Segment your users and gain valuable insights with B2Metric's User Segmentation analytics tool. Learn more in our latest blog post.

Hanane Nour Moussa & Cansu Alataş
9 Minute Read
Automated Machine Learning
Customer Journey Analytics
B2Metric IQ Analytics
Customer Segmentation
Customer Micro Segmentation
Digital Optimization

Table of Content

  1. What is User Segmentation?
  2. Why should you segment your users/customers?
  3. The Best Customer Segmentation Analysis
  4. What are the common types of segmentation categories
  5. Customer segmentation with B2Metric IQ Customer Journey Predictive Analytics
  6. Personalize the Customer Journey Across Different Channels with B2Metric IQ Customer Journey Predictive Analytics 


What is User Segmentation?


User Segmentation: A Roadmap to Understanding Your Customers

The business approach is changing daily, from business-centric to customer-centric, as understanding customers and meeting their needs are among the most important goals any business can have. Also, when customers feel understood and cared for, they are more likely to have a satisfying experience with the company, which leads to long-term loyalty. It’s undoubtedly a win-win situation. The numbers say the same thing! 81% of customers wish businesses know them better, whereas 94% of marketers want to know their customers/users better. However, even with more technological solutions suitable than ever before, 74% of marketing leaders say they struggle with their personalization efforts, according to a Gartner survey. Thus, if there’s a clear awareness of the need for digital platforms to understand users better, why do marketers face this issue? Because learning and gaining information about what users/customers want takes time, effort, and tools - especially when it comes to meaningful segmentation.


Marketing analytics platforms, such as B2Metric, aim to upgrade companies’ decision-making from sheer guessing to informed insights based on data generated from the customers’ interactions with the digital platforms. Among the many capabilities that marketing analytics provides, customer segmentation is one of them for understanding customers and providing them with personalized experiences. 


Despite its incredible usefulness, customer segmentation is at heart a basic concept: dividing customers into different categories based on some shared traits. The exact criteria based on which the split is performed varies from business to business and can range from demographic features to behavioral ones. However, the last goal remains the same: increasing profitability and driving growth by understanding the customer base. 


Why should you segment your users/customers?


Customer segmentation has significant benefits, all of which spur company success and growth. Some of these benefits can be broken down as follows: 


  1. Better marketing strategy: customer segmentation enables companies to develop different marketing personas (i.e., marketing strategies tailored to the needs of a customer segment). As a business learns more about the preferences of specific customer segments and the content and offerings likely to excite them, they can leverage this information to direct highly personalized and efficient marketing campaigns. 
  2. Efficient budgeting: customer segmentation does not enhance marketing strategy but also allows the business to make smarter decisions about its budgeting. Companies can get a greater return on their marketing investment by targeting the segment of customers that deliver the highest value and are most likely to convert. 
  3. Informed product development: customer segmentation enables businesses to unearth the likes and dislikes of different portions of their customer base. Product teams can use these insights to introduce new features and functionalities that would appeal to the users. 


The Best Customer Segmentation Analysis

Thus, how do you adopt a customer-centric approach that helps you succeed in crucial performance goals? 

Follow these three effective rules for a better customer segmentation strategy.

  1. Know your users more. What channels do they come from? Why, how, and when do they use your app? Gain your existing customer base and mobile app usage behaviors and habits as much as possible.
  2. Set prioritized aims. After you’ve created a couple of segments, define an objective for each. That will help you to have actionable strategies, engaging marketing campaigns, and measurable business aims.
  3. Revisit your segments. Don’t forget your approach for each segment. Check your segmentation strategy regularly and look for size, behavior, and engagement shifts. You should ensure that your current messaging still resonates with every segment or needs to refresh your approach and plan?



B2Metric blogpost



Customer segmentation procedure: 

To implement customer segmentation, the following steps have to be done: 

  1. Identify the type of data that has to be collected about customers and how it would be gathered. The primary data collected includes geography, device, browser, and payment method. More detailed data, which could be gathered as part of the selling or checkout process, could consist of age, gender, occupation, the reason for purchase, etc. More data could be purchased as third-party data, such as the presence of children, estimated household income, and lifestyle or behavioral interests. 
  2. Collecting and integrating the data from different sources
  3. Analyzing the data for segmentation. The approaches used at this stage depend on the company’s objectives. The analysis could be limited to grouping the customer into clusters or could be extended to predicting the segments of new customers.
  4. Establishing communication between different business units about the segments and leveraging them to reap the benefits mentioned above


B2Metric blogpost



What are the common types of segmentation categories: 

Different segmentation types can be made based on the data used, depending on the company’s interests. 


