If your product team is assuming or guessing what your customers and users want, you’re setting your product up for failure. Although we might think we know our customers well, we need to root our decisions in data — not assumptions.
If you interviewed the teams that built the best products, in any industry, you’ll start to see a trend. They used behavior analytics to make data-backed product decisions.
User behavioral data is a type of product analytics that enables product teams to understand your users and how they’re using a your product or service. Behavioral analytics captures engagement data on how users use, interact, and adopt your product, its flows, and its features.
In this article, we’ll define behavior analytics, explore how they should be used, and provide tips on how you can get started.
What Is User Behavior Analytics?
User behavior analytics track how end-users, customers, or visitors engage with and use a product, service, or website. User behavioral analytics enables product managers to track, measure, and analyze your product usage, map your journeys and user flows, identify friction areas, build user cohorts, track event conversions, and more.
Behavior analytics paint a clear picture and provides data into the gaps that traditional app analytics may not answer. For example, typical analytics might be able to tell you how many visitors a specific page gets in a day or week and how much time they spend on the page, but it can’t tell you what action a visitor is taking or where they raged quit an application — but behavior analytics can.
With behavioral analytics, product teams are able to take these insights to make data-driven decisions and create a useful product and intuitive user experience which ultimately drives product adoption.
Behavior analytics is typically separated into two groups: “user properties” and “event properties.”
What are user properties?
User properties are unique traits specific to each individual user. User properties include attributes such as:
- Unique or non-unique
- Active or non-active
- New or not new
Additional user property examples include how active they are, the size of their company, or how much data they’re storing in your platform.
User properties don’t change based on the user’s interactions with your website or app and will stay consistent even as events or behaviors change.
This user-level data empowers product teams with the ability to understand things such as:
- Where are users clicking?
- Where are users encountering friction points?
- Are users adopting new features?
- Is our onboarding experience and flow working?
- How long does it take users to convert?
- How effective are various in-app messages?
- How can we push users into various flows?
What are event properties?
Event properties are the actions a visitor or user takes when engaging with your platform or website. Common user events to track include engagement and usage events such such as:
- Making a purchase
- Inputting data in a field
- Interacting with a feature
- Identifying the sequence of events that led a user to a specific action
Again, the specific event properties you track will depend on your unique website or app. Event properties will be the same for each user.
7 Types of User Actions Tracked with Behavior Analytics
Here are seven specific actions to track with behavior analytics.
1. Clicks
When users click on an image, text, or another page area, they often expect to be brought to a new page or for a function to run. But sometimes, pieces of a website or app that users assume should be a link (such as images or logos) don’t lead anywhere — something that can be incredibly frustrating to users trying to find more information.
Tracking clicks can help you understand user behavior and what visitors expect. You can refine and edit your website to match their expectations and improve user experience.
2. Page scrolling
Scroll behavior tells how far down a user views your page before either clicking a link to a new page or leaving the website or app. Knowing where users are likely to stop scrolling can help you ensure all your most important information is easily visible and accessible.
3. Mouse movements
Mouse movements follow a user’s cursor as it moves around the screen. It can give you an idea of where the user is paying attention to and what information they find most appealing.
While mouse movements can be insightful, they often lack contextual information. When paired with other user engagement metrics, you’ll benefit most from this kind of behavioral tracking.
4. User feedback
In-app surveys and nudges for product feedback are another critical component of behavioral analytics. User behavior insights allow you to make recommendations directly from your users as they interact with and engage with your website or app.
Asking for feedback takes the guesswork out of understanding your audience so you can make even better decisions.
5. Overall page navigation
When clicks, scrolling, and mouse tracking all come together, you can get an overall feel for how your users navigate different pages of your website or app. See what information they’re interested in, where they’re pausing to read more information, and what CTAs or images encourage them to move on to the next page.
With this information, you can rearrange the contents of your page to deliver a better user experience and improve your conversion rates.
6. Drop-offs
Knowing when a customer chooses to leave your website or app is just as important as understanding what information and content they engage with. With behavior analytics, you can find the point where your user loses interest and drops off.
