Analytics For Product Managers: What to Track and How to Act Upon Data (original) (raw)

What is product analytics?

Product analytics is about collecting and analyzing user interactions across the product in an effort to understand what drives product adoption and long-term retention. It enables product teams to understand and address true customers’ needs and pain points and spot product friction.

Product management analytics lead to improved retention and conversation rates, resulting in revenue growth.

The typical questions product analytics answer are:

How do product analytics differ from marketing analytics?

Marketing analytics only explain the first step in the user journey. It draws insights into how visitors engage with the site and what marketing messages and channels attract relevant user segments.

Marketing teams aim to understand what converts customers and how to convert as many as possible.

Marketers rely on Google Analytics, Google Search Console, and other data visualization tools to analyze the first step in the user journey.

Likewise, product management analytics focuses on user engagement throughout the entire customer journey. It aims to understand what features users like/dislike and their customer experience.

The primary goal is to gather tons of information to build a product-led company, delivering the best solutions to the market’s needs.

How data analytics can help product managers

In short, data analysis enables companies to make data-driven business decisions on further product development to ensure product-market fit.

Let’s discover more benefits of product management analytics.

analytics for product managers

What’s the biggest question you want data to answer right now?

How do you currently track user behavior?

Once you find an insight, what happens next?

Close the loop between data and action.

Great product managers don’t just look at charts; they fix problems. Userpilot gives you the analytics you need (Retention, Funnels, Paths) AND the tools to act on them immediately without waiting for dev cycles.

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Product analytics help product managers determine how people are using their products

To do so, an analytics product manager relies on tracking specific user events. This translates into understanding how users use the product:

To track these analytics, product managers rely on analytics platforms (like Userpilot) to collect and analyze data. For example, you can set up custom events to collect data on completed milestones in feature adoption and the frequency of feature usage.

Custom events in Userpilot

Custom events in Userpilot

Product analytics’ retention metrics can tell product managers how sticky the product is

Customer retention is the metric that shows the percentage of recurrent customers (aka those who pay monthly and continue using your product).

For SaaS, it’s one of the vital product management analytics metrics that literally highlights whether businesses make it or break it.

Combine retention and usage metrics to understand how sticky your product is, and why.

Track how different user segments engage with the app and how this changes over time. And analyze product engagement across different cohorts over time to find patterns and make informed decisions based on the data.

For instance, you can learn that some features need to be sunset, or there are friction points in the customer journey that are causing churn and drop-offs.

What decisions can a product manager make based on product analytics?

Product analytics give product management teams insight into various aspects of the business and help them make data-driven decisions regarding questions like:

Tie customer insights with user analytics to drive product vision and impact key business results.

How can product managers track product analytics?

For analytics to make sense and guide your decisions, you need to combine insights, ask logical questions, and experiment with your data.

Create hypotheses, and test them to see how they work out in reality.

Here’s how product manager analytics helps with that.

Segmentation helps product managers perform an in-depth analysis of data

Customer segmentation is the process of grouping users by certain characteristics that they share (in-app behavior, sign-up date, goal, events).

For instance, needs-based customer segments allow you to compare how fast users of the cheapest plan adopt the product versus the enterprise ones.

You can see this by building segments based on the answers you collect through user feedback, and then tracking how each segment engages with your product. You can also conduct customer interviews from these segments to collect qualitative data to back the quantitative data from your analysis.

Segmentation in Userpilot

Segmentation in Userpilot

Cohort analysis gives granular insights into user behavior

Customer segments linked to a given period of time are called cohorts. Conduct a cohort analysis to see what a subsection of your users is doing with your software/tool at a certain time period.

There are two types of cohort analysis: absolute and relative. Absolute cohorts are created based on fixed groups of users. For example, those who completed product adoption within a week after you rolled out a new onboarding flow.

Relative cohorts analyze shifting groups of users (e.g., those who signed up within the past 15 days).

Cohort retention analysis in Userpilot

Cohort retention analysis in Userpilot

Funnel analysis helps reveal friction points

A funnel measures the steps that users take toward a specific goal. It also answers questions like how many users have completed the onboarding flow (activation funnel steps completed) and where they drop off.

For instance, you can use Userpilot’s events to track user interactions across the product’s interface:

And you can tag these interactions as “features” directly using the Chrome Extension.

Build a flow, spotlight, or tag a feature with Userpilot.

Build a flow, spotlight, or tag a feature with Userpilot.

Once you’ve set the features you want to track, it’s also possible to test them, so you can be sure you are tracking accurately.

Tagging UI interactions with Userpilot

You can then visualize these tagged interactions via funnel analysis and use that to identify friction and drop-off points.

Funnel analysis in Userpilot

Funnel analysis in Userpilot

Behavioral analysis allows product managers to understand customers on a deeper level

Behavioral analysis is a strategy of grouping customers based on how they interact with your product. Product teams use behavioral analysis to improve in-app experiences and promote customer expansion.

It also helps to predict future customer behavior, monitor growth patterns, and discover what drives growth.

You can also use session recordings (coming to Userpilot in Q2 2024) to collect relevant data and determine which features are working and which can be improved.

hotjar-session-recordings-analytics-for-product-managers

Hotjar session recordings

Path analysis shows the ideal customer path to value

Path analysis helps product managers discover the different paths users take. You can use this technique to find the happy path, which is the shortest path to value. Once you figure this out, you can replicate it for other customer segments to drive them toward product success.

Path analysis in Userpilot

Path analysis in Userpilot

Product analytics to track to make data-driven decisions

It’s essential to understand and track the main product manager analytics metrics that move the needle. This section will talk about essential product metrics that boost business growth.

Let’s learn all of them.

Product engagement analytics and metrics

Product engagement analytics tell you what product features are popular, how much time users spend using your product, and whether users are getting value from the product.

You can use this analysis to improve your retention with:

Onboarding checklist created in Userpilot

Onboarding checklist created in Userpilot

Here are several essential metrics of product engagement to keep an eye on:

You can use Userpilot’s core feature engagement dashboard to view these metrics in a single place. You can always customize these dashboards to suit your needs.

Core feature engagement dashboard

Core feature engagement dashboard

Product adoption analytics and metrics

Product adoption occurs when your users start using your product purposefully. In order to measure product adoption effectively, you need to understand the breadth, depth, and duration of feature adoption.

Some metrics needed to measure product adoption are:

Userpilot’s product usage dashboard shows product managers all relevant metrics to make data-driven decisions.

Product usage dashboard in Userpilot

Product usage dashboard in Userpilot

Product retention analytics and metrics

Product retention is critical for business growth as it increases your customer’s lifetime value.

Important product retention metrics include:

Userpilot has a dashboard for user retention as well. You can use it to view the retention rate for different time periods and user segments.

User retention dashboard in Userpilot

User retention dashboard in Userpilot

Financial product analytics and metrics

Common examples of financial metrics are:

Userpilot: The best product analytics tool for product managers

Out of the many product analytics tools in the market, Userpilot stands out. This is because of the advanced analytics functionality along with engagement features to act on the insights collected.

Here are Userpilot’s top product analytics features:

Trend analysis in Userpilot

Trend analysis in Userpilot

Userpilot integrations

Userpilot integrations

Conclusion

Product insights unlock product growth opportunities and put you on the same page with your customers. Without this, it’s merely impossible to build a solid product the market craves.

Start collecting customer data and take your product to the next level! Get a Userpilot Demo to unlock its full potential for product analytics.