7 Essential Product Management Analytics Tools for Product-led Growth

Product management is a data-driven profession – understanding every aspect of the product, from demand to development to real-life usage, lies at the heart of creating workflows that produce something meaningful for the end user. To achieve this, product managers need a whole arsenal of data analytics at their disposal, daily. Not to mention the fact that it’s a pretty underrated skill to be able to navigate between different data collection platforms without losing sight of the North Star goal of the business. If you are just starting out, the list of product management analytics tools in this article will help you navigate the sea of offerings. And if you are a seasoned PM, you might just stumble upon a hidden gem you never knew existed. Read on to find out!

Why bother with product management analytics?

Well, it’s a matter of choice between doing your job in a meaningful way and trying to find a needle in a haystack. For product-led companies, this is even more important as you simply can’t fix a bad product with great marketing. Just imagine trying to get buy-in for a new feature without backing up your claims with proper data outlining the need for the new feature. Or imagine a scenario in which you need to make a difficult decision such as prioritizing the development of one of two new features due to a lack of resources. You would want to know which one is more likely to produce the higher impact, right? That is if you’re not willing to sacrifice your career on a hunch. Having at your fingertips a toolkit of product management analytics tools will facilitate decision-making on a daily basis (and make it less stressful!). 

To be more specific, product-led businesses need insights into user behavior, preferences, and needs to inform product development and help identify opportunities for growth. Product-led growth (PLG) uses digital analytics data collection to:

• Understand user behavior: how users engage with the product, what features are most used, where users drop off, and what causes churn. 

• Identify product opportunities: trends and patterns in user behavior that may indicate areas where the product could be improved or expanded to meet user needs so that adoption rates increase.

• Optimize user acquisition: PLG aims to make the product itself the main driver of customer acquisition. Digital analytics tools help to understand which acquisition channels are most effective in driving product adoption, and which tactics can be optimized to drive more users to the product.

• Test and iterate: PLG relies on a continuous cycle of testing, learning, and iterating. Digital analytics data helps to measure the impact of changes made to the product, and identify which iterations are most effective in driving conversions, user engagement, and retention.

Your 1st Task: Setting up an Objectives Framework 

The first step towards the strategic use of product management analytics is to define a clear objectives framework. Why is that important? Because, as we already mentioned, navigating the sea of data is no joke. Working with 15 dashboards and 5 reports each day will make any sensible person lose their mind. To avoid this type of stress, you need to make sure you are laser-focused on the data you are tracking and the reason why you are tracking it. 

Setting up SMART goals as part of a broader OKRs system is a meaningful way to define the data you need. What do we mean by that?

• OKRs: Objectives & Key Results

• SMART goals: Specific, Measurable, Attainable, Relevant (Realistic), Time-bound

In the context of product analytics, OKRs can help product managers define measurable objectives and track progress toward achieving them using digital analytics data. Using SMART goals for the objectives part ensures that the PM remains laser-focused on results and doesn’t drift away from pursuing the ultimate business goal.

For instance, a product team may set an objective to increase user engagement by 20% over the next quarter (this is defined as a SMART goal in achieving the North Star of the company – 1M Weekly Active Users). They can then define key results that indicate progress towards this objective, such as increasing the number of users, reducing the bounce rate, or increasing the time spent on the product. The team can then use product analytics tools to measure progress toward these key results and adjust their product development strategy accordingly.

• North Star: Reach 1M Weekly Active Users in Q4

• Objectives: Increase user engagement by 20% in Q3

• Key Results: number of daily active users, bounce rate, time spent on the product

Setting your business’ North Star goal, as well as the objectives to follow to achieve it, is not the main topic of today’s article, but the least we can do is arm you with a few product manager analytics metrics you can use depending on your specific objectives. Print this cheat sheet and stick it to your monitor, or copy-paste it from the table below!

