The need for customer segmentation research arises from a simple fact – No two customers are alike. With highly competitive markets, customer experience takes center stage to improve customer loyalty and growth.
And the path towards driving engaging experiences starts with understanding your customer base, i.e., their needs and preferences.
By employing the right segmentation techniques, you can effectively target and engage different customer types with personalized strategies to drive conversions and build a solid customer base.
In this blog post, we will delve into different customer segmentation types and get you started on categorizing your customers. We have also added different means to collect data for customer segmentation analysis.
So dive in if you want to unlock the full potential of your customer base for growth.
What Is Customer Segmentation?
Customer segmentation is the process of categorizing the customer base into different groups based on their traits like
- Product usage
- Purchase value
- Average lifetime value
- Purchase behavior
Each customer has their preferences, expectations, needs, and traits. So, treating your entire customer base as one makes no sense.
By understanding the differences between customers, you can visualize your most profitable customers, the ones with high purchase potential, frequent users, etc. It would help to develop personalized strategies to target each segment individually.
Difference Between Market & Customer Segmentation
Market and customer segmentation processes overlap but also differ based on the target audience.
Market segmentation helps you categorize your target market into different segments, while customer segmentation focuses on existing customers.
Let’s first talk about the similarities between the two. As you may have guessed, some of the common properties would be
- Demographic traits
- Psychographic traits
- Geographic characteristics
Now, customer segmentation would add a new layer to this distinction with the traits of existing customers, like:
- Time of association with the brand
- Customer lifetime value
- Frequency of purchase
- Average order value
- Customer rating
So, market segments focus on who you want as your customer, while customer segments are who you have as a customer.
For example, a market segment can be potential customers from New York who earn more than $25000 a year and watch Football. Based on these traits, you can design marketing strategies to bring them into the conversion funnel and improve acquisition.
When this prospect becomes a customer, other traits like their favorite team, birthday, and the number of purchases would be associated with it. Based on these characteristics, you can now target this segment with personalized offers and strategies to improve sales and retention.
Why Is Customer Segmentation Important?
1. Identify the Most Profitable Customers
At the risk of repeating ourselves, not all customers are the same. Some bring in more revenue than others, and these customers are responsible for balancing and even offsetting your acquisition costs.
Think about it!
If the average acquisition cost for your campaigns is $110, you need to make at least this much revenue from each customer to break even. In reality, not all customers would generate this much money. Some would leave early, causing losses.
That’s where your high-value customers come to your rescue. The purchase value of these customers helps to balance the losses and contribute to the profit generated by your customer base.
Using a proper CRM tool like BIGContacts, you can run a value segmentation to find such customers and come up with ways to turn them into brand ambassadors.
2. Gauge the Actual Consensus of Your Customers
Viewing the customer base as a single entity may seem simple for management, but it poses its own problems when trying to get a pulse of your customers’ needs and expectations.
Read More: Voice of the Customer: A Complete Guide
It becomes more complicated when you want to use these insights in product development and optimization.
Suppose you run a simple survey across your entire customer base and get the following result:
Which feature should we build next?
|A – 35%
|B – 28%
|C – 37%
The votes are so close. How would you know which feature would achieve more customer engagement and positive reception?
Quite challenging, right?
But if you look closer and segment the respondents, say based on the total purchase value, you can see if high-value customers want a specific feature.
In the same way, you can categorize the respondents based on regular/casual users or paid/free users to get more in-depth context into the votes.
3. Build Ideal Customer Personas and Journeys
A customer persona is a fictionalized customer with the characteristics of a particular customer segment.
For example, a customer persona can be a 25-30 years old marketing expert with income between $15000-25000 who uses SAP in their organization. With this knowledge, you can see where your product offering would fit among their workspace tools.
Building customer personas helps to map the needs and issues of different customer segments across their journey. You can see the problems various segments face and develop relevant measures to resolve them. It would help design seamless experiences for each customer segment.
Read More: How to Build Customer Personas
4. Create Tailored Experiences
Customers want personalization from businesses and are even willing to pay more.
Personalized experiences can drive engagement and loyalty toward your brand. And it all starts with understanding the customer base.
You need to map their habits and behavior to design personalized experiences for each customer.
