Comprehensive Guide of Product Analytics

Product analytics allows you to understand how your product investment is affecting your business. With the right product analytics tools and data at your disposal, you can make informed decisions and enhance your business performance.

Jun 15 2020 5 min read

Table of Contents

    To keep customers coming back to your service or product, you need to be highly aware of the experiences you provide. Most customers interact with your business through your product, so you must ensure you provide an experience that keeps them returning.

    What Is Product Analytics?

    It’s an approach to understanding user engagement or whether users find value in your product. This involves using product analytics tools that monitor how users interact with what you build.

    It allows tracking digital footprints of users, analyzing their flow, and realizing what makes them engage, convert, churn, or return. The collection and analysis of this type of data help you make better decisions for your business.

    Why Is Product Analytics Important for Your Business?

    No matter the type of industry, everyone has competitors. However, the most successful companies know that meeting the needs of their users should be their top priority. So, they strive to provide their users with the best version of their product.

    Instead of evolving their product based on their gut instinct, guesswork, or internal needs, they create a better product using product analytics which makes them more profitable than their peers.

    Thanks to this data, they can understand how users engage with their product, what they like or dislike, what they do, and what makes them engage, churn, or return. These metrics can even be deduced with the help of in-app marketing analytics.

    If product managers use only discussions and surveys to find out the experience their users have with their product, they can easily come to the wrong conclusions. That’s because users can’t always tell or know what they value most about your product or why they interacted with your product in a certain way. This type of product feedback is often inaccurate.

    On the other hand, product analytics provides definite and objective data since you are tracking the actual behavior of users within the product. This can reveal valuable insights that help you create better products.

    Questions Answered Thanks to Product Analytics

    Regular approach to analytics won’t tell you the answers to some of the most important questions about the effectiveness and performance of your marketing activities and product development.

    With product analytics, you can find out:

    • Why customers use your product;

    • How much usage-specific features get;

    • The type of marketing channels that drive quality users;

    • The number of users completing a critical event;

    • The characteristics of the most engaged users;

    • The number of returning users;

    • Where they get stuck in the onboarding funnel.

    How to Use Product Analytics?

    Each product analytics tool is built around two basic functions that can help you find out valuable information about user experience:

    Tracking data – capturing actions, events, and visits;

    Analyzing data – visualizing data through reports and dashboards;

    After tracking, capturing, and organizing data, you can ask questions like:

    • What’s the usual behavior flow my users take through my app or site?

    • What are my user demographics?

    • What chances do I have to reduce churn?

    The answers to these and other questions provide you with statistically valid facts upon which you can make the right product and marketing decisions.

    Typical goals with this type of analytics include:

    • Segmenting the most valuable (profitable) users;

    • Improving product retention;

    • Discovering user pain points;

    • Realizing how people are using the app or site;

    • Deciding where to invest money;

    • Reducing churn.

    How to Analyze a Product?

    Here’s an example of product analytics implementation plan you can consider:

    Connect Data to Business Goals

    To avoid wasting time and money on collecting and analyzing sales data that your company won’t be able to use productively, make sure you outline specific business objectives for the data you intend to capture.

    For example, your business objective may be finding out how to convert more webinars leads to sales prospects.

    Make a Detailed Tracking Plan for Your Data

    Product analytics data is usually broken down into events that describe actions users take within your service or product. For instance, they access a new feature, send a message, open a new screen, close the app, etc.

    You can use a spreadsheet to create a tracking plan by listing all user actions or events you wish to track while users interact with your product. Make sure you don’t omit any step in a user’s journey to avoid losing valuable insight into their product engagement.

    Pick the Best Product Analytics Tool for Your Needs

    Today, there are many different tools to choose from, but make sure you pick the one that allows you to implement your unique strategy. Below you’ll find out more about these tools and tips to choose the right one for your business.

    How to Choose a Product Analytics Tool

    Product analytics tools provide you with visibility into your users’ interactions with your product or service, including interactions, events, and visits. They allow you to track digital interactions throughout your product to find out what is engaging users.

    The dashboards and reports offered by these tools analyze data and make it actionable to ensure a better user experience. They are most commonly used by product managers, designers, and developers to make informed decisions when establishing product roadmaps and developments.

    Businesses can use these tools to gain segmented views into their customers, find struggle points, understand how they are using their websites, and enhance the overall product experience.

    Nowadays, there’s a wide range of product analytics tools to choose from, so picking one can be challenging. What you should pay attention to when choosing the right tool for you is ensuring that at least it supports:

    • Integrations to all applications and websites you plan to track. Otherwise, you’ll need multiple analytics tools;

    Data security and reasonable uptime;

    • An intuitive user interface that’s accessible to everyone in the team.

    Best Product Analytics Tools

    Here are some of the best product analytics tools on the market, in no particular order:


    • Mixpanel;

    • Woopra;

    • Quantum Metric;

    Amplitude Analytics;

    What Are the Four Types of Analytics?

    Each type of analytics is important and offers valuable insight, so they are all interrelated. Here are the four types of data analytics that can help you make better-informed decisions for your business:

    1. Descriptive analytics – summarizing or describing existing data with BI tools to answer questions like “what has happened” or “what’s going on?”

    2. Diagnostic analytics – measuring historical data against other data to find out why something has happened. This type of analytics provides in-depth insights into a specific problem.

    3. Predictive analytics – forecasting the possible outcome with the help of machine learning and statistical models. It answers questions like “what’s likely to happen?”

    4. Prescriptive analytics – prescribing what action to take to take full advantage of a promising trend or avoid a future problem. This type of analytics uses business rules, algorithms, machine learning, and other advanced tools and technologies.

    To find out the type of data analytics your organization needs, answer these questions:

    • What is the current state of data analytics in your organization?

    • Should you dive deep into the data to find out the answers to your problems?

    • How far are the data insights you have right now from the ones you need?

    Answering these questions can help you make a unique data analytics strategy.

    Published on Jun 15 2020



    Former data analyst and the head of Whatagraph blog team. A loving owner of two huskies, too.

    Read more awesome articles

    Enter your email and get curated content straight to your inbox!

    Only the best content & no spam. Pinky promise.
    By submitting this form, you agree to our Privacy policy