Customer Segmentation Method: How, When, and Why?

What is customer segmentation?

Customer segmentation is defined as the process wherefrom the whole list; customers are categorized according to their needs and preferences. From a particular company, every customer will have a basic expectation, but after that, the streamlined desires will be specified concerning specific criteria like gender, age, location, etc. 

Why segment customers?

• It is an obvious question that might creep in mind about the need for customer segmentation. It is essential to segment customers because:
• The better the customer is known by the company, the better the company can develop a product or service suitable for the customer. It stops the process of guessing what the customer might want and puts a stamp on the customer’s needs and wants. 
• To improve customer experience. According to the census, 81% of the customers get disappointed with the brand if the customer experience is unsatisfactory. And out of them, 44% of the customers put their dissatisfaction over social media. 
• One of the most important reasons for segmentation is to figure out which segment is more profitable and let go of the features which might be less fortunate. It would also be more comfortable to modify the details that have more potential and improve those prospects. 
• Making the customers happy reduces the risk of customer disengagement with the brand. With the segmentation’s help, it is easier to improve the products and services by making them more personalized and according to customers’ desires. 
• Better the customer experience more would be the customer engagement increasing the revenue of the company. 
• Customer segmentation helps in price optimization. With the help of demographics, the customers can be segmented into groups for whom special offer packages and deals can be designed. 
• Customer segmentation can also help improve the overall marketing strategy as there is a better understanding of what the customer wants. 
• The overall promotion strategy is also improved to a great extent, for example, offering more deals or offering location-specific deals concerning the festivals and holidays. 
• There is a substantial impact on the product development because as the number of customers increases, more information about the likes and dislikes can be obtained to improve the product’s wrt the features and usability. 

How to segment customers

To segment customers effectively, it is essential to keep a few things in mind

1. It is wonderful if the categories of segmentation are broad in the beginning. These segments can be based on easily found information like gender, age, location, etc. As the customer engages more, complex data can be collected to make the segments more precise. This is basically aligning the problems and principles. Defining the problem that has to be solved gives a good start to the process. The usual problems are with

• Marketing 
• Sales
• Support 
• Product 
• Leadership 

2. The segments shouldn’t be too small. This is because putting so much effort into very few people is not worth the effort. This means establishing the principles that would guide the process. Example of this is:

• Defining the number of segments that has to be made.
• The freedom to evaluate past problems.
• A particular and selected source of segmentation.

3. A lot of organizations create customer segmentation based on guesswork and conviction. This is not recommended at all. Customer segmentation should be purely based on analytical data. The approaches of data segmentation can be categorised as:

• Performance- Customer segmentation is done on the basis of the performance of the customer in terms of using the product or service.

• Buyers persona- The buyer’s persona represents who exactly would buy the product. Who decides to buy your product? For example, you may find that individual users or founders make the purchasing decisions at small startups, team leads at mid-market companies and department heads at large enterprises. Your Marketing, Sales, or Research teams can likely shed light on your buyer personas.

• Channel and sales motion- Sales motions are steps and philosophy to be used to make the charts go higher up in sales. The customer segmentation is done according to these charts and tables.

4. This data should be taken from different sources, which can be done by using various tools like:

• Google Analytics
• Intercom 
• Mixpanel 
• Survey tools like Survicate

Customer segmentation is never really over. Once the initial phase of knowing the customer surveys are done, the surveys to keep track of whether their preferences have changed needs to be done. Along with this process, it has to be kept in mind that there will always be an inward current of new customers. Therefore, it is wise enough to say that customer segmentation should not stop its healthy growth. 

Customer segmentation models

Customer segmentation models can be categorized according to demography, according to psychograph, according to the goal of the customer and according to purchase a pattern.

According to Demography

In customer segmentation based on demography, as the name suggests, the target is on the customer’s demography. A demographic survey is held instead of the general information found through google analytics or CRM. 

Different questions about marital status, ethnicity, income, etc., depending on the purpose, are asked to the customer. 

With this information’s help, customers can be categorized into groups like whether they are single or are their parents or would they pay more money for quality and comfort, etc.

According to Psychograph

Sometimes the customers are segmented according to their attitude and personality. With the information, user personas are created that tags with individual lifestyles. 

For this segmentation, a survey is required. The survey comprises questions with options like highly agree and highly disagree.

For example, if we would want to know what the customer thinks about “Sustainable fashion.”

A few of the generalized questions can be:

• When was the last time the customer bought something?
• How many times did she purchase?
• What was the amount of money that she has spent?

With the help of this analysis, the company can figure out the High-Value Customers. 

If the company focuses on the appropriate customer for a particular correct product, then with proper marketing and sales, there can be an increase in the revenue. 

According to the goal of the customer

While trying to segregate customers according to their goal information from CRM, analytics tools, survey results have to be mixed. The behavioral information is recorded when the customer makes a purchase or takes action like adding things to the cart.

Similarly, surveys can be conducted on customers to check whether their preferences are the same compared to the last time or have changed. 