For example, Netflix shows you the recommended shows and movies based on your watch history. Or email campaigns that target customers based on their purchase history or lifestyle.
5.Explore Upselling and Cross-Selling Opportunities
Delving into different customers’ requirements and needs helps develop ideas to improve the average order value.
Let’s take the example of a laptop manufacturing company. Once they have grouped the customers based on their laptop needs, like gamers, professionals, etc., they can explore opportunities to improve the average purchase value.
They can pair gaming accessories with their laptops to improve the order value. In the same way, they can offer a 3-month subscription for a workspace tool like Microsoft365 with laptops designed for office professionals.
7 Types of Customer Segmentation Models
There are 7 broad categories in which you can segment the customers:
1. Demographic Segmentation
Demographic customer segmentation groups the customers based on social characteristics like:
- Marital status
Dividing the customers based on socioeconomic characteristics allows businesses to tailor product offerings, campaigns, and other strategies accordingly.
For example, a clothing company can create different campaigns for male and female customers to increase the average order value, just like gender-based ads from Nike.
2. Firmographic Segmentation
Firmographic segmentation is used for B2B customers to segment them based on organizational characteristics like:
- Experience (in years)
- Software usage
- Executive Title
3. Geographic Segmentation
Another most used way to cluster customers is according to their location. Customers’ needs, issues, and preferences may vary from city to city. Using geographic customer segmentation, businesses can map these challenges to develop effective solutions.
For example, a shipping company may have to set up multiple warehouses in larger cities to ensure timely delivery compared to smaller towns.
4. Value Segmentation
Probably one of the top three customer segmentation models, value-based cohorts serve a lot of different purposes for any business.
They help you identify the most profitable customers and the ones with the potential to become high-value customers with proper targeting. Once you have identified such segments, you can add another layer of characteristics to understand their behavior and interests to create nuanced experiences and deliver customer delight.
Another important aspect of value-based customer segmentation research is directing the marketing budget toward high-value targets.
For example, you can create a separate tag -‘ HVC(high-value customer)’ in your cloud-based CRM and helpdesk to automatically categorize tickets of customers with CLV above a certain threshold, say $700. It would help to prioritize the concerns of these customers.
5. Technographic Segmentation
Technographic customer segmentation focuses on the technological adoption of your customers (B2C and B2B) to group them.
For example, a laptop manufacturing company may categorize its users based on their needs and preferences, like professionals, gamers, graphic designers, casual users, etc.
Matching these characteristics with other traits like income and job type, the manufacturer can launch laptop models with specific configurations to target different user types.
6. Behavioral Segmentation
This type of customer segmentation looks at the behavioral patterns and characteristics for grouping the customers. These include:
- Regular shoppers
- Seasonal buyers
- Bulk shoppers
- First-time product users
- Churned users
Suppose a customer’s purchase history shows they do Christmas shopping every year for more than $2000. In that case, you can send them a discount coupon or notification about an upcoming seasonal sale to increase the average order value.
7. Psychographic Segmentation
Psychographic segmentation combines customers’ hobbies, interests, beliefs, and personalities to group them into different cohorts. It lets the brand connect with the customers at a deeper level by aligning the brand with the core beliefs and interests of the customers.
For example, a food delivery app may ask customers to donate $1 for a cause when they order food, like feeding people without housing. Or a shoe company that donates a pair of shoes for every pair sold.
Examples of Customer Segmentation Models
Now that we know the meaning of customer segmentation by definition, let’s look at real-life examples for each.
Google Adwords lets you adjust the demographic settings to personalize the ad campaigns.
Amazon’s laptop buying guide is designed based on user types.
Clothing ads based on regional climate.
Privileges and additional benefits for customers based on their income and yearly spending.
Standard Chartered offers different account and deposit types based on customers’ purchase preferences and saving habits.
TOMS’s one-for-one campaign to donate one pair of shoes for every order.
4 Methods to Gather Customer Segmentation Data
Surveys and customer forms are among the best sources of zero-party data that can reveal valuable insights about your customers. You can use this to gauge their experience, issues, problems, expectations, behavior, lifestyle, etc.
The best part is the flexibility of deployment and cost-effectiveness. You can use a dedicated survey tool like Qualaroo to deploy the surveys on multiple platforms like your website, app, and mail to target specific customers.
