What Is Customer Segmentation?

Customer segmentation is an invaluable tool in your bid to personalize products and marketing communications for greater profitability. This process delivers key insights, such as what drives customer loyalty, which segments are most profitable, and more.

If you’re wondering how best to identify your customer segments, we’re here to lend a hand. In this article, we answer your key questions and provide step-by-step segmentation guidelines, including how to use the best customer relationship management (CRM) software to analyze customer data.

What Is Customer Segmentation?

Customer segmentation is a way of grouping customers based on shared characteristics and behaviors. It enables you to personalize your sales approach and enhance your products and customer experience according to different needs.

What Is Customer Segmentation in Marketing?

Customer segmentation in marketing lets you target multiple audiences with tailored communications and offers. By making customers feel special and providing relevant promos, you increase key performance indicators (KPIs), like customer loyalty.

There are various ways to define your segments based on the type of analysis you’re performing. You can even have overlapping segments. For instance, you could group your audience by country, age, and preferred device.

Why Is Customer Segmentation Important?

Customer segmentation is vital for offering personalized experiences, retaining your customers, and growing your business.

Specifically, it can help you:

• Grow engagement on marketing channels
• Increase customer lifetime value and loyalty
• Design new or existing products
• Enhance customer experience and support
• Leverage automation and save time
• Increase sales
• Decrease business risk
• Set you apart from competitors

7 Types of Customer Segmentation

The most common ways to segment your customers are into demographic, psychographic, firmographic, behavioral, geographic, needs-based, and technographic groups.

Demographic Segmentation

Grouping your audience into demographic segments helps you provide targeted services and messaging. For instance, a mass-market retailer may provide budget, standard, and premium products to cater to different customer income levels.

Demographic factors include:

• Age
• Gender identity
• Ethnicity
• Occupation
• Disposable income
• Share of wallet
• Marital status
• Dependents status
• Homeownership status

Psychographic Segmentation

Psychographic factors let you categorize customers based on how they think and live. For example, you can market a service differently to those with an eco-conscious mindset.

Psychographic factors include:

• Hobbies and leisure
• Political views
• Social causes
• Values, such as eco-friendliness
• Personality types
• Preferred media channels
• Sports preferences
• Music preferences

Firmographic Segmentation

Firmographic segmentation is based on customers’ work-related information. This method particularly suits B2B companies wanting to pitch and deliver projects in more tailored ways.

Firmographic variables include:

• Industry
• Company size
• Job title
• Job seniority
• Job tenure
• Qualifications and awards
• Decision-making power
• Professional association membership

Behavioral Segmentation

Behavioral segmentation groups customers based on their interaction with your brand, including their purchasing patterns. For instance, you could offer one-time buyers and frequent buyers two different experiences.

Behavioral factors include:

• Purchase amount
• Purchase frequency
• Price elasticity, or how customers react to changes in price
• Tenure with your brand
• Last sign-in date
• Time spent on your website

Geographic Segmentation

Regardless of your reach, you’ll find geographic segmentation very useful. For example, it can enable you to use local dialects and cultural references in your communications.

Geographic factors include:

• Urban/suburban/rural environment
• City
• State
• Country
• Hemisphere
• Language preferences
• Cultural preferences

Needs-Based Segmentation

Segmenting your customers based on needs is useful for designing and promoting new products. It can also enable you to provide enhanced support, such as automating your customer service.

It’s useful to distinguish between customers’ personal or professional needs and their product-related needs.

Personal and professional needs include:

• Time constraints
• Pain points, such as a lack of adequate information
• Event-based needs (wedding, birthday)
• Industry-driven needs, such as compliance

Product-related needs include:

• Cost
• Project/subscription duration
• Product features
• Communication type and frequency
• Customer support

Technographic Segmentation

Technographic segments split customers based on technology use and preferences. This enables you to personalize digital experiences and increase engagement for different groups.

Technographic factors include:

• Preferred device types
• Preferred browser
• Preferred operating system (OS)
• Preferred social media platforms
• Time spent on social media
• Average email read time
• Openness to new technology

How To Segment Your Customers

1. Set Clear Targets

Setting targets allows you to use resources efficiently and extract insights that deliver business benefits. Ignoring this step could lead to impractical segmentation results that get permanently shelved.

So, start with your problem statements. What could you improve in customer-facing departments, like marketing and product? For example:

• Do you have email open and click rates that are lower than your industry average?
• Is a lack of personalized pitching damaging your sales targets?

Once you’ve pinned them down, formulate the ideal solution for each one, such as:

• Improve email marketing performance through personalized segment-specific messaging.
• Increase deal sizes and close rates by pitching to segment-specific needs.

2. Identify Relevant Variables

Each segmentation target should have a set of relevant variables. These are quantitative or qualitative attributes you’ll analyze about your audience. For instance, a residential realtor marketing to new customers would track variables such as geographic location, income, marital status, home-related needs, and hobbies.

