Are you starting to lose valuable data in GA4?

If you have GA4 implemented, you are probably starting to lose historical data. With the mandatory switch from Universal Analytics (UA) to Google Analytics 4 (GA4) that happened around 14 months ago, many businesses are now at the point where data retention limits are becoming a critical issue. If you haven’t thought about how this might affect your long-term data needs, now is really the time to do so.

Understanding data retention in GA4

GA4’s data retention policy determines how long your user-level and event-level data is stored before it is automatically deleted. By default, you can retain this data for either 2 months or 14 months. Once this period is over, any user-level or event-level data older than your chosen retention period will be gone forever.

It’s important to highlight that this limitation only affects user-level and event-level data. Aggregated data, such as total sessions, page views, and bounce rates, remains available in your GA4 reports indefinitely. However, the loss of detailed user or event interaction data could significantly impact your ability to conduct in-depth analyses, particularly for businesses that rely on long-term tracking.

For those using GA4 360, the enterprise version of GA4, the retention period can be extended beyond 14 months. If you have GA4 360, you might not need to worry about this just yet. But for standard GA4 users, the clock is ticking.

What does this mean for your business?

Let’s dive into some specific examples to understand the impact of losing user-level and event-level data.

Example 1: Lead generation business

Consider a lead generation business that tracks individual user interactions to monitor the effectiveness of marketing campaigns and lead nurturing strategies. Imagine you have set up custom events to track when users download a whitepaper, attend a webinar, or fill out a contact form. If you want to analyse the behaviour of users who engaged with your content 18 months ago, you would find that the specific events and user paths are no longer available in GA4. This loss could hinder your ability to see the complete customer journey and optimise your strategies based on long-term data.

Example 2: Ecommerce business

For an ecommerce business, let’s say you’re tracking detailed user interactions, like add-to-cart events, product views, or specific promotional click-throughs. These events help you understand individual customer behaviour and the effectiveness of your promotional campaigns over time. If you want to revisit the purchasing behaviour of customers who interacted with your store during last year’s holiday season, you would find that the detailed event data has been deleted if it exceeds the 14-month retention period. This can limit your ability to analyse purchasing patterns and refine your marketing efforts based on past successes.

How to avoid data loss: take control of your data

To prevent losing valuable data due to GA4’s retention limitations, you’ll need to proactively store your data independently. Here are two effective methods:

Manual export using GA4 reporting features

You can manually export your data using GA4’s reporting features, and the good news is that you can start this process right away. For instance, you could immediately export data from summer 2023 to ensure it’s almost completely saved before the 14-month retention period hits. This approach gives you some breathing room while you consider more permanent data storage solutions. Although manual exports are straightforward, they can be time-consuming and might not capture the depth of data required for long-term analysis.

Dumping data into a data warehouse

A more comprehensive solution is to set up automatic data exports to a data warehouse like BigQuery or Microsoft Azure. GA4 offers a seamless integration with BigQuery, allowing you to continuously transfer data to the warehouse. However, be aware that this connection is not retroactive; it won’t capture historical data before the link was established. To fully protect your data history, some additional setup and coding may be necessary.

Additionally, while BigQuery is relatively affordable for data storage, be cautious about data processing costs, which can escalate if you’re handling large datasets. Carefully planning your data exports and processing queries is essential to avoid unexpected expenses.

Need help navigating GA4?

Navigating GA4’s data retention limitations can be challenging, but you don’t have to do it alone. If you need assistance in setting up data exports or finding the right solution for your business, we’re here to help. Reach out to us, and we’ll guide you through the process, ensuring your valuable data is preserved and accessible for future analysis.