Guide Listicle

Top 10 Customer Behavior Analysis Tools

Discover the top 10 customer behaviour analysis tools to help your business decisions be more data-driven.
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First, an overview

In the dynamic landscape of today's business world, understanding your customers has become more critical than ever. From the first interaction to post-purchase engagement, every step of the customer journey holds valuable insights that can shape your strategies and drive success. This is where customer behaviour analysis tools come into play, offering businesses the power to decipher patterns, preferences, and pain points in their customers' actions.

But with so many tools around, which one should you use? Our blog has got you covered. In this blog we will talk about the top 10 customer behaviour analysis tools and give you tips on using them, along with examples.

What Is Customer Behaviour Analysis?

Customer behaviour analysis refers to the process of examining and understanding how customers interact with your product, service, or brand. It involves collecting, interpreting, and analysing data related to customer actions to gain insights into their behaviour throughout the entire customer journey.

At its core, customer behaviour analysis aims to answer a few crucial questions:

  • What do customers do? It involves tracking and understanding the actions customers take, such as clicks, purchases, interactions with content, or engagement with specific features.
  • Why do they do it? Understanding the motivations and drivers behind customer actions helps uncover the underlying reasons for their behaviours and decisions.
  • How can businesses respond? Analysing customer behaviour enables businesses to tailor their strategies, marketing efforts, and product enhancements to better meet customer needs and preferences.

The essence of customer behaviour analysis is in trying to capture the "voice of the customer." When you understand what customers feel and think about your product, it helps you stay relevant in a highly competitive market.

Why Customer Behavior Analysis Matters

You don’t just need qualitative data to analyse your customer behaviour but also quantitative data that signals towards their preferences and other details. Some of these quantitative data points are:

  • Demographic and psychographic information: Who your customers are, their age, location, preferences, and lifestyles
  • Purchase patterns: When and how customers make purchases
  • Product preferences: Which products or services your customers prefer
  • Customer journey mapping: The steps customers take from expressing initial interest to making a purchase
  • Feedback and reviews: What your customers think about your product

These insights combined together help you with making better decisions across the funnel. Here are some ways:

  • Targeted marketing campaigns that perform better
  • Informed product and service development, directed towards things that matter to your users and paying customers
  • Increased customer retention and loyalty through personalised experiences and offers on your website and app
  • Better customer experience and conversion rates, again, through a personalised experience

Top 10 Customer Behavior Analysis Tools

Here is an overview of the top 10 customer behaviour analysis tools:


Mixpanel is a comprehensive analytics platform that helps you analyse user interactions on your app and website. Its primary focus is to assist businesses in improving customer conversion and retention strategies. Unlike traditional reports that primarily rely on sessions and pageviews, Mixpanel employs an event-based tracking system.

With features like event tracking, funnels, retention analysis, cohort analysis, A/B testing, user segmentation, user flows, impact analysis, and real-time analytics, Mixpanel empowers you to gain valuable insights into how users engage with your product.




Mouseflow is a web analytics tool that specialises in customer behaviour analysis by recording and analysing website interactions. It offers features such as session recording, heatmaps, form analytics, funnel analysis, feedback surveys, user segmentation, real-time analytics, mobile analytics, and error tracking.

With a focus on visualising user interactions, Mouseflow provides businesses with insights into how users navigate and engage with their websites, helping them optimise user experiences and address issues in real-time.

Importantly, it integrates with popular platforms like Hubspot, Optimizely, WordPress, and Google Analytics for a cohesive analytics experience.




Houseware is one of the best customer behaviour analysis tools. What sets it apart is its user-friendly approach and self-serve nature that helps you create powerful visualisations.

Houseware sits right on top of your data warehouse and lets you analyse any and all of your customer behaviour data to enrich your hunches and back up your plans. Apart from these features, this consumer behaviour analysis tool offers cohorts, user segmentation, and funnelling capabilities.



Google Analytics

Google Analytics is a powerful web analytics platform that offers a range of tools for customer behaviour analysis. It provides insights into user demographics, acquisition sources, and behaviour flow. With features like event tracking, conversion tracking, and e-commerce tracking, businesses can measure user engagement, optimise conversion funnels, and understand transaction data.

Custom reports and dashboards allow for tailored analytics, while real-time monitoring provides up-to-the-minute insights into user activity. Google Analytics is a comprehensive tool for businesses looking to analyse and enhance the online experience for their users.



Crazy Egg

Crazy Egg is a web analytics and optimization tool that provides a variety of features for in-depth customer behaviour analysis. It offers heatmaps, scrollmaps, and confetti reports to visualise user interactions, helping businesses understand where users click, scroll, and engage the most. User recordings allow for the qualitative analysis of individual sessions, while A/B testing and snapshots enable the comparison of different web page versions.

The tool also includes features like on-page surveys for user feedback, element tracking for specific website elements, and mobile analytics for insights into user behaviour on different devices.




CleverTap is a robust customer engagement and retention platform that includes powerful tools for customer behaviour analysis. Key features of CleverTap include comprehensive user segmentation, personalised messaging, and multichannel campaign orchestration.

It enables businesses to track and analyse user behaviour, allowing for the creation of targeted campaigns based on customer preferences, interactions, and lifecycle stages. CleverTap's real-time analytics, funnel analysis, and A/B testing capabilities empower businesses to optimise their user experiences and marketing strategies effectively.




Hotjar is a comprehensive web analytics and feedback tool designed for customer behaviour analysis. Key features include heatmaps, session recordings, surveys, and user feedback collection. With heatmaps, you can visually understand where users click, move, and scroll on their website.