Drop-offs are a sign that users are experiencing friction in their journey. Identifying high drop-off areas empowers you with the data to overcome these friction areas and build better experiences that enable end-users to achieve their desired outcomes.
Drop-offs are a sign that users are experiencing friction in their journey.
7. Event completion
Standard analytics allow you to track significant conversions, but behavior analytics lets you look at more detailed event completions to track the micro-conversions that move users along the sales process.
Measure when a user interacts with a particular feature, engages with a CTA, or completes a form.
What Tests Can Be Run with Behavioral Analytics?
When you start collecting behavioral data, you’ll be empowered to run multiple types of user analyses and experiments to refine your product experience, based on the actions you want your users to take.
Here are the most common:
1. A/B tests
A/B experiment testing allows product managers to test two different variants against one another – whether that is the location of a new smart tip, the copy of a CTA, the number of fields on a form, and so forth.=
A/B tests allow product teams to take the guesswork of our product development and make product changes based on real data.
2. Funnel analysis
Every product team has a conversion goal for their website, app, or product. Anywhere along this user journey presents the opportunity for users to advance or fall off. A funnel analysis allows product managers to inspect various stages of that customer journey to fix user friction points and learn from experiences that are high converting.
3. User segmentation
User segmentation allows product teams to create cohorts of users and learn based on the profiles of these user segments and personas. Product teams can use behavioral data to group different types of users together, and then learn what works for different cohorts.
Analyze user behavior and track product usage with Whatfix Analytics
Enable your product managers to easily track and analyze user behavior and product usage with Whatfix Analytics, a no-code event tracking solution. With Whatfix Analytics, capture all user actions without engineering support, understand product usage, identify dropoff areas, understand feature adoption, map user journeys, build user cohorts, and make data-driven product decisions.
Benefits of Behavior Event Data Tracking
Implementing and tracking behavior analytics takes time — but the rewards are high. Here are some of the biggest benefits of tracking behavior event data:
- Better user experience means higher product adoption: Equipped with behavioral analytics, product teams are empowered to make data-driven decisions that influence your product experience – which helps to drive product adoption.
- Understand your users better: With deep user behavior insights, product teams are able to understand what their users engage with the most, what distracts them, and how they interact with your product’s interface.
- Improved conversion rates. When your website or app works the way your users expect it to, you can increase conversion rates and keep your audience engaged longer.
- Higher customer retention. Improving your user experience helps reduce time-to-value and helps users find their “aha!” moment with your product. Helping present the real value of your product allows customers to find ROI from your tool, which is fundamental to customer retention.
- Decrease service and support costs. Creating an intuitive product or app will reduce confusion and complications for your users, reducing the amount of service and support you need to provide.
- Increase customer satisfaction. Happy customers mean higher customer satisfaction — and satisfied customers are more likely to recommend your brand to friends and family.
5 Steps to Get Started with Behavior Analytics
Ready to set up your behavior analytic tracking? Here’s how to get started.
1. Build a behavior analysis team
Behavior analysis is a division entirely on its own. While it shares many similarities with traditional analytics, it deserves undivided (or at least specific) attention from experts who understand how to read the data.
Behavior analysis requires understanding human behavior and making educated assumptions based on the information provided. Before you begin building your behavior analytic tracking system, create your team. Having analytic experts on your side during the implementation phase can ensure you’re checking all the right boxes.
2. Set your behavior analytic goals and metrics
As with any analytic endeavor, knowing what you want to track and why is fundamental for building a successful behavioral analytic system. Before you dive too deep, set your behavior analytic goals and metrics.
Look at where your team might have gaps from traditional analytics. Are users failing to move beyond your homepage? Are they struggling to find and engage with special features? Is your support team seeing a lot of confusion about how to navigate your app?
A few examples of user behavioral metrics to track include:
- Daily active users (DAU) or monthly active users (MAU)
- # of cart abandonments
- % of new users who completed their onboarding flows
- # of users using a specific feature
- # of free trial to paid account conversions
- # of users who started to fill out a form but didn’t complete it
Begin with a problem to solve. Then map and benchmark your product adoption metrics. Then discover what behavioral analytic tools are available to you.
