What is market segmentation? Discover benefits and examples

Let’s face it. A one-size-fits-all approach no longer cuts it. Customers require relevance. 

Whether your users are browsing a homepage, opening an email, or engaging with your product feature, they expect experiences tailored to their needs and behavior. 

Segmentation delivers. It helps meet user needs with precision. 

Forget everything you think you might know about segmentation. It isn’t just simply slicing an audience into specific cohorts and hoping they convert. 

Rather, it’s a complete strategy that enables you and your team of product managers, marketers, and engineers to collaborate, personalize, and optimize across the entire user journey. 

Segmentation is key to your marketing success. 

In this comprehensive guide to market segmentation, you’ll learn exactly what segmentation really is, how it works, and why it’s critical for cross-functional teams. 

You’ll also get best practices, real-world examples, and a closer look at how Kameleoon transforms audience insights into action through AI-powered personalization and A/B testing.

You'll learn:

• What is market segmentation and why does it matter?
• What's the difference between segmenting and targeting?
• What is market vs. customer segmentation?
• The four main types of segmentation categories
• How to prioritize which segments to target
• How to create your segments: a five-step guide
• Predictive segmentation with AI Copilot
• Why segmentation is your cross-functional superpower

1  What is market segmentation and why does it matter?

Market segmentation is the process of dividing a broad audience into smaller, more specific groups, called segments. 

These audience segments share similar traits, behaviors, or needs. 

Breaking an audience into segments brings relevance to users. Instead of blasting the same message to everyone, it enables you to tailor campaigns, user journeys, and offers with precision. 

This personalized approach can help lift conversions, improve customer engagement, and strengthen product growth.

Segmentation is the foundation.

It helps you deliver the right message to the right group of people at the right time.

2  What's the difference between segmenting and targeting?

While segmenting involves targeting a specific audience, the two concepts are distinct. 

• Segmenting is the process of dividing your market into smaller subsets of individuals who share common characteristics like behavior, demographics, or interests.
• Targeting comes next. It involves crafting specific messages, campaigns, products, or experiences tailored to one or more of the segments.

You can think of segmentation as the strategic groundwork, and targeting as the tactical execution. 

As well, segmentation tends to be a long-term, ongoing process, while targeting is typically campaign-based and shorter-term. 

When used together, segmentation and targeting enable brands to deliver the right message to the right audience, at the right time, with greater precision and impact.

3  What is market vs. customer segmentation?

Segmenting your target audience into distinct groups, based on shared traits, creates more relevant, personalized experiences that convert. 

But when it comes to actually applying segmentation strategies, it’s important to clarify who you’re targeting.

That’s why the distinction between market segmentation and customer segmentation is critical. 

While the two terms are often used interchangeably, they actually represent two complementary approaches. 

Market segmentation 

Market segmentation is a broader strategy. 

It involves dividing your entire market, including both prospects and customers, into distinct groups based on characteristics like demographics, behaviors, geography, or psychographics. 

This approach is ideal for targeting new audiences and shaping top-of-funnel campaigns to attract the right customers at the right time. 

Customer segmentation 

In contrast, customer segmentation, specifically focuses on your existing or potential buyers. These are the users who are already familiar and have interacted with your brand. 

Customer segmentation draws on historical data like purchase behavior, frequency, loyalty status, or average order value to create more nuanced segments. You might use customer segmentation to identify high-value repeat shoppers or deliver exclusive offers to drive retention and upsell. 

It, therefore, helps you deepen relationships with loyal customers over time. 

Blending marketing and customer segments 

When brought together, both market and customer segmentation create a complete strategy that informs product decisions, improves testing accuracy, and drives sustained business growth. 

With a full-funnel web experimentation platform like Kameleoon, your team can apply both approaches to turn segmentation into a dynamic, revenue-driving force.

4  The four main types of market segmentation categories

Within both market and customer segmentation lenses, there are four primary ways to segment audiences. They include: 

• Behavioral criteria
  • Based on user actions, like browsing, purchases, device or feature usage
  • For example, a clothing retailer may recommend certain products based on past purchase behavior
• Geographic criteria
  • Relates to user location or local context, like weather, geolocation, region, or time of day
  • For example, a sporting goods retailer may recommend winter jackets to users in cold climates but lightweight gear to those in warmer regions
• Psychographic criteria
  • Based on values, lifestyle, beliefs, and interests
  • For example, a travel site may filter users into beach or mountain categories to personalize web offerings
• Demographic criteria
  • Assesses factors like gender, age, nationality, income, or profession
  • For example, a fashion brand may serve different homepages to users by gender 

This diagram shows the four main segmentation categories:

5  How to prioritize which segments to target

When segmenting across these four main pillars, it can be difficult to know where to begin. 

