Before It’s Too Late


    Don’t Lose Your Historical Google Analytics Data

    The Business Case for Acting Before the July 1st, 2024 Deadline

    Your business’s website is probably utilizing Google Universal Analytics (GA3) to track and measure customer interactions, including ad clicks, page rankings, and purchase behaviors. Since its launch in 2012, GA3 has served as a reliable tool. But it won’t be around for much longer. GA3 is being deprecated, which means you’ll lose access to the Universal Analytics interface and API starting July 1st, 2024. To save the historical Google Analytics data you’ve been tracking and the analysis you’ve been performing, you’ll need to migrate to Google Analytics 4. If your IT team or marketing director hasn’t yet informed you about this transition, it’s crucial to proceed with migration to effectively retain your data.

    However, simply migrating is not enough to manage this transition effectively.

    Google has announced that all historical data from GA3 accounts will be deleted on July 1st, 2024. This means you will lose access to years of valuable business insights that are crucial for making strategic decisions and optimizing your online presence. Act now to save your historical Google Analytics data before it’s too late.

    Before we delve into how to save your historical Google Analytics data, let’s review some basic concepts and terms to better understand the situation.

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    Understanding the Basics of Google Analytics Data

    Business Insight: The Key to Strategic Decision Making

    Business insight is built on knowledge gained about a company’s performance, operations, and market conditions. That knowledge is derived from analyzed data. This actionable information empowers you to understand your customers, competitors, market dynamics, and business performance, allowing for informed decision-making and goal attainment. Your proprietary data is your recipe for success. Without it, your path forward is unclear.

    In the era of Artificial Intelligence (AI) and Machine Learning (ML), your data is what sets you apart. Proprietary data has assumed paramount importance for businesses. Analyzing vast data sets to derive actionable insights is not only standard practice, but essential for growth. Safeguarding data on customer interactions and purchases is imperative for future utilization, ensuring you’re prepared to leverage your company’s data assets effectively.

    The Financial Implications of Data Erasure

    We’ve established how vital data is to the health and success of your business. But what happens if you lose it? Data erasure, the permanent removal of data from a storage device or system, can significantly impact your operations. It jeopardizes your ability to:

    • Analyze past performance,
    • Identify patterns, trends, and opportunities,
    • Benchmark current performance,
    • Forecast future performance,
    • Report results and demonstrate value to stakeholders,
    • Ensure compliance with legal and regulatory requirements.

    The consequences of data erasure extend beyond financial losses; they include the loss of time and damage to your reputation. Data erasure not only deprives you of your company’s history and valuable information for its future, but also gives your competitors an edge. They’ll be able to plan effective budgets, avoid fines and penalties, and use their own historical data to make smart moves, to list just a few advantages.

    Google Universal Analytics (GA3): A Treasure Trove of Proprietary Data

    Google Universal Analytics (GA3), launched in 2012, is the third version of Google’s web analytics service. It allows you to collect, process, and report data from your website and other online channels. GA3 is a repository of proprietary data that aids in understanding your website’s performance, user behavior, conversion rates, and more. It answers questions such as:

    • How many visitors come to your website, and where do they come from?
    • Which ads, search engines, browsers, and countries did they use? When do they visit?
    • Which pages do they view, and how long do they stay?
    • What actions do they take?
    • What are their purchasing habits? How do they interact with your content? On which devices?
    • How do they respond to your marketing campaigns?
    • What’s your ROI?

    Google Analytics 4 (GA4): The Future of Analytics, Ready or Not

    Google Analytics 4 (GA4), Google’s most current analytics platform launched in 2020, represents the latest in Google’s web analytics services. It introduces a new way of measuring and analyzing website and app performance. GA4 is the future of analytics. It enables you to:

    • Track and measure website and app performance in one place,
    • Utilize machine learning and artificial intelligence for insights and recommendations,
    • Understand users throughout their lifecycle across various devices and platforms,
    • Create and customize reports and dashboards,
    • Integrate data with other Google products and services.

    Of course, there are tradeoffs for innovation. GA3 offered much more in terms of drill-down capability, allowing users to explore detailed, granular data. By contrast, GA4’s user interface is more simplified. Reaching the data you may be used to analyzing will require more work and added steps to document the same insights. Fortunately, there are supplementary tools you can use to extend GA4’s capabilities while preserving your GA3 data.

    The Shift from Universal Analytics to Google Analytics 4

    GA3 vs GA4: What It Means for Your Business

    GA4 sets a new standard for web and app analytics, designed to enhance your understanding of customers and optimize marketing efforts. Unlike Universal Analytics (UA) or GA3, GA4’s measurement model is based on events and parameters, not sessions and hits.

    So, if you’re used to running certain analytical measures daily, weekly, or monthly using sessions and visits to demonstrate growth, viability, or visibility, you may need to tweak your methods. Though this may seem like a step backwards, you can use this opportunity to explore new metrics and datasets.

    GA4 offers several features and benefits not found in UA or GA3, such as:

    • Cross-device measurement: GA4 tracks users across various devices and platforms, including desktop, mobile, tablet, and smart TV, providing a comprehensive view of customer journeys and behaviors,
    • Predictive analytics: GA4 employs machine learning to forecast users’ future actions and outcomes, allowing for targeted, personalized messaging and offers,
    • Deeper integration: GA4 integrates more seamlessly with other Google products and services, enhancing data leverage across channels and tools to optimize marketing performance and ROI.