3. Map out your processes
Mapping out your processes before you start tracking can keep everyone on the same page and ensure you’re getting the most from your analytics.
Within your process, consider:
- What particular KPIs and metrics you’re going to track
- How you’re going to measure those KPIs and metrics
- How you’re going to store data and information
- How often you’re going to pull data and information
- What reporting process you’ll follow for sharing data and information with other relevant departments and teams
4. Choose explicit or implicit event tracking
Event tracking is either explicit or implicit. Explicit event tracking requires manual tagging of events, while implicit collects all user interactions and data automatically.
Implicit event tracking is easier initially because it doesn’t require custom coding, but because it captures all information and data, your team is left sifting through more information at the end to find what is relevant and what is not.
Explicit event tracking requires developers to collect relevant information based on their metrics and goals, but the end product is much cleaner and more specific.
Each style has its benefits and drawbacks, so choosing based on your unique goals and the team’s skill level is important.
Read our comparison guide that breaks down the differences between explicit and implicit event tracking, the use cases for each, and the benefits and challenges for each.
5. Implement your strategy and start tracking
With the foundation set, you’re finally ready to start tracking. Remember, making changes and adjustments to your tracking process is okay. As your goals change, so will the metrics you track.
Challenges to Implementing Behavior Analytics
There are barriers to setting up behavior analytics tracking – here are the most common challenges organizations face when looking to implement behavioral analytics:
- Setting the right goals: Behavioral analytics will unlock a wealth of data. Product teams must focus on granular product-related challenges and set the right goals to accompany this problem. Product teams will fail to find the ROI of behavioral analytics without setting the right goals.
- Lack of engineering and technical resources: Product teams need developers to help implement and manage behavioral analytics strategies for custom explicit event tracking. Without the support of engineering teams, organizations should look to implement an implicit event tracking framework.
- Too small or dirty data sets: A challenge when starting with product analytics is working with unclean data, or with small data sets. Both of these present data that may not be representative and raise false flags, which can lead product teams down rabbit holes based on poor data quality.
Types of Behavior Analytics Software
There are many types of tools product teams use to track customer and user behavior analytics. The most common types of behavioral analytics software includes the following:
1. A/B testing tools
An A/B testing tool empowers product teams to test new changes to a product or website and collects data on which variation performs better. These A/B test lets you directly compare two similar but slightly different pages to see how users interact with each. An A/B test acts like a controlled experiment so you can confirm a hypothesis and understand which version of your platform performs best.
For example, you might want to test different CTAs. Running an A/B test can allow you to push out different versions of your web page with different CTAs to see which gets the most clicks.
Examples of pure, stand-alone A/B testing tools include Optimizely and Adobe Target.
2. Digital adoption platforms (DAPs)
Digital adoption platforms (DAP), also known as product adoption tools, provide product managers with the no-code content editing tools to create in-app guided content. They also provide real-time insights and information about how users engage with your app or product. With digital adoption tools, you can find areas where your users might need additional direction or support and opportunities for adoption improvement.
With product adoption tools, you can also keep an eye on what app features are most popular with your users and might not be getting much attention.
Whatfix has consistently been named the best digital adoption platform by real users on G2, and is used by over 100 Fortune 1,000 companies.
Analyze user behavior and track product usage with Whatfix Analytics
Enable your product managers to easily track and analyze user behavior and product usage with Whatfix Analytics, a no-code event tracking solution. With Whatfix Analytics, capture all user actions without engineering support, understand product usage, identify dropoff areas, understand feature adoption, map user journeys, build user cohorts, and make data-driven product decisions.
3. Heatmap tools
Heatmap tools show engagement with a page or website, including clicks and scrolling. With a heatmap tool, darker or red areas will show high-traffic areas. “Colder” areas typically appear to be purple or even black.
Knowing where your visitors are putting most of their attention can help you ensure you’re getting the right messages in front of them or determine what information they find most important.
Popular heatmap software includes Hotjar and FullStory,
4. Session and screen replay tools
A session or screen replay tool records video sessions of visitors exploring your website. Unlike heatmap tools, a replay tool gives your users’ actions context. You can see where users click on different parts of your page, but you can also see the order they move in and where they give up on completing a task.
