With Google announcing that they will be sunsetting Universal Analytics (GA3) in July of 2023 for the standard version and October of 2023 for the 360, it is now apparent that businesses will need to make their migration to GA4 by that date. However, businesses that are not migrating to GA4 in the present are falling far behind. Here are the broad reasons why your business should make this transition as soon as possible.
Right now, you have one year to gain an understanding of GA4 while having the advantage of running your current analytics set up concurrently. You should take this one-year period to learn the ins and outs of the new GA4 platform while you can still analyze data with your current set up. This will help you avoid the pressure of setting up the platform last minute. You will then have more time to think about the optimal set up of your new GA4 property that benefits you and your team in the long-term. This option is certainly preferable to rushing to generate reports and creating a structure that leaves your business in technical debt.
Right now, every day that you don’t have GA4 set up is a day that your company is losing important and convenient analytics data. What many don’t know about Google ending Universal Analytics is that after 6 months from July 2023, Google says that they will be shutting down the platform entirely. This means that all your historical data from Universal Analytics will be lost. While you can export the data for safekeeping (as you should), it would be difficult to transform the data in a way that would be usable in GA4. Furthermore, it would be challenging to transform much of that data in a way that is useful for your business. Therefore, it is ideal that GA4 data collection is set up now so that you can have the historical data from the past year available to you. This will also help continue to improve the next point.
Right now, every day you don’t use GA4 is a day you are not taking advantage of Google’s machine learning technology. This includes the addition of predictive metrics, Google’s data-driven attribution models, and Google insights which allows Google to provide you insights based on certain questions that you ask. This data is based on machine learning, meaning that GA4 needs enough data to train, validate, and test its models before deploying them to your property. This means that the more data that you have, the better the platform will be able to work to provide the predictive and decision insights you need. It’s also worth noting that there is a high chance that Google is working on adding more predictive metrics to GA4 as we speak.
Moving on to the new GA4 platform can be nerve-wracking for many businesses, especially in figuring out how to structure their analytics and reporting. If you are looking to migrate to the new GA4 platform and improve your analytics infrastructure, please reach out to email@example.com.