What is Product Analytics?

What is Product Analytics?

If you’re responsible for creating websites and digital experiences, product analytics can tell you exactly who is using them. And how. And where. And when.

Product analytics software gives teams and leaders tools to see exactly what is happening in their products. You can assess users’ digital experiences, optimize performance of product usage, diagnose problems in your customer experience, correlate customer activity with LTV, and more.

If you want to create a great digital experience, you'll need to prioritize correct information and eliminate random guessing. To do this, you’ll need to capture everything and illuminate critical moments of friction and opportunity (even if you haven’t chosen to follow them.)

Then pair these insights with qualitative tools to see what people are experiencing. Then you’ll know which features customers use. Which they ignore. Where users experience friction. How to best reduce churn. And where you can personalize interaction for users.

Why are Product Analytics important?

With Product Analytics, you can:

• See in real time how well you’re meeting user needs.

• Measure the exact success of individual features.

• Make informed decisions on metrics that support business goals.

• Transform your ability to develop ideas and design user experiences.

Products are complex! There are a million decisions when building them. 

Of all the “correct” choices, which one is BEST?

Over 100 years ago, John Wanamaker said “Half of my ad budget is wasted—the problem is I don’t know which half.” Yet companies today still measure the effectiveness of their software with speculation and guesswork.

With respect to gut instinct and experience, data science gives us a smarter, more accurate path to decision-making, rather than relying on guesses or customer interviews. For product teams, analytics give you a superpower.

Now you’re making solid supportable decisions!

How do teams across the org benefit from Product Analytics?

First and foremost, by being able to make better decisions!

Analytics can answer inquiries from stakeholders everywhere in your organization. This supports evidence-based decision-making, enhances user experiences, and drives both product and business growth.

• If you’re a product manager: You can understand what your users are really doing, in order to craft digital experiences that captivate them. Now you’ll be able to make data-driven decisions, measure and run experiments, and increase activation, conversion, and retention. Try our guide to play with our CRO calculator.

• If you’re a marketer: You can see which programs bring in the most visitors. You’ll be able to identify the users most likely to convert, discover factors for long-term retention, and direct your efforts to improve product development.

• If you’re a dev team leader: You’ll be able to eliminate bugs, fine-tune features, and resolve friction in the user journey while you save precious engineering resources.

• If you’re a UX designer: You’ll learn in detail how people navigate feature sets. You can see what’s popular (and what’s confusing), identify roadblocks, and pinpoint key moments of abandonment.

• If you’re a growth manager: You’ll get a complete view of user engagement to help you define and refine retention strategies and optimize them according to business needs.

• If you’re a data analyst: You can translate data into meaningful information that informs business strategies by using product analytics to perform in-depth data analysis, identify trends, and generate actionable insights. 

• If you’re a business intelligence analyst:You’ll be empowered to create faster and more accurate processes that consolidate disparate insights into cohesive plans, turn insights into stories that inspire action, and answer questions in minutes, not months.

• If you’re on a customer success team: You can track the health of your different accounts in real-time and see what customers are doing. Now you’ll know which features users favor and how often they use them, as well as make onboarding easier and more intuitive.

• If you’re an executive in upper management: You’ll gain a holistic view of product performance, user engagement, and revenue metrics to help you assess business objectives, make strategic decisions, and track the overall success of the product.

At the end of the day, your customers benefit the most by having products they love, because they are intuitive, easy, and a pleasure to use!

Learn some of the top-performing uses for product analytics.

How does Product Analytics impact the Business?

Product analytics are great in many use cases. For any team, product analytics data is crucial for measuring and systematically improving main product metrics: AARRR, aka the Pirate Metrics.

Acquisition:

Knowing where your customers come from.

In order to gain new users, you need to know what’s effective at attracting them and enticing them to engage with your products, services, and brand.

Which channels do they favor?
What are optimal costs for converting each user? 

Activation:

The product experiences on the journey to becoming a paying customer.

