GA360 is a great tool, and for the enterprises that can afford and justify the cost, probably the best analytics tool they can invest in. At the same time, many companies don’t have the budget to pay upwards of $150k for an analytics tool.
Google Analytics 4 (GA4) is not yet fully GDPR compliant. Google is working to make GA4 compliant with the GDPR, but it is a complex process that is still ongoing.
At Reflective Data, we built a solution that enables companies to use GA4 in the EU safely.
Google Optimize and Optimize 360 will no longer be available after September 30, 2023. Your experiments and personalizations can continue to run until that date. Any experiments and personalizations still active on that date will end.
In order to not lose your data, you should act on exporting it now!
Possible use cases for a data warehouse are virtually limitless and depend on what kind of business you run. In this article, I’m providing some of the more common ways together with examples of how to benefit from having a data warehouse.
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.
No doubt that Google Analytics is the most popular tool when it comes to website analytics. Even though it’s free for most users, it does have some serious limitations. In this article, we’re going to figure out what’s the best alternative to Google Analytics.
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!
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.
Data protection and privacy rules are getting tougher all over the world. This is especially true for the European Union and even more so for some specific industries. Including finance, medical and others that handle sensitive information about their users.
While Google Analytics has been making some improvements in the privacy area and is GDPR compliant, this is not enough for many businesses and industries.
At Reflective Data, we’re often working with companies that are under close monitoring of their regulators. To help them out, we’ve built custom solutions that allow storing Google Analytics within the European Union or sometimes even completely locally.
Using Google Analytics Parallel Tracking and a custom data pipeline for Shopify, we managed to get all necessary data in BigQuery for more advanced analysis and reporting.