Engagement metrics	Daily active users (DAU) Time spent on site or app Pages viewed & Sessions per user
Activation metrics	Number of activations Trial/Freemium to activation conversion rate Number of drop-offs before activation
Acquisition metrics	Number of trial/freemium subscribers Number of paid subscribers Trial/Freemium to paid conversion rate
Monetization metrics	Cost Per Acquisition (CPA) Monthly Recurring Revenue (MRR) Customer Lifetime Value (CLV)
Retention metrics	Stickiness N-day retention Churn rate

We hope that you’ve spent some time reflecting on the best OKRs structure and now it’s time to move on to the fun part – measuring your results.

The Product Management Analytics Arsenal

We bet that you have scoured through at least three other articles on the same topic, looking to find the definitive analytics list for product-led growth. Well… You’re not likely to find such a thing on the internet. That’s because such a list always depends on your product and business plan. 

While in no way definitive, the following list focuses on the essentials. Our main goal was to give you a few comprehensive tools that are more than likely to serve all your data needs so you don’t have to switch constantly between ten data analytics platforms.

Google Analytics

Google Analytics is a free web analytics platform that helps you track and analyze your site or app performance. It is a part of a suite of tools offered by Google, including Google Search Console and Google Tag Manager, that provide various features to improve your online presence. 

One of the main benefits of using Google Analytics (GA) is that it provides a comprehensive view of your website or mobile app performance by collecting and processing vast amounts of data. This data is acquisition-oriented and includes information on the user side: how many visitors your site receives, where they come from, how they navigate through your site, what they do on your pages, and how long they spend on your site. You can use this information to gain critical insights into your audience. Because of this, it’s the main choice for marketing teams across the globe, but product managers can also glean insights from its dashboards, provided that they take the time to understand its limitations, set it up correctly, and integrate it with other tools they might be using.

GA uses a simple JavaScript code to collect data, which you can easily add to your website. If you wish to have better insight into event-based tracking, you will need to set up the events you need before you start collecting data using a tool like Google Tag Manager (which can be a bit tricky – and if you forget to add a specific event, you won’t be able to track it retroactively).

Heap

Just like Google Analytics, Heap is a product analytics software that collects data from every part of a website and presents it in an easy-to-understand data analysis format, focusing on customer engagement and activity. Heap tracks, collects, and analyzes data about the customer journey and your customers’ characteristics and habits. Rather than only looking at the big picture like GA, Heap focuses on tracking every action taken by your customers, allowing you to collect data according to your needs and preferences and see the emerging patterns of your customers.

Heap’s greatest advantage is that you don’t need coding knowledge to retroactively track data. It automatically collects data and organizes it into useful reports, so you can strategize data-driven plans and speed up the decision-making process. Heap tracks every click and every action that your visitor carries out on your website, without you having to instruct it to do so. This feature saves an enormous amount of time and effort, and provides a large data library for reference, at any point in time.

Mixpanel

Mixpanel is a step up from the previous two – a powerful product analytics tool that provides a user-friendly interface for deep data analysis on the website/app level and within the product itself which makes it a great add-on for SaaS companies. With Mixpanel, you can easily answer complex questions about your users, such as why they convert, what features they prioritize, and what keeps them coming back. For example, you can use Mixpanel to see top user flows, build funnels, and create cohorts with just a few clicks, without needing external help or SQL queries.

One of the key benefits of Mixpanel is Group Analytics. This feature allows you to calculate metrics at the company or account level, such as Active Usage, Product Adoption, and Retention. B2B SaaS companies, for instance, can use Group Analytics to better understand their customers’ usage patterns, prevent churn, and drive upsell.

Another perk of Mixpanel is its scalable infrastructure, which enables you to analyze raw user event stream data at scale without pre-computation. Mixpanel’s infrastructure can handle high-volume queries in seconds, even after ingesting trillions of events per year.

Amplitude

On the same front as Mixpanel, Amplitude is a tool that empowers teams with insights into what customer actions and features lead to outcomes, enabling them to optimize their business results. For example, you can use Amplitude to understand which product experiences and behaviors impact business value and customers, and which strategies to implement to improve retention, grow lifetime value and understand conversions.

