Product & Growth Tips

The difference between product analytics and marketing analytics—and why you need both

Glenn Vanderlinden Director, Technical Operations & Services at Semetis

This post is written by Semetis, a data-driven marketing agency located in Brussels, Belgium. Semetis works with different types of businesses, from start- and scale-ups to blue-chip clients, to help them grow and accelerate the digital side of their business.

Here’s what you’ll learn: 

To be successful, organizations need more data. More importantly, they need the right kind of solutions to interpret that data, and drive actionable innovation across their organization.

As a marketing agency focused on helping customers leverage data smarter, we work with a lot of customers who are trying to “growth hack” their success with data. It’s a brilliant strategy: identify what’s working and what’s not, and either double down on it, cut it, or fix it.

But when it comes to using data for product innovation, more often than not, there’s a mismatch between the tool teams use and the data they need. Companies often want to use Google Analytics, a marketing analytics solution, instead of a product analytics solution (like Mixpanel) to understand user behavior—and it almost never works.

Here’s how the story typically unfolds:

Company A hopes to expand their data-driven mindset from marketing into product development. We recommend implementing a product analytics solution. Despite our recommendation, they move forward with Google Analytics because it’s already widely used and loved by the marketing team—why wouldn’t it work for the product team?

Using a tag management solution, we hack up a workaround to track specific user actions within the product. Some data on how many times and how often these specific actions are performed start rolling into Google Analytics. It’s a start, but it’s not enough; the data isn’t actionable. 

Six months later, the team still doesn’t have the answers they need about user behavior to make data-informed decisions for product innovation, and we’re back to square one. 

It’s not that Google Analytics isn’t a valuable solution. It’s that it’s not the right solution for product teams to track and understand user behavior. Google Analytics, by trade, is a marketing analytics solution that’s built for marketers to understand the first part of the user journey (where users are coming from). It’s not, however, a tool designed to answer questions about how users are engaging with a particular product.

For this, teams need a dedicated product analytics solution that’s designed to track, measure, and analyze user behavior through out-of-the-box capabilities like custom event tracking, cohort analysis, user path comparisons, and flexible segmentation.

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

Google Analytics

Google Analytics is undoubtedly the king of marketing analytics solutions. Ask any company and the majority will have leveraged it at some point.

Google Analytics can be split into three different product offerings: 

  • Google Analytics: This is the standard, free version of Google Analytics that most businesses and marketers are familiar with.
  • Google Analytics 360: This is the paid tier equivalent of Google Analytics, offering more advanced features such as integrations with Display & Video 360, Campaign Manager, Bigquery integration, and removal of sampling.
  • Firebase: Google’s solution for app tracking.

Regardless of which product offering you use, they’re all designed to give marketers insights into which marketing initiatives are helping to drive the desired outcome. Their primary objective is to help marketers optimize traffic streams, and adapt their marketing budgets, efforts, and actions towards the means that drive maximum results—also known as attribution.

Google Analytics helps marketers track KPIs like bounce rate and sessions, as well as first-touch attribution (where users are coming from).

As you can see from the example above, the data and insights from Google Analytics are focused on traffic sources and acquisition, and “behavior” information is centered around rather generic metrics like bounce rate, sessions, and average session duration.

Google Analytics products provide very strong reporting on marketing KPIs such as number of page views, time on site, and completion of goals and transactions, but not nearly enough on product KPIs like engagement, retention, and conversion.

In addition to the two versions of Google Analytics, Google has recently introduced a new property type called App + Web that combines app and web data for unified reporting. Sounds promising—especially for companies with app-based products. Here’s the catch.

While the latest App + Web beta release is a step in the right direction for getting a unified view of activity across two platforms, it’s still behind when it comes to delivering on product analytics needs. It’s missing some key capabilities around reports, and accessing retroactive data and insights. The public product roadmap for addressing these gaps is unclear.

Luckily, there’s already a solution available in the market.

Product Analytics Solutions

Product analytics solutions, like Mixpanel, provide insights into how users are actually using the websites and applications product teams are building. They answer questions like:

  • Who are your power users? And how do their behaviors differ from other users? 
  • Why do some users convert, while others don’t?
  • How does retention differ by user cohort? Is it higher or lower when people engage with a particular feature?
  • What are the top drivers of user engagement and retention?
  • Did that new feature release cause the desired change in behavior?

All these questions are very hard—sometimes impossible—to tackle using Google Analytics. Why? Because it’s not built for providing that granular level of measurement. The single largest difference between Google Analytics and a product analytics solution is that the former relies on anonymized traffic data, and the latter uses an event-based tracking model designed to track specific actions users take within a product.

Product analytics tools are designed to collect all of these events and properties and link them to a single user ID, providing insights on how each web or app user is moving through the customer journey.  

Product analytics solutions use an event-based tracking model to track actions users take within a product, like signups and downloads.

This simple—yet powerful—difference is what allows product analytics solutions to answer deep questions about user behavior, and what makes them a much more suitable solution to fuel product innovation. After all, you can’t build or improve products without understanding how users are behaving in the first place.

With a full arsenal of out-of-the-box capabilities like user cohort trends, easily customizable event tracking, a powerful segmentation engine, and on-demand deep analysis on user behavior, product analytics solutions are designed to help product builders drive product innovation.

Google Analytics and product analytics: do you need both?

The short answer is “yes.” Hopefully, by now, it’s clear that the two tools are fundamentally different—built to serve different teams’ needs and objectives.

Google Analytics is an excellent tool for marketing teams who want to analyze and optimize traffic to improve marketing KPIs. Product analytics are the best solution for product teams who want to understand user behavior, which is crucial to product innovation. One can’t replace the other, and in fact, they live in a symbiotic relationship.

When both teams are equipped with the right tools, it creates a cycle of sustainable positive growth for the entire organization. Marketing teams optimize marketing spend to acquire new customers, which gives product teams a larger user base to find new ways to improve engagement, conversion, and retention. Businesses can then identify power users to market to and turn them into vocal advocates, helping fuel the marketing machine. Similarly, they can identify ‘struggling’ users to whom they should offer a different set of product and marketing experiences to reduce churn.

Happy customers, without a doubt, create more happy customers. But it takes a product analytics solution to provide the insights needed to understand the behaviors that drive it.

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