🗣 Product analytics solutions like Mixpanel and marketing analytics solutions like Google Analytics 4 are built to analyze different parts of the customer and user journey. Most data-driven companies will want to add both to their toolkit.
To be successful, organizations need data. But data is only powerful when unlocked with analysis, and not all analytics tools are created equal.
Relative to product analytics, marketing analytics is a well-understood, familiar concept. Many companies today are already leveraging marketing analytics to “growth hack”: identify the marketing channels that are bringing new users to your product and those that aren’t, then double down, fix, or cut those channels.
But if companies are already exploring data with a marketing analytics tool (typically Google Analytics), they often think it’s fine to forego a dedicated product analytics solution (like Mixpanel) to understand user behavior in their product—and that almost never works.
Here’s how the story typically unfolds:
Company A hopes to expand their data-driven mindset from marketing into product development. Despite being recommended a product analytics solution, 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 combination of built-in tracking and some custom tags, they track specific user actions within the product. Some data on how many times these specific actions are performed start rolling into Google Analytics. It’s a start, but it’s also about as far as a marketing analytics tool can take them in this application. Without product-tailored analytics to help them pinpoint why certain user metrics are going up and down, and among which users, their 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 improving their product, and they’re back to square one.
Understanding the capabilities of marketing analytics and products analytics can help you and/or your company avoid the above scenario by—in all likelihood—leading you to use both. Here’s why.
The difference between Google Analytics and product analytics solutions
How Google Analytics works
Google Analytics (GA) is undoubtedly the king of marketing analytics solutions, so there’s no sense in presenting a tool-agnostic perspective in this side of the comparison. And like other marketing analytics solutions, it was designed from the beginning to understand the first part of the user journey: where users are coming from.
Out of the box, Google Analytics provides very strong reporting on marketing metrics like:
Number of pageviews
Sources and attribution for those pageviews
Time on site
Completion of goals and transactions
And given its integration with the Google ecosystem, GA is frictionless when it comes to deeply understanding those metrics in relation to spend across popular marketing services Google Ads and Campaign Manager.
Google Analytics is built to help marketers track KPIs like bounce rate and sessions, as well as first-touch attribution (where users are coming from).
Even with the modernization of its data model in its newest release, Google Analytics 4 (more on that below), what GA is still not designed to do is answer complex questions surrounding how users engage with a product once a marketing channel brings them in.
How product analytics solutions work
Product analytics solutions, like Mixpanel, provide fast insights into how people are actually using the websites and applications product teams are building. They offer user segmentation features and reports that can 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?
With a full arsenal of out-of-the-box capabilities like user cohort trends, a powerful segmentation engine, and on-demand deep analysis on user behavior, product analytics solutions give input for product builders who are tasked with making improvements or additions to the product.
Did that new feature release cause the desired change in behavior? No? Maybe it needs a design tweak.
All of this specialization towards deep product usage means solutions like Mixpanel don’t default to collecting things like pageviews and reporting attribution.
How does Google Analytics 4 change the comparison?
With the release of Google Analytics 4, the technology differences between the most popular marketing analytics and product analytics platforms shrunk a bit. While earlier versions of GA had relied on grouped traffic data (sessions) to optimize for marketing analysis, product analytics solutions like Mixpanel have for years used event-based tracking models to read and record specific actions users take within a product.
GA4 marks a switch to a similar event-based data model, but the marketing orientation of GA shows in the preset choice of user events, which are meant to analyze the same basic acquisition metrics as always.
Though GA’s redesign does open the door to making it a more customizable analytics platform for companies who are willing to build custom event-tracking and reports themselves, the most powerful product analytics solutions require far less engineering time to get up and running on your product.
Does all of this mean GA today is a more interesting and powerful tool under the hood? Absolutely. But does that mean it’s all of the sudden the right tool for the job of product analytics? No. Instead, GA’s new event-based model makes it an even greater fit for coexisting with product analytics.
Google Analytics 🤝 product analytics
Hopefully it’s clear by now that marketing analytics and product analytics are fundamentally different—built to serve different teams’ needs and objectives. 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.
If you would like to explore the details of our work with other clients, please feel free to reach out. We are always eager to engage in insightful discussions.