Session recordings provide a playback of individual user sessions, offering qualitative insights into navigation patterns and behaviours. Hotjar's survey tools enable businesses to gather direct feedback from users, while features like funnel analysis and form analytics help in optimising conversion paths.



Lucky Orange

Lucky Orange is a web analytics and conversion optimization tool that facilitates customer behavior analysis. Key features include real-time analytics, heatmaps, session recordings, and live chat. It allows businesses to track user interactions in real-time, providing insights into visitor behavior, site usability, and conversion paths.

Heatmaps visually represent clicks, movements, and scrolls on web pages, while session recordings offer playback of individual user sessions for qualitative analysis. Additionally, Lucky Orange includes a live chat feature for real-time communication with website visitors, enhancing engagement and support. However, Lucky Orange's heatmap data is accessible for a limited 30-day window. So while it is ideal for immediate user issue identification, it is less suitable for tracking long-term trends on your website.




Pendo is a product analytics and user feedback platform that supports customer behaviour analysis. It offers features such as product usage analytics, user surveys, and in-app messaging. Pendo enables businesses to track how users interact with their digital products, providing insights into feature adoption, user journeys, and overall product engagement.

The platform also allows for the collection of user feedback through surveys and facilitates communication with users through targeted in-app messages. Pendo is designed to help businesses understand and improve the user experience by analysing customer behaviour within digital products.




Creabl is a software solution that empowers product managers to analyse website visitors' and customers' behaviour. This tool captures user sessions and creates insightful heatmaps for web pages. It can customise conversion funnels to help you turn visitors into paying customers.

The platform helps with user segmentation and cohort analysis. Custom funnels help you track user purchasing behaviour. Its retention tracking tools provide insights into feature usage, onboarding experiences, and churn risks.



User Behavior Analysis: Some Examples

Now that we have looked at different types of customer behaviour analysis tools, let’s get into some examples of customer behaviour analyses:

1. Funnel Analysis to Understand Friction

Funnel analysis tracks how users move through a series of steps, like the checkout process on an e-commerce site. For instance, if a business notices many users dropping off during checkout, funnel analysis helps identify the snag. It might prompt you to make changes like adding a guest checkout option or reducing the required fields to make the process smoother.

2. Path Analysis to Shorten Time-to-Value

Path analysis identifies the quickest route for users to achieve their goals. For instance, a company might use it to determine the steps new users need to take to use a product efficiently. This insight can lead to creating straightforward onboarding tutorials for a speedy start.

3. User Behavior Trends to Improve Adoption

Tracking user behaviour trends over time helps businesses identify patterns. For instance, if a business notices users repeatedly coming in from a specific region, they can use this insight to create targeted marketing materials.

4. Cohort Analysis to Improve Retention

Cohort analysis segments your users based on traits they share, like when they signed up or their go-to feature. It helps product managers track trends. For example, a business might check how many users from the last month stick around. By comparing different groups, they can determine which users might consider leaving.

5. Sentiment Analysis to Reduce Churn

Sentiment analysis uses machine learning to identify the sentiment of user feedback. This could include customer reviews or support tickets. For example, a business might use sentiment analysis to identify customers who are leaving negative reviews. It could then learn more about their concerns and resolve them.

6. Multivariate Testing Analysis to Increase Engagement

A multivariate testing analysis is a type of A/B testing that allows product teams to test many variables at the same time. For example, a business might use it to test different headlines, images, and call-to-actions on its landing page.

Best Practices for Using Customer Behavior Analysis Tools Well

1. Be Clear With Your Goals and Objectives

Think about what you really want to achieve with those data insights. Are you aiming to boost conversion rates, keep customers around, or fine-tune your marketing strategies? Having clear goals in mind ensures that when you dive into analysis, you're on a mission, and the results you get are not just information but actionable steps toward your objectives.

2. Collect Comprehensive Data

Gather information from various sources; consider web interactions, transaction history, social media activity, and customer service interactions. Gathering this diverse data gives a full picture of customer behaviour, patterns, and preferences from all angles.

3. Monitor Customer Journeys

Track user behaviour from the first moment of awareness to the conversion to learn the impact of various touchpoints. This data unveils drop-off points, conversion triggers, and the most impactful engagement moments, offering the insights needed to optimise every customer journey stage.

4. Collaborate Across Teams

Facilitate cross-team collaboration in customer behaviour analysis, involving departments like marketing, sales, customer support, and product development. Each team brings unique perspectives to the table. You create a comprehensive 360-degree view of the customer by sharing information and working together.

Are you ready to understand your customers in-depth? Sign-up with Houseware now to level up your customer insights, make smarter decisions, and develop better product strategies.


1. What are the processes and tools used to study customer behaviour?

Customer behaviour analysis involves the collection, analysis, and interpretation of data. Some of the common tools and methods are:

  • Customer surveys
  • Web analytics
  • Social media monitoring
  • Customer Relationship Management (CRM) systems
  • Data mining techniques

These tools help you understand customer preferences, buying patterns, and trends.

2. How do you analyse customer behaviour?

To analyse customer behaviour, you must:

  1. Segment your audience.
  2. Identify selling points for each segment.
  3. Gather a vast range of data.
  4. Cross-reference data with qualitative insights.
  5. Make necessary adjustments.
  6. Regularly evaluate results for continuous improvement.

3. What is a customer analysis tool?

A customer analysis tool is software used to collect, process, and analyse data related to customer behaviour, preferences, and interactions. It provides insights into customer demographics, buying patterns, and engagement. This tool helps businesses make data-driven decisions to improve their products, services, and marketing strategies.