Each breadcrumb along this trail is a “micro-conversion”. The point at which users fully connect and realize value is their “Aha! moment”. Product analytics can help you optimize these steps.

Retention: 

Are customers staying or leaving?

This is perhaps THE most important metric to understand. Figure out who’s satisfied (as well as who isn’t) and know WHY. Product analytics gives clues on how to win them over and make them happier.

Referral:

The only thing better than a satisfied customer….is a whole bunch of them!

Product analytics lets you measure your customer loyalty by tracking their actions.

Are your purchasers talking up your product?

Revenue:

Ultimately, it’s all about making more money with your product.

Streamlining your sales funnel will reduce acquisition costs and increase the value of the customers you retain.

How does product analytics help companies improve revenue?

Product analytics provides valuable insights into user behavior, customer preferences, and product performance. It enables businesses to optimize digital experiences, increase customer satisfaction, and identify opportunities for upselling and cross-selling.

By making data-driven decisions, companies can enhance conversion rates, improve user retention, and target marketing efforts more effectively, ultimately driving revenue growth.

What are the key differences between Product Analytics, Data Analytics, and Business Intelligence? 

Product Analytics Tools are used to optimize product experiences. They focus on analyzing user behavior and interactions within digital products like websites and mobile apps. Primary users: Product teams looking for insights into user engagement, conversion funnels, and feature usage. 

Business Intelligence Tools are used to make strategic decisions and monitor business performance. They focus on analyzing overall business data and performance across various functions like sales, marketing, and finance.

Primary users:  Executives, analysts, and business teams looking for insights into key performance indicators (KPIs) and business trends.

Data Management Platforms (DMPs) provide audience segmentation and targeting capabilities for marketing and advertising purposes. They focus on collecting, organizing, and segmenting large sets of audience data from various sources.

Primary users: Marketers and advertisers creating targeted campaigns to reach specific audience segments.

Web Analytics gives insights into website traffic, page views, and user interactions. These tools focus on analyzing user behavior and interactions on websites.

Primary users: Marketers, website owners, and businesses who wish to optimize marketing strategies and site performance.

What are some specific examples of Product Analytics, and how are they used?

In general, a good analytics tool will give you the following capabilities:

• Behavior Tracking can be automatically applied to user actions across your sites and apps

• Cohorts allow you to identify trends and patterns among user groups based on common characteristics

• Segmentation teaches you who users are, where they came from, and when

• Profiles let you establish user categories around criteria of your choice

• Notifications permit you to alert product teams and communicate with users

• A/B Testing compares versions of messaging and features for effectiveness

• Dashboards allow you to visualize data in useful and revealing ways

• Heatmaps and Session Recordings let you see hotspots of activity and replay individual user sessions to observe user behavior and discover their pain points. Read our guide to learn about the best heatmaps tools. 

• Funnels can be set up to explore different paths to conversions

• Measurement tools allow you to evaluate each feature’s user engagement

What are some great Product Analytics Tools?

How do Product Analytics platforms work?

By tracking the actions users take on your site—all of the clicks, pageviews, formfills, swipes, and other activities involved in navigating a digital product. 

In our opinion, there are three requirements for a truly great product analytics platform.

1. Automatic Data Capture. Ingesting and processing every bit of user data from the beginning is key, because manual tracking requires advance planning and uses valuable engineering time. You don't want to be playing catch-up with your data! Without automatic capture, your dataset will never be fully complete.

2. A data science layer that brings your analytics efforts to the next level. It predictively indicates hotspots, logjams, and red flags in the user flow, steers your teams towards insightful questions, and shows you the invisible steps between the steps users take. This means you can surface insights even where you are NOT looking! Data science encourages you to make effective decisions with real information for maximum gains.

3. Integrated Session Replays, so you can see exactly what customers see. Now you can identify and reproduce any situation where users encounter friction. You’ll learn whether users are finding your highest-value features easily, see where people are getting stuck, and understand why.Session replays add rich visual context to traditional product analytics metrics, so your quantitative data and qualitative data support each other. And fully integrated means no wasting time going back and forth between different tools.

