What Is behavioral analytics?

Behavioral analytics refers to the analysis and observation of how users interact with a website, mobile app, or other digital product. It involves collecting data on the actions that users take and then analyzing that data to identify trends, patterns, and insights into user behavior. Companies like Flywheel track all user interactions automatically — both on your website and in your product.

The core focus of behavioral analytics is on understanding user actions and interactions, like where they click, tap, scroll, and type on a site or app. This provides invaluable insight into how users really experience and engage with digital products in the real world.

By surfacing details on how users navigate interfaces, locate information, fill out forms, and more, behavioral analytics shines a light on the human actions and behaviors that sit behind the data and metrics. It essentially helps create a visual map of the user journey.

Some key elements that behavioral analytics can reveal:

• Where users most commonly click, tap, hover, or scroll on a page

• What content users engage with most frequently

• Form fields or buttons that present bottlenecks in conversion funnels

• Pages or user flows with high exit or bounce rates

• Areas of confusion where users struggle to find information

• Parts of the interface that receive little attention from users

These kinds of behavioral insights are extremely useful for optimizing and improving the overall user experience. They help identify usability issues that may frustrate users as well as opportunities to guide them more seamlessly towards key actions and conversions.

In short, behavioral analytics provides businesses and digital teams with an x-ray into how real users interact with their online touchpoints. It transforms abstract data on traffic, clicks, and form submissions into visual insights on user psychology and behavior.

Types of behavioral analytics tools

Behavioral analytics encompasses a range of tools that provide insight into how users interact with digital interfaces. Here are 4 of the main types of behavioral analytics tools:

Heatmaps

Heatmaps visually display where users are clicking, tapping, scrolling and hovering on a page. These heatmap overlays reveal user behavior patterns and highlight areas that attract attention or are being ignored. Common uses of heatmaps include:

• Identifying clickable elements that get overlooked

• Optimizing call-to-action button placement

• Reducing scrolling by moving important content higher up

• Detecting undesirable ad placements or dead zones on a page

By revealing where users focus their attention, heatmaps help recognize opportunities to improve page layouts and content prioritization.

Session recordings

Session recordings capture videos of real user interactions on your site or app. Watching actual sessions provides qualitative insight into usability issues and pain points. Session recordings are helpful for:

• Witnessing how users navigate your user interface

• Identifying confusing elements in the user flow

• Diagnosing checkout abandonments and form drop-offs

• Understanding complex customer support issues

Viewing session recordings allows you to gather contextual insights and see user behavior first-hand.

Funnel analysis

Funnel analysis evaluates each step of your conversion funnel to find leaks and opportunities to optimize. Key metrics examined usually include:

• Impressions

• Clicks

• Add to carts

• Checkouts

• Purchases

This reveals where your funnel is losing traffic so you can focus on reducing fallout at each stage. Funnel analysis provides data to guide improvements to landing pages, product pages, pricing and checkout flows.

A/B testing

A/B testing, also known as split testing, compares two versions of a page to determine which performs better. This involves:

• Setting up an experiment with a control and variation

• Driving traffic to both versions

• Measuring conversion rates

• Applying statistical analysis to identify the winning variation

A/B testing enables data-backed optimization of page designs, content, calls-to-action, pricing, and other elements. Iterative testing leads to continuous improvement over time.

In summary, heatmaps, session recordings, funnel analysis and A/B testing all provide actionable data to understand user actions and optimize the customer experience. Combining different behavioral analytics approaches provides both quantitative and qualitative insights to guide digital product improvements.

Key benefits of behavioral analytics

Behavioral analytics provides many benefits that can help businesses optimize experiences, increase conversions, and drive growth. Here are some of the top reasons to use behavioral analytics:

Identify friction points

One of the biggest values of behavioral analytics is shining a light on friction points and pain points in your customer journey. For example, "rageclicks" can show where users struggle to find a certain button or click repeatedly on the same object. Session recordings reveal when users get confused or lost trying to complete a process.

By identifying friction through behavioral data, you can pinpoint exactly where users are getting stuck and why. This enables you to fix confusing workflows, simplify complex pages, and remove obstacles to conversion.

Understand user attention

Heatmaps and scroll maps from behavioral analytics tools vividly illustrate what captures user attention on a page and what gets ignored. You can see what visuals users focus on, which areas get glanced over, and where their mouse hovers the most.

These attention maps are like x-rays into the user mind, highlighting the page areas and content that resonate most. This helps you double down on effective design and further test versions that better hold user attention.