However, screen replay tools are time-consuming. Unlike other types of analytics, you can’t just print out a report. You’ll need to be prepared to invest time into watching videos, but it can be well worth it in the end.
5 Best Behavior Analytics Software in 2024
Here are five of the best behavioral analytics software for product teams:
1. Whatfix
Whatfix is a digital adoption platform that provides no-code content creation tools that empower product managers to create in-app content, as well as capture and analyze product analytics.
With Whatfix, product teams can build in-app guidance such as step-by-step walkthroughs, product tours, onboarding task lists, and self-help support widgets within an application.
With Whatfix Analytics, capture user behavior insights into product usage and adoption. With Whatfix, you can identify dropoff areas, build user cohorts, measure feature adoption, map user journeys, and track custom event conversions.
With Whatfix Analytics, product managers are empowered to capture and analyze user behavior insights into how individual features, flows, and the overall products being used. With Whatfix, you can identify key drop-off spots, where users look for additional assistance, and what features or areas of the app users are most drawn to.
You can then adjust your user experience to reduce support queries, improve customer satisfaction, and improve adoption rates.
What sets Whatfix apart is its hybrid approach to event tracking that allows product managers to create custom, explicit event tracking parameters in a no-code, implicit-like implementation. This means there is no reliance on engineering to help get your event analytics tracking live.
Ready to get started? Set up a no-stress Whatfix demo now!
2. Amplitude Analytics
Amplitude Analytics is an explicit event tracking solution that provides self-service product data to help you increase conversions and engagement. With Amplitude, you can get new visibility into your customers’ digital journeys to build better experiences and drive revenue. Visualize the journey from start to finish to find exactly where users drop off or become disengaged.
Amplitude also features machine learning to help forecast future behaviors to help inform your business goals and decisions. With machine learning, you can predict users’ likelihood of performing certain actions, like buying or churning, to understand their behavior better.
One challenge of Amplitude is its technical nature, meaning organizations will require heavy engineering support to get their behavioral analytics implemented and managed.
3. Mixpanel
Mixpanel creates interactive reports that help you answer more questions about your product. Run different scenarios in just a few clicks to visualize engagement trends or see the impact of different product launches and changes.
Mixpanel lets you see who converts and why and identifies areas of friction. Segment users based on actions to closely examine how different users engage and perform with your app.
Like Amplitude, Mixpanel also requires heavy support from engineering to get its analytics set up.
4. Pendo
Pendo is another digital adoption platform that collects comprehensive product data across web, mobile, and apps to help better understand what users engage with across platforms and devices. Pendo is designed for teams of all sizes and skill levels, empowering teams without engineering or analytic experience to understand the information in front of them.
Pendo makes it easier to make data-driven decisions and build digital experiences that users enjoy.
5. Hotjar
Hotjar is the leading tool for creating heatmaps and recording user sessions and screens. With Hotjar, product managers are able to identify what draws your users’ attention and what gets ignored, and even compare behavior on different pages based on the device the page is viewed on.
Hotjar also offers feedback collection and surveys, allowing you to reduce the number of tools you use to collect and analyze behavior and expectations.
Behavior analytics can take your data and insights to a whole new level. By implementing a tool that lets you get to know your users and audience better than ever, you can build products and websites that truly meet their needs — not something you assume will meet their needs.
Before deciding on a behavioral analytics provider, answer the following questions to help guide your decision:
- Do I need behavioral analytics software for a mobile, web, or desktop application?
- Do I need to capture user and event data?
- Do I need access to data in real-time?
- Do I implicit or explicit event tracking?
- Will I have engineering support to help implement and manage our new analytics tool?
- Will I have the tools and resources to take action based upon our behavior data insights and create new in-app content, or will I need to rely on developers?
With Whatfix’s digital adoption and product analytics platform, non-technical product managers are empowered with no-code tools to implement behavioral event tracking, automatically generate analytic reports, set up and publish A/B tests, and create entire new user experience flows and in-app messages.
You get started by learning more about Whatfix Analytics here.
Request a demo to see how Whatfix empowers organizations to improve end-user adoption with no-code tools to create in-app content and capture product analytics.
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