One of the key benefits of Amplitude is cross-functional data access. Amplitude is easy to adopt throughout the organization, which can increase visibility, and improve decision velocity and quality. This allows different teams to easily collaborate and gain insight from each other’s work. Amplitude also offers breadth and depth of insights as it can analyze billions of events in less than a second. 

Hotjar

Hotjar is a popular tool that provides insights into the product experience of your customers by analyzing their behavior and collecting feedback data through tools like heatmaps, session recordings, surveys, and a feedback widget. It complements the insights gained from traditional web and product analytics tools like Google Analytics or Mixpanel. Hotjar is a service that helps you connect the dots between what is happening on your site and why it’s happening, making it easy to understand and empathize with your customers.

By using Hotjar, you can improve customer experiences and build digital products that will resonate with your customers’ pain points. Hotjar provides aggregated visual data about what’s happening on your site, helps you understand why people behave the way they do, and does all of this quickly without requiring a steep learning curve. On the flip side, its heatmapping tools can only go as deep as showing an aggregated visualization of the way people behave – and this is done page by page so you have to go elsewhere in search of sitewide trends. 

Optimizely

Optimizely is a digital experience platform that provides a range of applications in areas like e-commerce, search, marketing, and personalization. Product teams can use it to improve customer experiences by experimenting, optimizing, and ultimately – rolling out new features more quickly and safely. It allows you to run different types of tests, such as A/B tests, feature tests, feature flags/rollouts, and ‘multi-armed bandit’ tests, to determine which variations perform better and deliver more value to customers.

One of the key advantages of Optimizely (and what sets it apart from the rest of the tools on this list) is that it enables product teams to make informed decisions more quickly and efficiently than traditional product development processes. By measuring the performance of different variations, you can determine what works best and roll out changes with confidence, knowing that you are delivering value to your customers.

When conducting multivariate tests it’s of paramount importance to have a robust OKRs system in place as it helps your team to stay focused on their top-line goals and ensure that their experiments are aligned with their overall strategy rather than conducted in a vacuum.

SessionStack

We saved the best for last. SessionStack is a comprehensive Digital Experience Analytics platform that combines all the best parts of the options above in one neat package that can be installed in a matter of minutes and works its magic with tagless autocapture. It was built to provide both qualitative and quantitative data – that is, both the statistics and the real-life usage visualizations needed to conduct a thorough analysis of the user journey. Equipped with user segmentation, sitewide trends dashboard, and funnel analysis, it gives PMs the ability to quickly spot areas of frustration and opportunities for improvement. To validate their assumptions, session replay comes to the rescue with visualizations of user behavior during specific sessions. SessionStack is the best option if you’re looking for a platform that combines all the numbers and intangible insights into the user experience. 

What makes SessionStack unique is that it was built to provide a holistic overview of the entire digital experience journey, including the stages after conversion, stepping into the realm of customer success with low-latency co-browsing (not available on any of the other tools). 

It is especially suitable for product managers because it doesn’t require complex instrumentation or a steep learning curve. Its dashboards can be used on a daily basis to help PMs spot friction points before they become bottlenecks for growth. 

So, which tools are on your shortlist? A combination of a few might be the best option if you have enough resources to allocate to analysis. But, in case you are stretched to the limit – like many other PMs out there, a simple yet powerful tool like SessionStack may be all you need. Take it for a ride – it’s free!

To recap…

Product management is a data-driven profession that relies on a whole arsenal of product management analytics. For product-led businesses, understanding user behavior and needs is vital to inform product development and identify growth opportunities. Digital experience data helps measure the impact of changes made to the product, and identify which iterations are most effective in driving user engagement and retention. To do that, a mix of tools might be needed to correctly capture each stage of the journey. To make things easier, SessionStack has packaged some of the most impactful ones in one neat package you can try today for free.