Get real-time feedback

Rather than waiting weeks or months to get survey feedback, behavioral analytics provides instant feedback on the customer experience. As soon as someone visits your site, the behavioral tool will start detecting interactions, emotions, and pain points.

This real-time stream of insights enables you to iterate and test changes to your site much faster. You don't have to wait long periods to understand whether a new feature drives engagement or a redesign hurts conversion. You'll know right away based on user behavior data.

Drive buy-in for changes

Heatmaps, session recordings, and other behavioral insights make a very compelling case when proposing changes to your website, app, or campaigns.

Rather than just relying on opinions, you can use concrete behavioral data showing that a certain button placement increased conversions or that fewer people engaged with a redesigned page layout.

This makes it much easier to get buy-in from stakeholders when suggesting changes. Behavioral analytics provides the evidence and validation needed to confidently make updates.

Who uses behavioral analytics?

Behavioral analytics provides powerful insights that a wide range of roles and teams can leverage to improve business outcomes. Here are some of the most common users of behavioral analytics:

Marketers

For marketers, behavioral analytics is invaluable for optimizing user journeys to increase conversions. By analyzing customer onboarding funnels, marketers can identify where users are dropping off and fix pain points in the conversion process. Heatmaps help marketers understand what users pay attention to on landing pages and where their eyes are drawn on the page. This enables better page design and layout. Behavioral data also empowers smarter personalization and segmentation so marketers can provide targeted experiences for different user cohorts.

Sales teams

Sales teams can leverage behavioral analytics to better understand user intent signals and identify the hottest leads more likely to convert. Session recordings allow sales reps to see exact user behavior sequences that indicate buyer readiness. Funnel analysis shows where prospects fall out of deals and enables sales teams to proactively address obstacles. Behavioral analytics also provides a 360-degree view of accounts so salespeople know the full history of engagement.

Customer Success

Customer Success teams use behavioral analytics to identify common points of friction in digital products that lead to support tickets. This allows them to proactively fix usability issues and reduce support volume. By analyzing help documentation and self-serve resources with behavioral data, support teams can also optimize knowledge bases and improve findability of answers. This leads to faster resolution of customer issues. Session recordings also aid support agents in replicating user issues.

Data analysts

Skilled data analysts can leverage behavioral analytics to gain deeper and broader understanding of customers. User behavior data allows analysts to segment users based on actions, not just basic attributes. Funnel and cohort analysis provides windows into the user journey over time. Integrating behavioral data with other sources like CRM data enables analysts to enrich customer profiles for a holistic view. This powerful perspective is invaluable for identifying new opportunities and gaining competitive advantage.

The richness of behavioral data unlocks insights across the customer lifecycle. Any role focused on optimizing user experience and business outcomes can benefit from behavioral analytics.

How behavioral analytics works

Behavioral analytics works by tracking and analyzing how users interact with your website or mobile app. The process involves three key steps:

Collecting user interaction data

The first step is using tracking code to collect data on how users engage with your digital product. Products like Flywheel track these events automatically, without the need for engineering time. These events can include:

• Clicks

• Scrolls

• Taps

• Page views

• Buttons clicked

• Forms filled out

• Videos watched

• Products viewed

Essentially any user action can be tracked to gather quantitative data on user behavior.

Analyzing the data for insights

Next, the behavioral analytics software analyzes all of the user data that was collected. This analysis looks for trends, patterns and insights in the data. In Flywheel, we create collections of events called Features and analyze their change over timev

Some key insights the analysis aims to uncover include:

• Identifying areas of friction in user journeys

• Finding parts of the site users engage with most/least

• Understanding how users navigate the site

• Seeing where users are exiting or abandoning

• Identifying effective page designs and flows

One of the most powerful ways that we gather these insights are by filtering our session recordings by feature usage. This is an out-of-the-box filter ability of Flywheel.

Providing visual reports and recommendations

The last step is taking all those user behavior insights and presenting them in a visual way to make it easy to understand for non-technical people.

Common report types include:

• Heatmaps showing click patterns

• Session recordings to see user struggles first-hand

• Funnel analysis of drop-off points

• Cohort analysis to compare behaviors

• Recommendations to improve specific pages and user journeys

These visual reports make the data actionable by clearly showing opportunities to optimize the site experience.

How is behavioral analytics different From google analytics?

While Google Analytics focuses on site traffic metrics and overall analysis, behavioral analytics digs deeper into the qualitative user experience data behind the numbers.

