What’s the difference between Google Analytics and product analytics?

More than ever, organizations rise and fall on their ability to gather and leverage data. They need robust interpretation to implement practical changes across teams, departments, and the whole organization. 

But for data to be effectively leveraged, organizations need the right tools to gather the data they need. In product innovation, many organizations fall back on Google Analytics, which is focused on marketing analytics, over a product analytics solution. They use Google Analytics to gather data on user behavior- but the mismatch between what Google Analytics offers and what they need means that companies often fall short of leveraging their data for their directives. 

Google Analytics is a vital tool in its own right, but it’s designed for market analytics rather than product analytics. It’s designed for the early stages of user engagement by collecting and tracking acquisition or where users are coming from. It’s not built to track how users engage with a product, making the work of a product analytics team much more difficult. Because Google Analytics is not equipped to track user retention and engagement with the product, which is a much later stage of user engagement, product analytics are left without the data they need to produce valuable, actionable insights. 

To get these insights, product analytics teams need tools developed explicitly for product analytics, with features targeted at tracking user engagement and retention, such as cohort analysis, user journey comparisons, and segmentation analytics. 

But beyond this, what are the differences between Google Analytics and a product analytics tool?

Google Analytics

Google Analytics is the gold standard of marketing analytics tools. It’s a workhorse used by marketing analytics teams the world over. These teams use three different Google Analytics products:

Google Analytics 4

Google Analytics is the standard, free tool that is the most widely used by businesses and marketing teams.

Google Analytics 360

Google Analytics 360 is the paid, premium version of Google Analytics, which offers additional features like Display & Video 360, Campaign Manager, and machine learning models.


Firebase is Google Analytics’ tool explicitly tailored for tracking apps.

All of Google Analytics tools are designed to provide marketing teams clarity on which marketing directives lead to achieving their goals. The primary purpose of these tools is to assist marketing teams with adapting their marketing budgets and actions, optimizing their work towards what brings about the ideal user journey or attribution. Google Analytics helps marketing teams track key performance indicators (KPIs) like first-touch attribution, bounce and exit rates, and average session duration. While this is very valuable for marketers who want to collect information on marketing KPIs, such as traffic sources, page views, time on site, and completion of user outcomes, Google Analytics has few metrics on product KPIs that focus on user engagement, conversion, and retention. 

In addition to Google Analytics, Google recently launched Google Analytics 4 property (formerly App + Web) that tracks and processes web and app data combined. While this tool is promising for teams that need a combined view across web and app platforms, it still has gaps in meeting product analytics needs. Like Google Analytics, it is inadequate for gathering information on product KPIs. 

Luckily for product analytics teams, there are other solutions. 

Product Analytics

Product analytics tools provide information about the later stages of the user journey, namely how users engage with the websites and applications that product teams develop. They help product analytics teams answer behavioral questions such as:

  • Why do some users convert? Why do other users not convert?
  • How is retention linked to different user cohorts? What are the fluctuations in retention when users engage with other features?
  • What are the most prominent factors leading to user engagement and retention?
  • Who are your power/super users? What makes their behavior different from other users?
  • Is the release of a new feature correlated to or even caused the desired change in user behavior?

If teams use Google Analytics, the questions above are tough to answer. Answering questions about user behavior requires more sensitive and granular measurement, which Google Analytics simply isn’t built for. While Google Analytics relies on general, anonymized traffic data, product analytics tools use a tracking model centering on events. Products analytics tools track, on a much more granular level, the actions users take to engage with a product, like sign-ups, downloads, and uploads. By treating these events like nodes, product analytics tools link actions and behaviors to a single user, thus providing discrete insights into how each user’s behavior develops throughout the user journey. This allows product analytics tools to provide much more in-depth information about user behavior and answer the questions that product analytics must pose. It makes these tools a much better fit to drive product improvement and innovation, as it’s tough to improve products without understanding how users engage with them.

Product analytics tools boast a wide range of features for tracking user behavior, including event tracking, user cohort trends, powerful segmentation capacities, and easy access to in-depth analysis of user behavior. They assist product analytic teams, and product developers innovate their products even further.

But- do you need both?

In short, yes. Google Analytics and product analytics tools are structured for fundamentally different aims and needs. Google Analytics is a robust tool for marketing teams working on analyzing traffic to optimize marketing KPIs. On the other hand, product analytics tools work the best for product teams working on product innovation and need detailed information on user behavior. The two are not interchangeable and, in some sense, are entangled with each other.

When marketing and product teams use the tools that best fit their needs, the organization benefits from optimized innovation and growth. Marketing teams engage in market analysis which brings in new customers and allows product teams to rely on a more extensive user base to learn more about user behavior and improve engagement, retention, and conversion. Organizations can identify power/super users to convert into product advocates, which helps drive marketing. In a parallel sense, organizations can identify users with less engagement to whom they should market differently, to reduce bounce and exit rates. Satisfied users bring in more satisfied users. But organizations need product analytics tools to provide the in-depth information required to understand these users’ behavior.