    The End of Universal Analytics: Implications for Your Business Data

    While GA4 presents many advantages over UA or GA3, it also introduces challenges and risks for your business data. The primary concern is GA4’s lack of backwards compatibility with UA or GA3, meaning historical data cannot be imported from UA or GA3 to GA4.

    This lack of backwards compatibility is major. Here’s what it can mean for your business:

    • Loss of valuable insights: Historical data holds extensive information about customer behaviors, preferences, and trends,
    • Loss of continuity and consistency: Historical data serves as a baseline and reference for future data analysis and decision-making,
    • Loss of trust and credibility: Historical data is a testament to your expertise, authority, and reputation in your industry.

    How to Save Your Precious Past and Future Data in Google BigQuery

    Therefore, to save and safeguard your historical Google Analytics data and facilitate a smooth transition from UA or GA3 to GA4, you may want to consider migrating your data to Google BigQuery.

    BigQuery is a cloud-based data warehouse that allows fast, scalable storage, querying, and analysis of massive data volumes. By integrating UA or GA3 data with BigQuery, you preserve historical data and ensure constant access. You can also combine it with GA4 data and other data sources for comprehensive dashboards and reports.

    Some of the actions you can take with BigQuery include:

    • Create a project on the Google Cloud Platform and enable billing.
    • Establish a dataset in BigQuery and set access permissions.
    • Link your UA or GA3 property to BigQuery and configure data export settings.
    • Develop custom SQL queries to extract actionable insights.
    • Integrate BigQuery with Google Looker Studio for advanced data visualization.
    • Automate data imports and exports using Google Cloud Functions.
    • Implement and utilize machine learning models and BigQuery ML.
    • Combine GA4 data with other data sources for holistic analysis.
    • Enable real-time data streaming and set up data retention policies.
    • Create and share interactive dashboards.
    • Schedule regular data backups and secure storage for compliance.

    The Benefits of Using BigQuery and Looker Studio to Visualize Your Historical Google Analytics Data

    GA4 BigQuery Integration: Automated Analytics Data Storage and Machine Learning Opportunities

    A significant advantage of GA4 is its native integration with BigQuery, eliminating the need for manual linking as with UA or GA3.

    You can enable BigQuery integration in your GA4 property settings for automatic data export to BigQuery on a timely schedule, depending on your plan. This automation saves time and ensures up-to-date, accurate data.

    Combining GA4 and BigQuery allows you to unlock the advantages of artificial intelligence and machine learning. Additionally, combining GA4 and BigQuery unlocks advanced features like machine learning, streaming analytics, and data transformation.

    Real Life Example: Quiz Traffic Analysis

    Consider a scenario where a company offers a popular self-assessment quiz.

    With thousands of users taking the quiz monthly, the question arises: if the company increases traffic to this free feature through advertising, what would the ROI be? Is it worth the investment, or should they promote a paid assessment product instead?

    By leveraging tools like Google BigQuery ML and existing analytics conversion metrics, it was determined that an additional 5,000 quiz page visits could lead to an extra $10,500 in sales, based on average purchase revenue and predicted new purchases.

    At first glance, a 5,000 visit increase might seem modest. However, considering the quiz receives 100,000 visits annually, this seemingly modest 5% uptick in traffic represents a notable sales boost.

    This data-driven approach enables accurate ROI predictions, facilitating informed decision-making, execution based on insights, and continuous improvement over time. Such analysis underscores the importance of retaining historic data for informed decision-making and strategic planning.

    Why Google BigQuery is a Game Changer for Business Data Ownership

    Another benefit of using BigQuery to save and manage your Google Analytics data is that you gain full ownership and control over your data. Unlike GA3 or GA4, where your data is stored and processed by Google and subject to Google’s terms and policies, with BigQuery, you own your data and can decide how to use it, share it, and delete it. This gives you more flexibility and security and allows you to comply with data privacy and protection regulations, such as GDPR and CCPA.

    Owning your data with BigQuery means you decide how to use it.

    Furthermore, with BigQuery, you can access and analyze your GA4 data without any limitations or restrictions, such as sampling, aggregation, or retention. You can also export your GA4 data to other platforms and tools, such as Google Looker Studio, Google Sheets, or third-party BI solutions, and use them to create custom dashboards and reports that suit your specific business needs and goals. SQL queries and spreadsheets can be created to organize the data however it is needed.

    Google BigQuery and Google Looker Studio Integration: A Powerful Combination for Business Intelligence

    • Connect your GA4 and BigQuery data with other sources of data, such as CRM, social media, YouTube, e-commerce, and more, to create a single source of truth for your business intelligence,
    • Create interactive and dynamic dashboards and reports that display your key metrics and trends, and allow you to drill down into the details,
    • Share your dashboards and reports with your team, clients, or partners, and collaborate on data analysis and decision-making.

    Save Your Historical Google Analytics Data Now

    GA4 represents the future of analytics, so it is essential to be prepared for it. By migrating your data from GA3 and GA4 to BigQuery, and utilizing Looker Studio to visualize your data, you can save your historical Google Analytics data and gear up for what’s ahead.

    Additionally, you can take advantage of the features and capabilities that GA4 and BigQuery provide, such as cross-device measurement, predictive analytics, machine learning, data ownership, and more. If you choose to take our advice, you can employ the most advanced analytics technology to date, sharpening your competitive advantage in the marketplace.

    If you want help with migrating your data from GA3 or GA4 to BigQuery, or in creating dashboards and reports with Looker Studio, we recommend reaching out to us today. Time is running out!