Some key differences between behavioral analytics and Google Analytics include:

• Data focus: Behavioral analytics centers around user experience data - how users actually interact with your site or app. This includes session recordings, heatmaps, scroll maps and click tracking. Google Analytics looks more at traffic volumes, channels and overall analytics.

• Qualitative insights: Behavioral analytics tools provide qualitative data by recording real user sessions on your site and generating heatmaps. This enables you to see real examples of UX issues and where users struggle. Google Analytics lacks this qualitative context.

• Advanced testing: Behavioral analytics platforms have built-in A/B and multivariate testing capabilities to test and optimize user flows. While Google Optimize can enable basic A/B testing, behavioral analytics tools offer more advanced options.

• Segmentation: Behavioral analytics allows for more sophisticated segmentation and cohort analysis based on user actions and engagement. Google Analytics segments users based more on firmographics and traffic source data.

So in summary, behavioral analytics provides a deeper layer of qualitative UX data, advanced testing capabilities, and user-focused segmentation to complement the higher-level traffic analytics from Google Analytics. Together they offer a comprehensive view of both website metrics and user experience optimization.

Choosing a behavioral analytics tool

When selecting a behavioral analytics platform, there are a few key factors to consider. For a comparison of the top companies in this space, check out our page on product analytics tooling.

Identify your needs

First, think about your specific needs and which features are most important. Do you want advanced segmentation and cohort analysis? Heatmaps to see where users click? Session replays to view user recordings? A/B testing capabilities? Identifying your must-have features will help narrow your options.

Know your space

B2C and B2B companies require different types of behavioral analytics. Modern products like Flywheel focus on showing account-level analytics in addition to user-level analytics.

Evaluate data and insights

Look at the types of data each tool captures and the insights they provide. Can it track every user action? How does it visualize behavioral trends? Make sure the tool provides the depth of analytics and reporting you need to gain a comprehensive understanding of your customers.

Assess ease of use

Consider how easy the tool will be to implement and use day-to-day. Look for an intuitive interface that allows you to quickly analyze data without complex setup or coding skills needed. The platform should have detailed onboarding and ongoing support.

Compare pricing and integrations

Factor in pricing tiers based on your needs and budget. Also look for integrations with analytics, CRM, email marketing and other tools you already use to create a seamless data stack. Having behavioral data flow between platforms provides more holistic customer intelligence.

Prioritize your must-haves

Make a list of your top priorities and needs, then evaluate tools to find one that best matches your requirements. Comparing the key differentiators will help you choose the ideal behavioral analytics platform to provide the greatest value and ROI.

Implementing behavioral analytics

Getting started with behavioral analytics requires a few key steps:

Add tracking code to your website or app

The first step is to add the tracking code from your chosen behavioral analytics software to your website or mobile app. This allows the tool to start collecting user interaction data. Our version of this code is called Flywheel.js.

Most tools provide step-by-step instructions on how to properly install the tracking code. Be sure to add the code to every page you want to track.

Integrate with other tools

Next, you'll want to integrate your behavioral analytics tool with other platforms you use, such as your CRM, marketing automation software, heat mapping tools, etc.

This allows you to combine behavioral data with other customer information for more complete insights. Most tools offer integrations and APIs to connect with other martech solutions.

Analyze the initial data

Once your behavioral analytics tool starts collecting data, you can begin analyzing user activity on your site. Look at high-level metrics like most visited pages, buttons clicked, and navigation paths.

You can also dig deeper into data for specific user segments. Identify where key actions like form fills or checkouts are being abandoned. See if certain pages have high exit rates.

This analysis will reveal opportunities to optimize pages and user flows to improve engagement. Be sure to continue monitoring the data over time to identify trends and see the impact of changes.

Future of behavioral analytics

Behavioral analytics is a rapidly evolving field, with some key trends shaping its future:

Integration with AI and machine learning

AI and ML will allow for deeper analysis of behavioral data. By combining behavioral analytics with predictive capabilities of AI, businesses can gain more actionable and personalized insights. AI can help uncover hidden patterns and enable recommendations based on user behaviors.

Rise of automation

Automating parts of the behavioral analytics process will allow for faster insights. Automatically capturing user sessions, analyzing key trends, and generating reports will make behavioral analytics more scalable. The ability to immediately surface issues and opportunities based on user data will become essential.

The automation of behavior analysis along with the application of AI and adaption to mobile will take behavioral analytics to the next level. Companies will be able to extract more value from user behavior data and use those insights to constantly refine the customer experience. Behavioral analytics will become a core component of customer intelligence.