What is Customer Segmentation and Why It Is Crucial?

Understanding your customers is carving the path to success. It helps in crafting the solutions as per customers’ requirements instead of guessing their preferences. As a marketer, segmenting customers into groups based on their similarities helps in developing a better understanding of these groups. According to the needs and preferences of every segment, targeted campaigns can be built, and customized products and services can be offered. In a world where 80% of buyers prefer to purchase from brands that offer tailored experiences, it’s time to understand customer segmentation to its core and adopt it to thrive in the competition.

What is Customer Segmentation?

When a business organization divides its customers into different groups based on their similar characteristics to market each group effectively, it is known as customer segmentation.

In , businesses segment customers on the factors listed below:

  • Industry
  • Number of employees
  • Location
  • B2B marketing Products purchased from the companies previously

In B2C marketing, customer segmentation takes place on the basis of the following factors:

  • Gender
  • Age
  • Location
  • Life stage

Segmentation can be performed on several other factors, including behavior, psychographics, and demographics. Under demographic segmentation, customers are grouped on the basis of income, education, level, gender, and age. However, psychographic segmentation divides customers on the basis of values, lifestyle, preferences, and personal traits.

Why is Customer Segmentation Crucial for Modern Businesses?

Each business introduces products and services for different customer groups. For instance, a business might produce both costly and budget-friendly products in order to meet the needs and requirements of both middle and higher-income groups of people. However, apart from income,  a number of other factors also affect customer segmentation. Some of the most crucial reasons for customer segmentation by businesses are listed below:

Enhanced Customer Satisfaction

Once a business organization understands the preferences and needs of multiple customer groups, they craft their services, products, and marketing efforts in order to align with the needs of the customers. This results in enhanced customer loyalty and satisfaction, which ultimately drives revenue and sales growth.

Increased Effective Marketing Campaigns

Customer segmentation gives businesses the power to craft relevant marketing campaigns aligning with every group of customers. It results in improved conversion rates, increased customer engagement, and higher response rates.

Better Product Development

After a business carefully monitors and analyzes the needs and preferences of the customers, it produces new and better products and services to increase customer satisfaction. This even results in better product innovation, offering top-notch quality and bettering the reputation of your brand amongst the competitors.

Efficient Resource Allocation

Customer segmentation assists businesses and allocates their resources efficiently by targeting the most profitable customer segments. This results in enhanced return on investment and increased profitability.

Customer Segmentation Examples

Some examples of customer segmentation are:

Demographic Customer Segmentation

This type of customer segmentation groups customers on the basis of the facts of their lives. It includes factors such as age, occupation, gender, marital status, and household income.

Example: H&M 

It has demographic segmentation on the basis of date of birth. They offer discounts on birthdays that are valid for a specific period.

Geographic Customer Segmentation

Under geographic customer segmentation, customers are divided according to the region or location. It includes location, cultural factors, and preferred language to segment customers based on their location, which means that you can provide messages in their languages.

Example: Coca-Cola

It offers its products globally and tailors its offering to local tastes. 

Behavioral Customer Segmentation

This segmentation includes grouping your customers according to their behavior online. It includes factors such as previous purchases, products they’re interested in, and how frequently they buy from your brand. In behavioral customer segmentation, customers are grouped on the basis of customer loyalty, purchase behavior, and usage.

Example: Duolingo

Understanding that the initial drive of the learners soon seems to fade away, Duolingo adopts milestone achievements, badges, and rewards. 

Psychographic Customer Segmentation

Psychographics segmentation includes the division of your customers on the basis of their interests, values, lifestyle, and attitudes. Based on psychographic customer segmentation, you can group your customers on the basis of their interests and hobbies, personality traits, and values. You can even monitor previous purchases, shopping behavior, and survey responses to acknowledge the kind of life your customers live and what things they enjoy and value the most.

Example: Nalu

This women’s clothing brand has collections that feature a limited number of items. It has a segment called newsletter subscribers who get early access to the items so that they can purchase them before they run out of stock. This tactic strengthens their bond with high-value clients. 

Technographic Customer Segmentation

Under technographic customer segmentation, customers are grouped on the basis of the apps and technology. It considers how your brand is promoted to the customer and the device used in order to engage with your products. 

This segmentation divides customers on the basis of preferred devices, online behavior, and technology adoption.

Key Approaches to Customer Segmentation

Once you are clear with the attributes and best categories for customer segmentation, you should be clear with the approach you will apply for creating those segments. Two of the most common approaches for customer segmentation are cluster-based segmentation and rule-based segmentation.

