Behavioral Analytics decoding human behavior-Saxon AI
Data Analytics / July, 05 2023

Use cases and business benefits of Behavioral Analytics 

In the vast digital landscape, understanding your customers and their needs is the key to success. This is where behavioral analytics steps in—a dynamic concept in business analytics that unveils fascinating insights into “customers’ behavior” across various digital channels. 

Each interaction provides invaluable signals about the customers’ desires, readiness to purchase, and more—knowledge that can revolutionize your customer profiles – Microsoft Dynamics 365

Thus, behavioral analytics is an effective data-driven approach. It can be a powerful tool to help you make informed decisions, personalize experiences, enhance products, and drive strategic initiatives. Are you a CIO seeking to harness the vast potential of Business Analytics and lead them toward optimized business outcomes? Then this blog is for you.  

Let us look at an instance. Presume you want to buy a car. You decide to explore your options by going through a car manufacturer’s website, where you gather information about different model trims. You also check out the local dealers’ websites to review the available deals, and then you finally visit the dealership in person. Wonder what information can the sales representative at the car dealership examine to understand your purchasing needs and decide the best options to offer you?   

What is Behavioral Analytics?

It is a concept in business analytics that reveals in-depth insights into how customers behave on your website, e-commerce site, mobile app, chat, email, IoT, and various other digital channels. Every time a user engages with one of your digital channels, they send out key signals about their requirements and wants, and even their buying readiness. You can capitalize on this data to create more accurate client profiles.  

Behavioral analytics, an aspect of digital analytics, aims to predict customers’ requirements proactively. It does so by comprehending where they are in the customer journey and identifying the next required information and details. Further, it also recognizes any roadblocks they may encounter. While there is an array of data and analytics available, behavioral data holds a unique advantage. It comprises of tangible, user-generated data that facilitates highly accurate predictions of customer intent. Furthermore, when combined with cross-channel behavioral analytics and other customer data like transaction history and demographics, businesses can gain deeper insights to drive truly personalized experiences.    

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For this reason, behavioral analytics is extremely significant when it comes to business growth. It helps attract both existing and new customers, ensuring their retention is based on actual interactions and usage patterns. By leveraging these analytics, enterprises can forge stronger connections with their customers, foster loyalty and propel their growth trajectory. 

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Who benefits from behavioral analytics?

Behavioral analytics offers broad benefits across different organizational roles, empowering anyone at any level to leverage its insights. While multiple team members can utilize these analytics, specific roles mainly derive the most value from them:  


Marketers can harness behavioral analytics to create cohort data. That data assists in optimizing campaigns, acquiring customers effectively, and enhancing retention and conversions. They can further create multidimensional customer profiles by combining behavioral data with transactional and demographic information, enabling more personalized and relevant engagements.  


Behavioral analytics acts as a crucial link between marketers and the sales team. By leveraging behavioral data-driven campaigns, marketers help the sales team demonstrate tangible returns on investment (ROI) and build a larger, qualified sales funnel. Understanding users’ browsing habits and reactions enables sales teams to identify upselling and cross-selling opportunities for responsive customers, resulting in increased sales volume.  

Data Analysts

Data analysts play a vital role in deciphering the complete customer journey by utilizing signals acquired through behavioral analytics. They compare user intent with actual behavior, identify customers at risk of churn, and identify those likely to remain loyal. By conducting complex user analyses and transforming data into actionable insights, data analysts enable marketers to make data-driven decisions and streamline workflows.  

Customer Service

Even with accurate predictions, there are instances where customer feedback indicates a mismatch. Customer service teams at the forefront of receiving such feedback through online engagement channels benefit from behavioral analytics. It equips them with appropriate responses based on user behavior. As a result, valuable customer experience information can be shared with sales and marketing teams for continuous improvement.  

Behavioral Analytics vs. Business Analytics: Understanding the Distinctions

Behavioral analytics, although related, differentiates itself as a subset within the broader realm of business analytics. While the two concepts may share similarities, there are crucial distinctions to be aware of. Business analytics, categorized under business intelligence, involves analyzing historical data using statistical methods and technologies. In contrast, behavioral analytics relies on a combination of user segmentation and behavioral /event-tracking technologies to arrive at more precise conclusions.  

Segmentation entails categorizing customers based on specific traits or data. Among various segment categories, behavioral segmentation focuses on user actions, such as login frequency, time spent, and overall engagement levels.  

While business analytics adopts a wider lens, examining the “who, what, where, and when” aspects, behavioral analytics delves deeper, providing more targeted predictions of user actions. By leveraging seemingly unrelated data points from the user journey, behavioral analytics extrapolates insights, identifies errors, and predicts future trends, ultimately aiming to facilitate the completion of the customer journey.  

Types of User Data in Behavioral Analytics

Behavioral analytics captures valuable user-level data regarding user interactions and reactions across your digital channels. This data is often sourced from multiple digital platforms and devices, forming what is known as cross-channel analytics. When utilizing behavioral analytics, it is essential to leverage three distinct categories of user data. Each contributes to the transformation of raw data into valuable insights:  

  1. Registered Data: This category encompasses data stored within your customer relationship management (CRM) or marketing tool. Registered data provides valuable information about user profiles, demographics, preferences, purchase history, and other relevant customer relationship data. 
  1. Observed Data: Observed data provides a comprehensive overview of the UX by tracking interactions with various elements of your website or app. This data includes user behavior patterns, clickstream data, session duration, page views, and other metrics that shed light on how users engage with your digital channels. 
  1. Voice of the Consumer: This category captures the sentiment and feedback expressed by customers through online channels. It includes proactive and reactive forms of customer expression, viz reviews, ratings, comments, social media posts, and other user-generated content. Voice of consumer data offers insights into customer perceptions, satisfaction levels, preferences, and areas for improvement. 

Businesses can transform raw data into valuable information by effectively leveraging all three types of user data.   

5 steps for effective user Behavioral Analytics

Integrating behavioral analytics into your business processes requires careful attention to technical, analytical, and strategic aspects to ensure effective insights. You can follow these five essential steps to kickstart your user behavioral analytics project: 

  1. Define Achievement Metrics, KPIs, and Goals: Clearly define what success looks like and establish measurable targets to track the impact of behavioral analytics.  
  1. Design the Optimal User Journey: Craft a user journey that optimally satisfies both customer needs and business objectives. Map out users’ desired steps and touchpoints, ensuring a seamless and engaging experience throughout their interactions with your digital channels.  
  1. Track Relevant Signals: Identify the specific user signals and events that are critical to track based on the user flow. Create a comprehensive tracking plan that captures key interactions and events, regularly revising it as needed to align with evolving requirements.  
  1. Unify Data Sources: Bring together transactional, demographic, and behavioral data to gain a holistic understanding of your customers and business. Build and enrich customer profiles by integrating these data sources, enabling deeper insights and more personalized experiences.  
  1. Implement an Integrated Behavioral Analytics Experience: Deploy a unified behavioral data analytics solution that enables machine learning models’ swift development, training, and fine-tuning. Embrace custom AI/ML models that provide flexibility for updating the tracking plan as you learn and adapt, fostering continuous innovation.  

Are you looking for a tech partner to meet your behavioral analytics needs? Look no further. Saxon specializes in assisting organizations with advanced analytics, automation, the latest Microsoft offerings, and accelerating their business. Explore our solutions today to learn more about how we can help.  

Bring us your use case; we’ll provide the expertise and guidance you need to succeed. Contact us to get started.  
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