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Product Analytics: A Comprehensive Guide for SaaS Product Managers

SaaS Product Management
Aug 2, 2023
Product Analytics: A Comprehensive Guide for SaaS Product Managers

How do your product users really feel about your software? User feedback surveys are a great way to find out, but they don’t tell the whole story. Whatever insights stay hidden, data can uncover. By analyzing real user behavior, product managers can uncover common problems and improve user experience at scale.

In this article, you’ll learn what product analytics is, and how you can use it to build more impactful products that solve real user needs.

What is product analytics?

Product analytics is the process of analyzing customer behavior in digital products. Product teams can track, measure and analyze user engagement to learn how their customers are using their platform.

With good product analytics data, SaaS product managers can better understand what makes their product stick with customers. It reveals which product features customers use most, where they struggle, how they get value out of the software, and more. With this rich information, product managers can make better product decisions, and shape more impactful products.

Why use product analytics?

Better decision-making

Qualitative data, like feedback from customer interviews, is useful to grasp what a single customer likes or dislikes about your product. But quantitative data, like product usage, will show you problems and opportunities that affect a whole group of customers. Combine both, and you’ll deeply understand your customer’s needs. It will help you make better decisions about your roadmap, and prioritize what creates the most impact for your customer.

Product analytics help product managers be more confident about which features will make their product better. Likewise, product marketing teams have a clearer direction for their go-to-market strategy.

Customer retention

The more time a user spends in-product, the more likely you’ll retain them as a loyal customer. Product analytics can help you find all sorts of levers to boost customer engagement and retention. Customer success and product teams can work together to keep customers engaged, and help them get the most out of your software. And as a result, you’ll likely see less churn.

Improved customer experience

With product analytics, you can pinpoint and solve glitches in the customer journey. From onboarding to long-term users, you can identify where users drop off and fix one problem at a time. Step by step, you’ll improve the user experience in every stage of your product lifecycle.

Even if you identify pain points in your product experience you can’t immediately fix, your customer success team can proactively step in and help look for specific workarounds.

Product innovation

By spotting trends in product usage, you can discover new products or innovations that tie directly to your user’s needs. Let’s say you run a marketing SaaS. Three of your top five most used features are related to reporting and analytics. With this knowledge, you can identify similar new features to build during product discovery.

Product analytics vs embedded analytics

It’s easy to confuse embedded analytics with product analytics. Although they are two completely different things, most Product Managers deal with both at some point. Let’s look at some of the key differences.

Product analytics helps product teams measure the success of their digital products. It lets you track and analyze user behavior, so you can decide which product features to prioritize during sprint planning.

Embedded analytics, however, helps your product users make better decisions in their day-to-day workflows. It exposes dashboards or reports inside your software, for your software users to consume.

For example, let’s say you manage the roadmap for an email marketing SaaS. With product analytics, you can track product KPIs like daily active users or most used features. With embedded analytics, your customers can track the clickthrough rates of their campaigns or email list health and growth, all from within your marketing application.

While product analytics is an internal process for SaaS companies, embedded analytics is a product feature. Both improve the product experience for your customers, just in different ways.

Product analytics vs embedded analytics comparison

Which product metrics to track?

The first step to a data-driven product strategy is to decide which data you want to track. Here’s a list of common data points to track in your SaaS product:

  • Active users
  • New users
  • Page views
  • Session duration
  • Feature usage
  • Completion of certain milestones (= actions you’ve defined as key user engagements)

Once you’re tracking your key user actions, you can calculate more detailed product engagement metrics like product adoption rate, time to value, or product engagement scores. Which product metrics are right for you depends on your goals. While early-stage startups may focus on acquiring new users and product adoption, mature products will spend more time on increasing retention and stickiness.

Product analytics use cases

Let’s look at a few specific examples of how to use all that behavioral data as a product manager.

A/B testing

UX designers use A/B testing to run experiments and find out product designs work best. With product analytics, you can track user engagement on both versions and evaluate your hypotheses. It’s a great way to improve conversion rates and usability of a software product. In fact, partnering with conversion rate optimization experts can significantly enhance these efforts.

Funnel analysis

Analyzing funnels is essential for product managers to improve their conversion rates. The trial-to-paid user funnel is a typical example, but you can build funnels for almost any user journey. By understanding in which steps your users drop off, you can take actionable steps to boost product adoption.

Cohort analysis

A cohort analysis segments product users into groups with common characteristics, for example:

  • Demographics: age, gender, location,...
  • User actions: users who used a certain feature
  • Funnel stage: trial vs paid users
  • Activity: most or least active users

A cohort analysis analyzes user behavior of each segment during a specific timeframe. It can tell you which characteristics define your most and least engaged customers. And once you know that, you can use that information in messaging or engagement strategies to move customers from low to high-value segments.

User retention analysis

If you’re already tracking product logins and active users, you can start doing user retention analysis. By analyzing how often users return to your product, you can better understand engagement across your entire user base. Once you know which user groups are less engaged, you can define actions to lead them back to your product.

Best product analytics tools

Google Analytics

Although mostly popular among marketers, product teams can also use Google’s free web analytics service to track engagement in simple web applications. If you’re just starting out, it can be a good starting point.

Google analytics dashboard showing app usage metrics
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Mixpanel

Mixpanel is one of the most powerful product analytics software to track user interactions on web and mobile applications. It has very robust features for user segmentation, cohorts, drop-off analysis, and it comes with a bunch of integrations.

Screenshot of Mixpanel's product metrics dashboard
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Amplitude

Amplitude is a powerful analytics solution with a range of product analytics features, but it really excels at reporting, custom dashboards and advanced funnels.

Example of Amplitude product analytics
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Pendo

When it comes to ease of use, Pendo is one of the most intuitive analytics platforms. They also have a proprietary “Product Engagement Score” to score user engagement. They also offer features like in-app feedback, which makes it a great all-in-one tool.

Screenshot of Pendo including feature usage and NPS statistics
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LogRocket

LogRocket is used by many product development teams for error monitoring and session replays. It’s great for debugging and resolving glitches in your user experience.

Mobile app performance monitoring in LogRocket
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Wrapping up

Product managers who effectively use product analytics will set themselves apart from companies who rely on gut feeling to shape their roadmap. Equipped with insights into real user behavior, you’ll be able to build products that answer real user needs and solve glitches in your product experience.

And if you really want to take things to the next level, you can consider opening up important usage metrics to your customers. With embedded analytics tools, you can empower customers with key metrics to make confident decisions, all from within your SaaS application.

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