Rule-based segmentation

This aims to set thresholds for determining the segment of a customer. Rule-based segmentation includes customer division on different factors. However, it would help if you acknowledged the attributes used to segment customers each time. This makes it easy to analyze trends by considering them. 

Cluster-Based Segmentation

Cluster-based segmentation doesn’t set fixed rules or thresholds to divide customers. Instead of this, it finds the most balanced and natural way to group them based on their similarities. It uses a method called K-means to do this. The benefit of this approach is that it uncovers unexpected customer groups and can consider multiple characteristics when creating segments. However, it’s a bit complex to set up without a skilled data scientist’s help, but it offers more powerful segmentation options with less ongoing maintenance.

Types of Customer Segmentation Models 

There are multiple customer segmentation models. Some of them are:

Predictive Segmentation

Under this model, machine learning models are used to predict customer segments on the basis of a combination of numerous factors and historical data.

RFM Segmentation

This model uses frequency, recency, and monetary value to segment customers based on recent purchases, how much they spend, and how often they buy.

Loyalty Segmentation

It identifies loyal customers, one-time purchasers, and occasional customers.

Usage Segmentation

This model monitors how frequently customers use a certain product or service and the benefits and features they prioritize.

Value-Based Segmentation

Based on their monetary value to the business, such as low-value, medium-value, and high-value customers, customers are segmented.

Needs-Based Segmentation

This model classifies customers according to their specific needs or problems they are trying to solve. 

Regardless of the type of segmentation model a business decides to implement, as the first step to segment the customer base, businesses need to divide their customers into groups as per their requirements. As a result, they will have a series of tiers for every segmentation model. Hence, to create more segments, businesses can mix multiple tiers across models to craft more enhanced segments. 

How to Perform Customer Segmentation Analysis?

To begin with, your customer segmentation analysis must focus on industry-wide data and later consider your data on the basis of your customer population. Now, monitor the subset of your customer population. Consider the similarities that bring together a group of customers and begin your segmentation. Find the correlation, consider the process of finding a correlation, and learn about the engagement strategy that will leave a great influence over the customer segment. Hence, your customer segmentation variable must include:

  • Who are they?
  • What do they do?
  • What are the requirements?

When looking at data, consider that some products are more linked to specific groups, like music, while products like food appeal to a wide range of people. It depends on your goals whether you should be very detailed or more general in your data analysis. If you’re unsure, here are some questions to ask yourself to decide when to be specific with your analysis and when to keep it broad:

  1. Think about how different factors relate to each other.
  2. Use experience data to understand these connections.

To get the data you need for customer segmentation, you can collect information in different ways. You can either ask customers directly or look at data that gives you clues. Here’s a list of these methods:

1. Direct methods 

This might include asking customers questions in surveys to get their direct answers. This method includes:

  • Relationship survey 
  • After store visit surveys
  • Post-purchase survey
  • Product satisfaction survey
  • Brand tracking 
  • Video feedback

2. Indirect methods 

It involves looking at data that wasn’t collected directly from customers but can still show patterns in how customers behave. This helps you understand how customers act. Indirect methods include:

  • Omnichannel analytics
  • Social listening
  • Frontline feedback

Qualtrics can assist you in understanding both of these methods by using DesignXM and CustomerXM to explore important trends and reasons behind consumer behavior.

Once you’ve sorted your customer groups based on the connections you’ve discovered, you should use them to figure out your brand’s position, the messages you send, and your overall market strategy. These groups provide valuable insights into how to meet your business goals effectively because they show you who to target and how to do it to boost your profits.


Customers follow their unique paths, so if your business analyst understands how different groups behave, they can create paths that suit their needs, making it easy for them to complete their journey. Matching your customer groups with your goals will guide you in deciding how detailed these groups should be. For example, a big global brand like eBay launching a service for everyone will have different customer groups than a brand focused on small businesses. As a business analyst, when you’re segmenting customers and connecting them to your goals, ask yourself what you want to achieve. 

To master as an analyst, access Data Analyst course offered by Simplilearn and perform customer segmentation to clearly understand and fulfill your customers’ needs.


Q1. How often should I revisit and update my customer segments?

Most of the segmentations are useful for about 2 to 3 years. However, in case of any major events taking place, your segmentation might fluctuate. Moreover, if your segmentation crosses 3 years, you must update it.

Q2. Can customer segmentation help small businesses?

When discussing small businesses, demographic segmentation is extremely useful as this segmentation offers a clear understanding of the targeted customers and their requirements.

Q3. What tools can businesses use for effective segmentation?

You can opt for tools such as Optimizely, VWO, or Google Optimize to perform experiments and examine multiple variations of your strategies and marketing for every segment.

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