In short, a good product analytics platform should let you answer any questions you have—even ones you haven’t thought of yet.

What Can I Expect From A Product Analytics Tool?

Any good product analytics tool will also have the following features:

• Virtual Events provide endless flexibility with the data you’ve autocaptured. Put events into any context that’s important, and answer any question you need—even retroactively. Prove and disprove multiple hypotheses without having to rewrite code. Different teams can assign multiple labels to the same interactions, so your dataset stays clean yet accessible.

• Cohort Analysis lets you see how many users are returning within specific time periods. Behavioral analysis helps you understand how your customers react to your product, so you can determine how and when to reach them to cultivate the greatest rates of retention. This is especially useful for finding your product-market fit.

• Data Governance keeps your information safe, clean and organized. You can easily categorize events, segments, reports, personal sandboxes, and staging environments, while role-based project access and default user roles give you total control over who views and modifies your dataset.

• Behavioral Segmentation offers much greater refinement than demographic segmentation. You can sort users according to the actions they take in your site, see who your best customers are, and learn what they like to do.

• Integrations allow you to enrich your dataset to answer more complex questions. You can connect to external sources (CRM, email marketing, testing, accounting, payment systems, etc.) and run analysis on their information. The more integrations your product analytics can accommodate, the better.

• Mobile support lets you streamline data collection across devices without the hassles of broken tracking, or inconsistent tagging schemas. Mobile SDKs make it easy to combine data from different platforms into a single event or property. This way, you get a trusted view of user behavior across iOS and Android, and your users get the frictionless mobile or cross-channel experiences they deserve.

• Data warehousing is important! It’s the ease with which you can set up and maintain data access. Many systems require engineering time and resources to create this pipeline, but Heap Connect gives you an easy connection to your data warehouse. All data entering or leaving our infrastructure is securely encrypted with TLS/HTTPS. This is especially valuable for enterprise companies with lots of data and scarce engineering resources.

• Security and compliance procedures are critical to handling your sensitive information. Each account’s data must be logically separated, with access protected by authentication and authorization controls, and all cloud databases encrypted at rest.

When a tool has most of these, it lets you give customers more of what they respond to—and less of what they don’t. The result? You can create experiences that are most enjoyable for users—and most profitable for you.

Is the new Google Analytics (GA4) a good tool for Product Analytics?

Google Analytics was one of the first analytics tools, and best of all it was free. But it was never built for the depth and sophistication of a modern customer journey. GA4 brings major changes: event-based models, more views, new engagement metrics, more detail across the board, and “codeless tracking” that doesn’t require engineers to set up. 

However, you’ll still have to decide what events you want to track in advance. So you still end up with an incomplete, biased dataset. And the other limitations are significant:

• No way to surface things you’re not already tracking.
  There’s no way to see user behavior as it actually happens.

• No retroactive data capability.
  You’re limited to collecting data on events from the moment you decide to track them. 

• Limited integrations and customizations. This is a big problem when trying to do more things to make your data useful.

• Middleware is mandatory. While a free sample of BigQuery is included, you still have to pay for the data.

• “AI and predictive metrics” are basically alerts.
  You still have to manually define conditions you deem important or critical.

• No way to analyze hidden behaviors. Automated results may save some time, but they don’t qualify as true insights.

Together, we think these make GA4 less than ideal for building a great user experience. To do that right, you need the deepest insights and actionable information about your users.

You can only fix non-performing features and optimize the effective ones by understanding in detail how users interact with what you build, and what users like best. This way you can engage them longer, upsell them more, and keep users happily coming back again and again.

To learn more about GA4, read our complete guide.

What is Mobile Product Analytics—and why is collecting mobile data so important?

Mobile analytics deals with analyzing user behavior related to their smartphones, tablets, and apps. When mobile teams can understand how users interact with their mobile devices, they can assess where to improve things like user experience, user engagement, and conversion rates. 