For example, customers are more inclined towards organic and sustainable packaging. So the company might want to survey whether or not they want to give up on plastic packaging completely. 

According to Purchase Pattern

The purchase pattern helps in understanding what the customer would like to buy according to the previous purchases. The customers can be segmented based on who kept buying from the brand and which of them disengaged. And these customers are known as active customers and lapsed customers. 

This model helps to understand who are the new customers and who are the previous customers. By creating this demarcation, it is easier to provide help to the new user than those who are well versed with the process. 

Establishing Segmentation hypothesis and variables

Even if the company is experienced in the market traits, it is not advisable to assume situations and scenarios and have guesswork as a means while taking business scale up decisions. 

Thus customer segmentation is used to minimize the scope of error. For the segmentation process, variables are set, and hypotheses are developed, confirmed by accurate and proper scientific research processes. When the segmentation is done based on needs and values, this is specifically used. Although the hypotheses created for having segments are not mathematical and statistical, they are incredibly logical and useful. 

An example of a hypothesis can be:

• Customers with an annual earning of $50000 will be segment-A.
• Customers with a yearly income above $50000 will be segment-B.
• Customers with an annual income below $50000 will be segment-C.  

In the example, the customers are segmented based on their yearly income but using the same technique; they can be segmented according to their gender, age, online presence, etc. 

It is essential to develop hypotheses and variables because building the framework and eventually concentrating on intricate details becomes much more comfortable. 

Read more about segmentation hypotheses and variables.

Customer segmentation analysis

Lightweight clustering analysis

Lightweight customer analysis is used when the number of customers is less, and thus, the number of hypotheses involved is also less. The process of the study is as follows: A table is created containing the details of all the customers to be analyzed along with their quality scores. The segmentation hypotheses selected for testing are also listed. The table is sorted with regards to the quality scores, and the segmentation hypotheses are carefully analyzed to find a relation between the data fields. One example of such links can be:

Customers with a yearly salary above $50000 are placed in the top 10%, while customers with an annual salary below $50000 are in the bottom 20%. 

Following the same step, the whole table is sorted, comprising all the data and the associated hypotheses. This helps to understand whether or not the analysis is assisting in the process of segmenting the customers and separating one from the other. 

Tree-based Clustering Analysis

For such type of analysis, the data is categorized into quartiles according to the quality scores. “A” customers are the ones who have the best qualities while “D” represents the ones on the lowest quartiles. If the number of customers is large, then deciles can also be used. The characteristics of each quartile are evaluated by using the proxy variable to look for any obvious pattern. The found design is collected and taken into account. This helps in: Narrowing the herds of variables into a relevant few.

The tree is attractive to look at, and the information shared is easily understood. It effectively describes the cutoff points, which cannot be explained by regression analysis. During analysis, the first decision point is the most important and shapes the rest of the process. It is also better for the procedure if unnecessary branches are not added between the nodes. For example, segmenting 100 companies in groups of 2 based on industries, creating 50 different industries again, produces large amounts of data.  

Know more about Tree-based Clustering Analysis

Validation with Regression Analysis

After the segmentation is done by the different analysis methods, it is possible to validate them numerically by using regression analysis. Large sets of variables are taken, and multivariate regression analysis is done. The result helps in understanding which variables are not essential and which are too correlated to each other. Eliminate them and rerun the regression so that all the variables are significant enough and also a little independent of each other. Thus we find the segmentation variables for the project. 

Customer segmentation examples

Customer segmentation is done by all companies and is most effectively done by the companies that are the most successful. Among all these stories, one of the most famous maybe Target who used to be a pregnant woman. The company, by mistake, informed a lady’s father that she was pregnant before she had the chance to break the news.

The company had the information because a pregnant woman’s cart tends to have typical diapers and maternity articles. The analysis of the customer’s cart can evaluate the customer and segment him or her. This can increase the business effectively. 

FAQs about Customer Segmentation Model

What are the primary customer segments?  

The primary customer segments are demographic segment, psychographic segment, behavioral segment, and geographic segments. 

Why is customer segmentation important?

Segmentation helps the company to categorize the customers in terms of their preferences and needs. This allows the company to save money and effort and also increases the customer company bond. 

What are segmentation examples?

A few examples of segmentation are gender, age, personality traits, values, beliefs, lifestyles, etc. 

What are the characteristics of market segmentation?

The six main characteristics of market segmentation are: substantial, accessible, stable, differentiable, actionable, identifiable.

How is psychographic segmentation used?

Psychographic segmentations are used based on the values, personality traits, interests, beliefs, etc., of a customer. These traits are analyzed, and customers with similar characteristics are segmented. 

What is an example of behavioral segmentation?

Examples of behavioral segmentation can be: how the user became a customer or when the user became a customer, how frequently they use the product etc.  

What are the examples of geographic segmentation?

Geographical segmentation, as the name suggests, depends on the location of the customer. If the customer is based out of an area where temperatures get low, then he would be presented with warmer clothes more. 

What are the five main types of segments in demographics?

The five main types of segments based on demographics are based on age, gender, occupation, cultural background, family status.