It can help you collect different data sets related to demographic, psychographic, technographic, and other characteristics.
Read More: What Question Should I Ask
Another benefit of using surveys is relevancy. Suppose you are targeting multiple segments using the same survey on your website. In this case, you can use question branching to collect relevant information from respondents.
With skip logic, the respondents would see the next question based on the previous answers.
So you can even disqualify irrelevant respondents from the survey using screening questions.
2. Customer Management System or CRM
A customer management platform such as BIGContacts is the next best source of customer segmentation data for you.
You can use it to create value-based and behavioral segments with data like:
- Contact information
- Purchase history
- Interaction history
- Usage history
- Lifetime value
- Churn data
- Average value
- Preferred communication channel
3. Behavioral Data
Next in line comes behavioral tools like heatmaps and session recordings. These help in mapping user flows and on-page customer behavior. You can visualize the steps customers take to complete the goals and where they struggle.
This data type is useful for gauging the product experience of different customer types, like new users, early adopters, and churned customers.
You can analyze the data to resolve the issues and streamline the product workflows to deliver customer delight.
4. Analytics Data
If you host a website or app, analytical tools like Google Analytics(GA) can help you understand your website’s customer behavior and journey. You can gather data on various interactions like:
- Most visited pages,
- Average cart value
- Traffic sources
- Goal completion rate
Customer Segmentation Strategy: 3-Step Process
With everything in order, it’s time to tackle the task of customer segmentation analysis. The data sets may seem mountainous, but the process is rather simple.
1. Sketch the Scope of Your Project
You should have an idea of the end result of your project to understand your project scope.
The customer segmentation campaign’s goal would help you find and target the right people within your customer base.
2. Collate the Data Under One Screen
The next step is to bring the customer data sets under one screen. This includes all the data from CRM, GA, surveys, and service points.
You can pull the data into a spreadsheet or use a tool like Kissmetics to assist you with the customer segmentation process.
3. Create Relevant Segments
Now that you have the data, it’s time to categorize it and create viable customer segments
Here is an example of different segmentation types:
|Canada, North America, England
|Quebec, Seattle, Los Angeles, London, Liverpool, Manchester
|Urban, suburban, rural
|Boomer, Millennials, GenZ
|Level of Education
|Grade school, high school graduate, university graduate
|Male, female, non-binary
|Single, Married, Divorced, separated, widowed
|Under $10,000;10,000- 24,999;25,000- 39,999;40,000- 59,999;55,000+
|Experience (in years)
|Less than 1 year,1-3 years4-5years5-8 years8+ years
|IT, automobile, marketing, Manufacturing
|Student, athlete, office-goer,
|Less than $299,$300-$499;$500-$1000;$1000+
|User, ex-user, prospect, first-time visitor, repeat visitor,
|Risk of churn
|High, medium, low
|Regular user, light user, rare user
4. Parse the Data to Create Personas
Now, we can group customers with specific traits to build target customer personas.
Suppose you observe that a particular product or product category is popular among individuals aged between 20-25 years and from a specific location. Then, you can pitch the products to similar customers to increase sales.
You can create different personas to find the ideal customers for your product and marketing campaigns.
Stitching It Together: Customer Segmentation for Business Success
Customer segmentation is an indispensable component of modern marketing strategies as it lets businesses understand their target audiences better.
Remember, the key to successful customer segmentation is employing the right techniques and refining the process.
Start by using a dedicated survey tool like Qualaroo to collect customer data using simple demographic and experience surveys. Then collate the data with your CRM tool’s existing customer usage data.
Once you have the customer personas, send them to different teams to create customer journey maps. It will help you visualize the issues and opportunities to optimize customer experiences.
Implement the strategies and measure the impact on your business KPIs. Then, rinse and repeat.
Now that you’re equipped with this actionable plan, it’s time to harness the power of customer segmentation.
Frequently Asked Questions
Customer segmentation is the process of categorizing the existing customer base. Market segmentation helps to segment the target market and prospects.
Customer segmentation is useful in several strategies, like product development, optimization, marketing, and personalization.
Market segmentation helps to design campaigns to increase acquisitions, retention, and customer lifetime value.
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