4 min read

Google Analytics (GA4) Foundation and use-cases

Google Analytics (GA4) Foundation and use-cases
Earlier this year, Yann and I had the privilege of hosting a compelling global webinar that centered around Google Analytics 4. The significance of this topic has grown exponentially, particularly due to the impending halt of data collection by Universal Analytics in just 33 days, starting from July 1st. It's noteworthy that the majority of teams across the globe have either successfully transitioned to GA4 or are actively engaged in the migration process.In this post, I will provide a quick summary of the webinar and talk about specific details on leveraging BigQuery to solve some advanced analytics use-cases using GA4 data.

During the webinar, we extensively discussed the compelling reasons for companies to adopt GA4, along with practical guidance on how to initiate the process while leveraging your existing account through the concept of "dual-tagging." Moreover, we delved into exploring advanced features like Predictive Metrics and the seamless export of data to BigQuery.

Core benefits of GA4

  • Unify and deduplicate data across devices and platforms using both your 1st party data as well as Google’s to understand customer journeys across devices
  • Derive business insights more quickly with the power of Google’s Machine Learning behind your data
  • Action on those insights seamlessly to optimize your marketing with Google Ads, Google Marketing Platform and other partners
  • Invest in a future-focused and privacy-first platform that uses Google’s industry-leading approach to privacy
From my perspective, the paramount business function addressed by GA4 revolves around its ability to seamlessly integrate and harmonize both app and web data through event-based data collection.
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You can implement Events automatically and with custom options:

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From a reporting perspective, you can use GA4 to Derive powerful insights by leveraging an updated user interface with robust reporting capabilities

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Now, let's dive into one of my personal favorite topics that I discussed: harnessing Google's advanced modeling techniques to facilitate the discovery of insights and detect anomalies more effectively.
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Out of the Box
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You can Reach predictive audiences in Google Ads. Analytics will now suggest new predictive audiences that you can create in the Audience Builder. For example, using Purchase Probability, GA4 will suggest the audience “Likely 7-day purchasers” which includes users who are most likely to purchase in the next seven days. Or using Churn Probability, GA4 will suggest the audience “Likely 7-day churning users” which includes active users who are not likely to visit your site or app in the next seven days.

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In the past, if you wanted to reach people most likely to purchase, you’d probably build an audience of people who had added products to their shopping carts but didn’t purchase. However, with this approach you might miss reaching people who never selected an item but are likely to purchase in the future. Predictive audiences automatically determine which customer actions on your app or site might lead to a purchase—helping you find more people who are likely to convert at scale.

In addition to building audiences, you can also use predictive metrics to analyze your data with the Analysis module. For example, you can use the User Lifetime technique to identify which marketing campaign helped you acquire users with the highest Purchase Probability. With that information you may decide to reallocate more of your marketing budget towards that high potential campaign.

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And finally, by exporting the data into Google BigQuery, you unlock a realm of possibilities for advanced analytics use-cases. One such example is Customer Segmentation, where you can harness the power of CRM and other data sources to gain deeper insights. Additionally, you can enhance your analysis by combining loyalty, CRM, and offline sales data with GA4, enabling you to calculate Customer Lifetime Value (CLV) more accurately.

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In my upcoming blog post(s), I will delve into the intricacies of exporting GA4 data into BigQuery tables and demonstrate how you can leverage the capabilities of GCP Machine Learning models in Vertex AI. These powerful models will enable you to create sophisticated predictive models that can be utilized to supercharge your marketing campaigns.

In this series, I will explore how to leverage the immense potential of GA4 data and harness the capabilities of Google BigQuery to supercharge your marketing strategies. 📈💡

Here's what you can expect from this series:

  • 🔍 Deep dive into GA4 data: Gain a thorough understanding of the wealth of insights GA4 provides and learn how to extract valuable data to fuel your marketing analytics initiatives.
  • ⚙️ Unlock BigQuery's potential: Discover how to seamlessly integrate GA4 data into Google BigQuery and unleash the full power of its advanced analytics features.
  • 📊 Advanced marketing analytics use-cases: Explore practical examples and real-world scenarios where you can leverage GA4 data in BigQuery to drive data-driven decision-making and achieve remarkable marketing outcomes.

Stay Tuned!