Your mobile teams work extra hard to deliver an experience that’s easy and intuitive for users. 

They face struggles that other teams rarely—or never—have to face.

• Manual data collection is messy.

Each mobile platform has its own way of collecting data, and since the platforms changed often, teams had to keep updating their tracking methods.

• Dirty data pollutes the entire lake.

With so many updates and re-tracking efforts, it’s hard to know which data is trustworthy and which isn’t. Incorrect data is useless at best, and  at worst, it’s actively harmful to business goals!

• Massive data volume overwhelms teams. 

Mobile applications generate a vast amount of data, which is challenging  to collect, store, and analyze effectively. 

• Integration from many sources obscures the big picture 

Integrating social media and third-party mobile data involves many formats and structures. When teams are left with incompatible data, they can’t see what users do as they move from web to mobile, or vice versa.

• Mobile devices have complex commands and actions.

Laptops are simple—you type and you click, and there’s a nice big screen. Mobile devices are tiny by comparison, but have way more commands! Finger swipes, scrolls, drags, zooms, typing, drawing, facial ID, not to mention portrait and landscape modes. Whew.

How does a mobile analytics solution work?

Mobile analytics automatically collects data from mobile apps and analyzes it to provide insights into user behavior and app performance. A software development kit (SDK) is typically incorporated into the mobile app, which then tracks user behavior and sends data to the analytics platform. The platform processes the data and provides metrics and reports for you to analyze.

What are the top metrics I can analyze with mobile analytics?

• User engagement

• Conversion rates

• App installs

• Active app users

• App crashes

• Number of app downloads

• Cost per install (CPI)

• App store optimization (ASO)

• Daily active users (DAU)

• Feature adoption 

• Mobile Heatmaps

• Session length

• Retention rate

• Click-through rate (CTR)

• Average revenue per user (ARPU)

To get the full picture of your mobile users, you need a tool that can automatically capture all behavioral data from mobile devices, all the time.

See how apparel company Alo Yoga uncovered a more detailed story from customer acquisition through site browsing and purchase.

When should my company invest in Product Analytics?

That’s an easy one: anytime you wish to affect and improve user experience!

When you’re curious about the experiences users have on your site. You’re concerned with making interactions smoother. You want to build a product people like. Or better yet, love!

• If you're a small company:

  • Discover your product-market fit

  • Conduct user and market tests

  • Develop your MVP into an optimal offering

• If you're a mid-market company:

  • Ensure that you scale properly

  • Develop your data value chain

  • Increase your retention and conversion rates 

  • Lower your customer churn

• If you're an enterprise company:

  • Perfect your data storytelling

  • Ensure that you continue to evolve with the market

  • Beat your competition (who also uses product analytics)

  • Avoid disruption by the hungry startups out to eat your lunch!

How do I choose the right Product Analytics for my situation?

The best way to get maximum insights is to start with the end in mind. Autocapture will do the hard work of collecting data for you, but the real value in product analytics comes from how, and how often, you use it to develop thorough processes within your organization.

The more ways you flex your data, the more insights you will get. 

• Be laser-focused on the outcome. What are your business goals, and how will data help you achieve them?

• Set your KPIs. What are important milestones? How will you know when your situation has improved or your problem has been solved?

• Establish targets. Product analytics can even help you figure out where to aim. See how many (and which kinds of) customers use different elements of your product. Notice what’s performing well and what isn’t.

• Have objectives for your objectives. You can’t be too granular when tracking data. Get as specific as you can with each step. As performance increases, make sure you know what it means.

• Be open to exploring. Keeping spreadsheets of all the events and properties you want to track is tedious. Heap tracks all your data and keeps it organized so you can ask any question you want, at any point in the process.

How should I approach implementation?