Your ideal variables could be among the demographic, technographic, or other segment types we covered. However, you should also include KPIs to examine links between customer characteristics and business results. Identify relevant metrics at different customer touchpoints, such as email click and open rates, page views, deal close rates, satisfaction rates, and churn rates.

3. Collect Customer Data

Next, collect the data associated with your segmentation variables and targets. You’re likely already tracking some of it, and other data you’ll need to gather from customers.

Here’s a list of essential data collection sources and methods:

• Leverage your CRM database: Your customer records contain rich information, such as age, location, job title, interests, past purchases, and more. Run reports focused on your chosen segmentation variables.
• Collect social media data: Also known as social listening, documenting online engagement with your brand helps you analyze audience sentiment and brand perception. Record quantitative and qualitative data, including the number and content of posts and comments.
• Extract email marketing data: Download email engagement reports featuring open, click, and unsubscribe rates, plus other key metrics. Also, track emails’ type, tone, content, and word count for enhanced context.
• Export commercial and financial reports: You’ll likely find these in your accounting software or ecommerce platform. Ensure they contain customer identifiers, like names and transaction IDs, so you can analyze transaction data alongside customer data.
• Conduct customer surveys: These are especially useful if you’re missing key segmentation variables, or need up-to-date stats. Clarify the survey aims, like gathering product feedback or general market research, and offer incentives, such as gift cards.
• Hold customer interviews and focus groups: These are most useful when seeking granular or personal insights. For instance, ask how participants perceive your brand and products, how they describe themselves, and what marketing messages they most relate to and why.

4. Perform Customer Segmentation Analysis

The last step is performing analysis—drawing actionable insights from the collected data according to your segmentation targets.

Let’s look at this step in detail.

What Is Customer Segmentation Analysis?

Customer segmentation analysis is a process of identifying patterns in your data that indicate how different segments behave, and how they impact your KPIs.

This crucial stage empowers you to make evidence-backed decisions across sales, marketing, product, and other areas. In turn, the methodical approach can lead to measurable service improvements and risk reduction.

Sounds scary? Don’t worry. We’ve broken down the process for you.

Customer Segmentation Analysis Steps

1. Define Your Objectives

Haven’t we already set targets? Yes—but your customer segmentation targets describe business-level aims, like crafting more personalized sales pitches. By contrast, analysis objectives are specific to your variables and data sets.

Here are a handful of examples using the SMART objective framework.

2. Clean and Organize Your Data

For many businesses, collected data doesn’t arrive in mint condition. For instance, it might include typos, unlabeled columns, and duplications. To avoid errors, spend time cleaning and organizing it.

Here’s an example: When designing a loyalty program, you’ll analyze variables including customer demographics and spending amounts. So, cleaning and organizing data involves exporting CRM reports, isolating the required data, labeling data sets, and removing errors. You’ll also categorize the data into sheets and tabs according to, say, time periods and products.

Top tip: Depending on your audience’s jurisdiction, cleanups may include anonymizing and protecting customer data sets, especially financial ones.

3. Find Data Patterns

Next, search for patterns in your data. For instance, these could include correlations between customer buying behaviors and satisfaction rates.

You can use Excel data tools for small sets and less complex objectives, like checking what age group contributes the most to your revenues. However, confirming statistical relationships between variables, including correlation, multivariate, and cluster analysis, requires specialized software.

There are two main ways to find data patterns using software:

• Do it yourself (DIY): By this, we mean hiring a statistician and equipping them with statistical analysis software, such as SAS and IBM SPSS Statistics. Provide them with your cleaned-up data sets and analysis objectives, and wait for the science-backed conclusions to pour in.
• Use your CRM’s AI tools: CRM products, like HubSpot and Salesforce, have inbuilt AI segmentation features that find statistical patterns in your dataset. While it doesn’t offer as much control over variables and tests as the DIY method, using CRM tools is quicker and possibly cheaper.

4. Define Your Segments

Now, use the data patterns you identified to define individual customer segments.

Say your analysis objective is to find your top three frequent-buyer groups. You learn that frequent spending is correlated with lower age groups, tech-savvy iPhone users, and extroverted personality types. These attributes could form the basis of three different segments, or prompt you to check if they overlap and represent one segment instead.

Defining a segment looks different for B2C and B2B businesses:

• Consumer personas: The persona is a hypothetical target for a campaign or product with human-like traits, needs, and behaviors. For instance, a flower business can have the Sweetheart, the Guest, and the Decorator as consumer personas based on common purchasing reasons.
• Business segments: These are defined by firmographic factors, like job title and decision-making power, as well as needs and geographic location. A consulting firm, for instance, targets buyer segments like C-level executives, innovation directors, and procurement decision-makers. Simultaneously, it could target industry segments, such as financial services, technology, and engineering.

5. Detail Segment Preferences and Follow-Ups

The final step is adding context and actionable recommendations to each customer segment. This helps your team better understand each customer type, avoid misunderstandings, and implement findings in their day-to-day jobs.

Here are useful details to add to your segment description: