Let’s start with an interesting example. Did you know that in your personal life, you have most likely performed one or more types of customer segmentation without even realizing it? For example, you might have shared an ‘event reminder’ with your friends through a group text before informing your co-workers via email. Though they’re not your customers but you segmented them and communicated through different media.

In this article, you’ll know the different types of customer segmentation and why they are important for a business success.

What is Customer Segmentation?

By definition, the strategic process of customer segmentation involves categorizing and grouping customers based on common characteristics such as age, location, device used, industry, gender, and more.

Each group of common characteristics forms a ‘Customer Segment’. This strategic process allows for the customization of marketing, service, and sales initiatives tailored to the specific needs of these distinct groups. The outcome is the potential enhancement of customer loyalty and an increase in conversion rates.

At times, the most efficient communication strategy for businesses involves grouping customers based on shared characteristics. Just as you tailor your messages differently for various social circles, businesses enhance their communication and effectiveness by addressing different types of customer segments.

What are Customer Segmentation Models?

Customer segmentation models represent systematic frameworks that help group customers according to particular data points and business goals.

Whereas customer segmentation is the general practice of segmenting customers, customer segmentation models are the approach to achieving this end.

In today's world of businesses, segmentation models include:

• Demographic criteria
• Geographic criteria
• Buying habits
• Engagement activity
• Value of the customer
• Technology used
• Company criteria
• Customer lifecycle stage

Each model serves its own purpose and is suitable for various businesses; for instance, the retail industry can use a behavior and value-based customer segmentation model, whereas SaaS companies will benefit more from using a technographic and usage-based model.

The best companies usually employ a combination of customer segmentation models.

Why Businesses Use Customer Segmentation Models?

Some of the ways that customer segmentation models benefit organizations include:

• Personalized Customer Experiences: Today’s consumers are looking for personalization. Segmentation allows organizations to personalize their approach to different types of customers.

• Customer Retention: Through customer segmentation, at-risk customers can be identified and retention strategies implemented before losing these customers.

• Improved Customer Experience The customer experience must vary from one consumer to another. Segmentation makes it possible to achieve that.

• Increased Revenue: Revenue is increased by ensuring that the target market gets the message in order to boost conversions.

Types of Customer Segmentation Models

There are several approaches that companies can use to segment their customers according to their needs and business objectives.

Demographic Segmentation

Demographic segmentation involves categorizing customers based on demographic attributes such as:

• Age
• Gender
• Income
• Educational attainment
• Occupation
• Whether or not customers are married

Geographic Segmentation

Geographic segmentation involves segmenting consumers according to their geographical location through variables such as:

• Country
• State or province
• City
• Region
• Weather
• Urban and rural locations

Behavioral Segmentation

Behavioral segmentation involves the examination of the activities of the customers. The behavioral aspects considered for segmentation include:

• Purchase frequency
• Browsing behavior
• Product use
• Website interactions
• Loyalty
• Email interactions

Psychographic Segmentation

Psychographic segmentation is conducted based on the psychological and lifestyle characteristics of the consumers. Some of the psychographic variables are:

• Interests
• Values
• Lifestyles
• Personality
• Motives
• Attitudes

Value-Based Segmentation

In value-based segmentation, consumers are segmented based on their value to the company. The following aspects are taken into consideration:

• Lifetime customer value (LCV)
• Profitability
• Consumer spending behavior
• Order value

RFM Segmentation

RFM segmentation is one of the most commonly employed segmentation techniques. This model considers the following criteria to segment customers:

• Recency: When did the consumer last make a purchase?
• Frequency: Frequency of purchasing
• Monetary value: Total spend by the consumer.

Firmographic Segmentation

Firmographic segmentation is the B2B equivalent of demographic segmentation. Businesses are segmented based on:

• Company size
• Industry
• Revenue
• Employee count
• Growth stage
• Business model

Technographic Segmentation

Technographic segmentation groups customers based on technology adoption and usage. These include:

• Software stack
• Devices employed
• Adoption of cloud technologies
• Maturity in the digital world
• Preferences for technology

Customer Segmentation Models Comparison Table

‍How to Choose the Right Customer Segmentation Model?

The choice of the best segmentation model will depend on a variety of factors, such as your business goals, data available on customers, and specific industry requirements. Though some companies find it sufficient to perform demographic segmentation, others need to apply more complicated strategies to succeed in their business. Understanding which of these elements applies to you will make your segmentation project efficient.

Goals of Your Business

• Your business goals will affect the choice of the segmentation model.
• Customer Acquisition: Demographic and Geographic Segmentation.
• Customer Retention: Behavioral and RFM Segmentation.
• Upselling and Cross-Selling: Value-Based Segmentation.
• Personalization: Psychographic and Behavioral Segmentation.

Customer Data Available

To implement a specific model successfully, one needs to have enough data about customers. For those who have just some basic customer information, demographic and geographic segmentation will be helpful.

Those who know something about customers' purchase history and engagement can try behavioral and RFM segmentation. And, finally, those companies that deal with a huge volume of customer data can use machine learning and predictive segmentation.

Industry Requirements

Methods of segmenting customers differ from industry to industry as customer behavior and business objectives vary significantly.

• E-commerce: Companies working within the e-commerce industry usually employ behavioral, RFM, and value-based methods of customer segmentation to increase their conversion rates, foster more repeat business, and better match products to customers' needs.
• SaaS: Companies operating within the SaaS domain may often resort to behavioral, technographic, and life-cycle customer segmentation practices.
• Financial Services: Firms that provide various financial services prefer demographic, value-based, and risk-based customer segmentation.
• Retail: Companies from the retail sector usually opt for geographically, demographically, and behaviorally based customer segmentation.

Advanced Customer Segmentation Models

With the increased availability of customer information and better analytical tools, many companies are now turning towards advanced customer segmentation models that provide better insight and more accurate customer segmentation. Advanced segmentation involves consideration of several variables, identification of patterns, and accurate customer groupings, which is impossible through traditional customer segmentation techniques. Such techniques are quite important for companies that handle a large number of clients and need to target them on a highly customized basis.

Cluster Analysis Segmentation

In cluster analysis segmentation, statistical methods and algorithms are used to divide customers into different segments depending on several variables. It does not rely on certain rules, as clustering automatically detects patterns in customer data and creates clusters depending upon them.

Companies can segment their customers according to several different variables, such as their purchasing patterns, engagement levels, demographic statistics, and other factors. An example of such segmentation includes a cluster of customers who spend a lot of money and buy products from a company whenever there are seasonal campaigns, as compared to the cluster that spends less often but in larger quantities.

Machine Learning Segmentation

Machine learning segmentation is another form of dynamic customer segmentation that utilizes artificial intelligence techniques in analyzing massive amounts of data in order to create customer segments. As compared to other segmentation methods, machine learning constantly analyses customer data and changes customer segments according to their behaviors.

This method analyzes purchase history, interactions within a company's website, engagement levels, transaction patterns, and customer lifecycle stage to create highly accurate segments. Businesses usually apply machine learning for predicting churn, personalizing recommendations, estimating customer lifetime value, and planning marketing campaigns.

As compared to manual processes of customer analysis, machine learning allows for making quick business decisions and creating relevant customer experiences.

Micro Segmentation

Unlike other forms of customer segmentation, micro segmentation includes dividing large groups of customers into small segments based on very detailed data regarding behaviors, demographics, psychographics, and other factors. In other words, businesses do not target broad customer groups but small segments with specific characteristics and requirements.

For instance, online retailers might divide their clients not only based on age and location, but also based on their browsing, products they choose, purchase frequency, and other aspects. As a result, marketing campaigns become personalized for all micro-segments.

Why do we need Customer Segmentation?

Your customers possess distinct characteristics, preferences, and expectations for your business. Recognizing these individual traits, needs, and pain points is essential.

Suppose a business decides to go with the 'one size fits all' approach. This leads to critical issues like lack of personalization and inefficiency in resource allocation.

Smart Businesses think beyond this approach. The types of customer segmentation extend beyond mere categorization; it involves a comprehensive understanding of individuals within those categories. 

By customer type segmentation, you can delve deeply into their characteristics, enabling the creation of tailored content that addresses the unique needs and challenges of each segment.

This strategic segmentation enhances customer service, marketing, and support initiatives of businesses. 

It enables internal teams with insights to proactively address challenges specific to different groups.

Moreover, it facilitates targeted communication with customers through their preferred channels or platforms, fostering effective engagement.

Additional Benefits of Utilizing the Right Customer Segmentation Model

• Enhanced Consumer Engagement: Targeted ads and personalized marketing messages establish meaningful connections with potential consumers, fostering sustained engagement from existing ones.

• Increased Consumer Satisfaction and Loyalty: Brands that make customers feel seen, heard, and understood cultivate higher levels of satisfaction and loyalty. This personalized approach goes beyond treating customers as mere order numbers.

• Improved ROI: Customer segmentation reduces wasted time and resources on marketing efforts that don't resonate with the right audience. By comprehending your consumers' needs, you can efficiently address those needs, leading to a more cost-effective and rewarding marketing strategy.

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Different Types of Customer Segmentation

Your business can segment customers in many models. Here, you’ll get to know majorly four types of customer segmentation, as listed below.

Demographic Segmentation

Demographic segmentation involves categorizing customers into groups based on significant life factors. Parameters of demographic segmentation include age, gender, income, education, and marital status.

This is one of the most important types of customer segmentation where you get a foundational understanding of a customer base. This information serves as a crucial building block for businesses to better understand the type of audience that they are going to serve.

Industries such as ecommerce and fashion commonly utilize demographic segmentation to tailor their marketing strategies.

For instance, in the fashion industry, a business owner may target both men and women. By segmenting customers based on gender, the business can deliver personalized product recommendations and messages to each group.

Let’s talk about an insurance broker company Policybazaar. They regularly communicate their offers for different age groups. Take a look -

Here, Policybazaar is targeting people who are born between 1975-1995. 

While below you can see that the company is trying to target elder audience to communicate its Senior Citizen Health insurance plan.

Their internal team might be using Geographic Segmentation model further as well to analyze the results and optimize campaign performances to drive results.

Seeing the use of one of the popular types of market segmentation examples, you can take inspiration and start building models for your business.

When executed effectively, this approach contributes to building a more loyal customer base, fostering long-term relationships of your business with customers.

With the use of tools like Nected, grouping of customers based on shared characteristics is effortless. It uses demographics to segment customers into micro-segments that refresh daily. This allows businesses to create targeted marketing initiatives and optimize their strategies.

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Geographic Segmentation

Geographic segmentation involves categorizing customers according to their location, spanning countries, states, cities, towns, etc.

This segmentation model becomes particularly relevant for businesses operating in multiple locations within the same city, state, or country, or those engaged in shipping products to diverse geographical regions.

The rationale behind segmenting customers by geography is to customize communication in a way that resonates with their specific locale. This entails adopting regional language nuances, referencing local points of connection, and tailoring messaging to align with the cultural context of the audience.

When businesses incorporate elements that reflect the experiences of customers in their particular location, it demonstrates a thoughtful approach to content creation. This, in turn, signals the customers that the message is crafted expressly for them, establishing a connection through relatable and localized communication.

With tools like Nected, you can analyze large amounts of consumer data to understand what products the customers really want, and apply strategies accordingly.

Let's take a look at an example of how you can use Nected to perform geographical segmentation. Here we take a sample set of data and we want to provide different discount rates to domestic and international customers respectively.

