Optimal GA4 Setup For High-Traffic Websites and Apps in 2024

Collecting close to or above 1 million events per day? Then you’ve probably realized that using the free version of GA4 you’re hitting several limitations around sampling and raw data export.

In this article, we’re going to explain some of the approaches you should be taking to make sure you get the most out of your valuable data without losing any of the valuable insights. Oh, and without having to upgrade to GA360.

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How to Avoid Google Analytics 4 [GA4] BigQuery Export Quota Limit of 1 Million Hits

While the new version of Google Analytics, the GA4, comes with the native BigQuery export feature available in the free version and some of the other quotas aren’t as tight anymore, GA4 still has a fair share of limitations we need to account for.

The limit I’m covering in this post is set on the BigQuery export. More specifically, the GA4 to BigQuery native export feature has a limit of 1 million hits per day. Luckily, there are some ways around it.

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Case Study: Building and maintaining a Data Pipeline and Data Warehouse for the Enterprise

At Reflective Data, we’ve worked with companies big and small. This means we have seen all levels of maturity when it comes to the infrastructure and knowledge around data pipelines and data warehouses.

Some of the most challenging projects have been enterprises with quite some infrastructure, legacy pipelines, and of course, opinions. Smaller businesses are just starting to adopt the concept of having all of their data stored in a data warehouse but many enterprises have been doing this for a decade!

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Measure Long-Term Metrics Like Customer Lifetime Value (LTV) Using Google Analytics

Long-term metrics like customer lifetime value (LTV) and churn can be so much more insightful and lead to better results when optimized for when compared to the more basic metrics like transactions or revenue. Yet, these metrics are often ignored or at least not involved in the analysis and optimization processes enough. One of the reasons is that it’s quite difficult to track them using common analytics and testing tools like Google Analytics and Optimize.

In this article, we are going to explore some of the ways we can leverage Google Analytics to track churn, LTV and other really useful metrics.

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