Don’t set your strategy in stone. Keep implementation a fluid process, and evolve with every new milestone:

• Insights

• Sales targets

• Business goals

• Website features

• Changes to the product

• New ideas produced by your experimentation

Make sure you review your plan regularly to update goals, metrics, and reports. This is easiest with a product analytics system that has the most flexibility around events and tracking, in order to fast track your implementation and avoid delaying the time to value.

Ideally you can choose the product analytics solution that does the engineering for you.

What are some major platforms in Product Analytics?

There are many providers in the product analytics space. And while of course we recommend Heap, there are other leading solutions.

Mixpanel is a self-serve product analytics solution that helps companies build better products through data-driven decisions. It provides insights into user behavior, engagement, and conversion funnels, allowing product teams to gain a deeper understanding of how users interact with their products. One of Mixpanel’s strengths is measuring the success of launches and campaigns. 

Learn more about Mixpanel and its alternatives.

FullStory is a digital analytics platform that helps businesses understand how customers interact with their websites and mobile applications. Upon install, FullStory captures user sessions, including mouse movements, clicks, scrolls, and keystrokes, as well as device and browser information. The platform enables companies to monitor user behavior, analyze customer journeys, identify opportunities for improvement, and fix issues that may be causing friction in the user experience.

Learn more about FullStory and its alternatives.

Pendo is a product experience platform that helps businesses understand and improve the user experience of their digital products. Pendo is more than just a data tracking or surveying platform, offering tools for product analytics, user feedback, and in-app guidance. Its strength is delivering personalized onboarding and feature walkthroughs to optimize user experiences.

Learn more about Pendo and its alternatives.

GA4 is the latest version of Google Analytics. It offers improvements over its predecessor, Universal Analytics (UA) by using event-based tracking for more detailed data on user interactions. GA4 provides enhanced cross-device tracking, deeper integration with Google Ads and AI, a user-centric focus, a simplified interface, and improved reporting and visualization to return better insights and more comprehensive analytics to optimize user experiences and marketing strategies.

Learn more about GA4 and its alternatives.

Amplitude provides tools and features to track, analyze, and visualize user interactions within digital products. It offers event-based tracking, allowing product teams to understand user actions and pinpoint valuable customer behavior patterns. Amplitude enables product managers to dive deep into user data, create cohorts, and perform advanced analysis to uncover trends and patterns.

Learn more about Amplitude and its alternatives.

What makes Heap’s Product Analytics stand out?

Heap approaches product analytics differently, beginning with our philosophy of exploration. We believe that product-market fit is the ultimate measure of success for companies of every size.

Why stumble into this balance with guesswork, when you can map the territory? With Heap, you can create any hypothesis you want to test, at any point in the dev process, and the data will be there for you.

Why is Heap the ideal Product Analytics solution?

Heap is the only digital insights platform that gives you complete understanding of your customers’ digital journeys, so you can quickly improve conversion, retention, and customer delight.

Now you’re free to be both an artist and a scientist with your data. 

Heap gives you the most complete and systematic way to test, measure, and improve product-market fit. And it’s super easy to implement!

• Heap enables codeless product insights, with no engineering required to run product analyses.

• A single javascript snippet autocaptures every click, swipe, tap, pageview, and fill, offering complete access to your historical data.

• Heap provides full historical data for new events, even the ones events you never thought to define or track.

• Powerful data science surfaces insights you didn't even know you were looking for!

• Fully integrated session replays let you step directly into the shoes of any and every customer you choose..

No manual tracking, advance planning, or engineer time is required. 

You can also:

• Add new behaviors for Web, iOS, and Android without engineering. 

• Enrich data with sources like A/B testing, CRM systems, and email providers. 

• Audit, verify, and modify behaviors and events. 

• Relax knowing PII privacy is protected.

See how our customers are using Heap in:

• SaaS

• eCommerce

• FinServ

• B2B

You have lots of choice when it comes to choosing product analytics…but just having the tools is not enough. You need to use them wisely, with support from a first-class team. 

Your data is a vast world to explore. 

Heap gives you a treasure map.