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To create a complex rule set called the Pricing Rule, we need to access the data from the database and select the desired columns. We can use the Nected Query Builder to easily connect to any data source and drag and drop the columns we want to use in our rule set.

Next, we need to define the logic for our rule set. We want to provide different discounts to international and domestic customers based on their location. We can use the Nected Rule Editor to create a conditional statement that checks the ‘customer_location’ column in our data. Just click on the drop down list and select the desired parameter.

This rule set will assign a result and a discount value to each customer based on their location. We can test our rule set using the Nected Simulator to see how it works on sample data. We can also modify our rule set as needed using the Nected Rule Editor.

Finally, we need to deploy our rule set to our application or website. We can use the Nected API to integrate our rule set with any platform or service. We can also use the Nected Dashboard to monitor and manage our rule set performance and analytics.

Behavioral Segmentation

Behavioral segmentation is centered around customer actions and interactions with your brand. Instances of categorizing customers based on behavior include their inclinations, frequent activities, product usage, and routines.

This segmentation model proves particularly valuable in campaigns involving PPC or YouTube ads, ensuring that your advertising budget is directed toward customer segments that align with your brand. Instead of relying on external demographic factors, behavioral segmentation groups consumers based on their habits and actions. 

This is one of the most used types of customer segmentation models by marketers and businesses.

For instance, it considers factors like purchase history and the preferred social media platforms used by customers. By honing in on specific platforms, you can optimize your ad strategy and, for instance, send targeted sales emails to frequent or repeat online buyers, creating a more effective and personalized marketing approach.

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Technographic Segmentation

Technographic segmentation is slowly becoming one of the most important types of segmentation methods. It is a strategic approach that categorizes customers based on the technology they use. This method is becoming more prominent as businesses progressively transition their operations to the online ecosystem. 

Notably, this trend has spurred significant growth in sectors such as Software as a Service (SaaS) and online marketing analytics.

The basis of technographic segmentation lies in its ability to allow businesses to fine tune their targeting strategies to consumers based on the specific software or online services they use regularly. This form of segmentation goes beyond traditional demographics, offering a highly personalized approach that considers factors like mobile and desktop usage, preferred apps, and software choices.

The significance of understanding the technological preferences of individuals cannot be overstated, whether for online marketing needs or for SaaS enterprises that are heavily reliant on technology to deliver their services. As businesses continue to embrace digital transformations, the relevance and impact of technographic segmentation are poised to grow. This approach not only provides a more nuanced understanding of customer preferences but also offers a more effective way to connect with diverse consumer segments.

For example, when we look at Zomato, one of their most important messaging channels is push notifications on smartphones. This form of messaging would have been way less effective if the target customers’ primary device would have been a laptop or personal computer.

Here’s How You Can Use Nected for this type of customer Segmentation

As you now know, technographic segmentation involves categorizing customers based on the technology they use. 

For example: In this dummy rule set, technographic segmentation focuses on scoring customers based on the devices (Mobile, PC), applications, and software they utilize. 

Just like this, by analyzing the technological landscape of your customers, you can do segmentation & create rules that assign scores or prioritize customers based on their tech preferences. This can help businesses in tailoring marketing strategies, product offerings, and customer interactions to align with the tеchnological profiles of different segments.

Explore how Nected can help you utilize different types of segmentation methods.

Utilizing customer segmentation enhances conversion rates by better targeting and delivering more pertinent information to your audience. 

It’s time to utilize different types of customer segmentation in your business to boost the revenue. Consider using a user-friendly No code tool for customer segmentation and drive maximum results. 

FAQs Customer Segmentation

Q1. What is a customer segment?

When a set of common characteristics of customers are defined, it’s called customer segment.

Q2. Why do customer segmentation

By doing Customer Segmentation, you can get better results in marketing, service, and sales initiatives for your company.