B2B companies focus on company data, industry sector, whether the company is public or private, company size, location, etc. B2C is more concerned about customers covering demographic and behavioral characteristics. 


Keeping this variety in mind, standard segmentation models include: 

  1. Demographic: This is a primary type of segmentation that relies on static data such as gender, parental status, location, etc. 
  2. Recency, frequency, monetary: this type of segmentation relies on data about the recency of the customer’s purchase, the frequency of purchase, and the economic value they deliver to the company. 
  3. Customer status: this type of segmentation buckets customers into active and lapsed based on the recency of their activity. 
  4. Behavioral: using behavioral segmentation, past customer behavioral trends such as brands they purchase most and the seasons or occasions in which they are most active are used as indicators of future actions. 

When presented with such a plethora of segmentation models, companies ought to choose the one most aligned with their data and business goals. 


Customer segmentation with B2Metric IQ Customer Journey Predictive Analytics


B2Metric ML Studio AutoML Platform and B2Metric IQ Customer Journey Analytics Platform support your business’ marketing analytics efforts from primary KPIs to robust predictive models. Bundled within B2Metric’s features, there are many functionalities for customer segmentation: 


  1. User composition: using B2metric IQ, you can understand your customers better by exploring their composition according to different criteria from your data. This functionality is flexible, as it allows you to generate reports according to the requirements that you choose dynamically and generates visualizations that can be shared to convey insights across different business units. 


B2Metric blogpost


2. RFM analysis: B2Metric ML Studio includes an RFM report within its main dashboard. This report groups users across buckets based on their Recency-Frequency-Monetary data, allowing your business to direct its marketing efforts better. 

B2Metric blogpost

3 . Clustering: In addition to the automatically generated reports, B2Metric allows you to leverage the power of AutoML to build your own clustering algorithm to group your users into different segments. Clustering models belong to the class of unsupervised machine learning, and their task is to divide data points into different groups or clusters such that points belonging to the same cluster are more similar than ones from distinct clusters. However, do not worry about all the jargon! AutoML enables you to build a clustering algorithm with just a few clicks without prior ML knowledge. B2Metric ML Studio also generates thorough ML explainability reports to ensure that your results are actionable and interpretable. 




B2Metric blogpost




After having created your customer segments, B2Metric accompanies you in using these segments for insightful analysis using: 

  1. User lookup: this functionality allows you to view users based on specific criteria. In the case of segmentation, it can be used to view who the users in each segment are. 

B2Metric blogpost


  1. Audience tracker: a highly flexible functionality that allows you to track each segment of your customers by viewing the events that they triggered over a given period of time.


B2Metric blogpost


  1. Funnel analysis: the funnel report enables you to take a detailed look at your segment’s conversion and drop-off rate across different customer journey stages. 


B2Metric blogpost


Personalize the Customer Journey Across Different Channels with B2Metric IQ Customer Journey Predictive Analytics 

Mobile marketing automation and personalized content are game-changers in the digital world between users/consumers: high personalized messages target customer interests, demographics, and location. Customer-centric data creates deeper insights for mobile marketing campaigns and supports omnichannel marketing strategies at every customer journey stage.

The correct mobile marketing analytics regularly gathers and analyzes data for the purpose of automated customer messaging and delivering seamless product/service experience across mobile, web, and in-app channels. By using B2Meric IQ Customer Journey Predictive Analytics, you can reach your users that do not currently visit your app by delivering personalized messages that attract your user’s attention and let them return to your app.



Customer segmentation is a valuable gem in the product analytics toolkit; it allows businesses to know exactly who their customers are and thus the kind of service and products they should deliver. It is a real game changer to make marketing, budgeting, and product development efforts more focused and thus the business more profitable. 


Click here to learn more about the Customer Segmentation Solution of B2Metric.



Sign up Today

Sign up to receive the latest best practices, news, and product updates.