Here’s the key: identify high-priority segments that align most closely with your strategic goals. Targeting these segments will have the greatest potential to impact on your ROI. 

But how do you know which segments these are? 

Use these three factors to guide you: 

1. Relevance

Start by evaluating how well a segment aligns with your business objectives. 

A relevant segment is one that directly supports your current growth strategy, whether it’s driving revenue, increasing retention, or expanding into a new market. 

2. Profitability 

Not all segments are created equal. 

To be worth targeting, a segment must offer clear business value. 

It should be large enough to justify the effort in targeting it. It should also demonstrate strong purchasing power, and show a high likelihood of converting or engaging. 

If a segment lacks scale, intent, or profitability, targeting it may not be a strategic use of resources. 

3. Accessibility 

Even the most promising segments are only valuable if you can actually reach the needs and expectations of the audience you’re trying to engage. 

Before targeting a segment, consider whether your team has the right channels, tools, and messaging frameworks to effectively access the audience. 

Here’s a summary checklist to help you prioritize which segments to target:

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6  How to create your segments: a five-step guide 

Prioritizing segments based on relevance, profitability, and accessibility helps ensure your efforts are focused on what matters most: delivering measurable, profitable returns. 

But once you’ve identified high-value segments, how do you actually build these segments and track their impact? 

Here’s a five-step action plan to help guide you: 

1. Choose your segmentation methodology 

Before you begin building segments, you need to decide how you’ll define them. 

There are two main methodologies: 

• A priori segmentation (rule-based)
• Post-hoc segmentation (cluster-based) 

A priori segmentation (rule-based) 

This process involves dividing your audience into predefined segments based on attributes like age, gender, or location. 

These segments are usually built using research, industry benchmarks, or internal data that suggests which markets are most relevant to target. 

Here’s a visualization showing an a priori segmentation of audience by age group:

But you aren’t limited to segmenting by a single variable, like age. 

You can also segment by multiple factors. 

For example, a fashion brand might use a priori segmentation to define rules a website should show winter coats to women in London during December but swimwear to Spanish men in June. 

While setting these rules, and segmenting audiences by them, can offer valuable insights to help guide optimization decisions, a priori segmentation has three main limitations. 

These limitations are that: 

• The approach is only effective if you already have a strong understanding of your market
• You need access to highly reliable demographic or contextual data
• It makes assumptions based on trends that may not reflect individual intent 

For example, some female shoppers in London might actually be looking for vacation swimwear, not winter jackets. In these situations, data-driven flexibility is essential. 

Post-hoc segmentation (cluster-based) 

That’s where post-hoc segmentation comes into play. 

Also known as cluster-based segmentation, this approach is the opposite to the a priori approach. 

Instead of starting with predefined segmentation criteria, post-hoc segmentation organically uncovers and defines segments, but only after observing real user behavior and identifying the patterns that emerge. 

These patterns can include browsing journeys, product preferences, survey responses, or other user behaviors like non-purchasing users, one-time buyers, or frequent buyers. 

Here’s a visualization of how cluster-based segmentation might look by purchase behavior:

Because these clusters are based on real-world behavior, rather than assumptions, post-hoc segmentation often results in more accurate, actionable audience targeting.

On the downside, if the post-hoc analysis isn’t guided by clear goals, it can reveal clusters that may look good, but don’t statistically align with business objectives or customer needs. 

So it’s ideal to blend both methods. 

How Kameleoon enhances both approaches 

Kameleoon’s has been designed to support both segmentation methods, and goes a step further with its AI Copilot. 

Using machine learning to analyze behavioral and contextual data in real time, it automatically creates dynamic segments that adapt with each interaction. 

So whether you already have clear audience rules, or you’re just beginning to explore segmentation, Kameleoon empowers you to experiment, refine, and scale with confidence. 

2. Define what success looks like 

After choosing your segmentation method, whether a priori, post-hoc, or a blended approach, get clear on why you’re segmenting in the first place. 

Your segmentation goals shape everything: what data you use, how you group users, and how you measure success. 

Start by asking yourself, is the primary goal to: 

• Improve customer retention?
• Increase market share in a specific region?
• Reduce email unsubscribe rates?
• Grow average order value or repeat purchase rate?
• Something else? 

The more specific and outcome-driven your goal is, the easier it becomes to track, measure impact, and prove the ROI. 

3. Analyze the data 

Next, once you’ve clearly defined your goals with specific, measurable outcomes, review any customer data you already have. 

Look for patterns that show which segments are most active, profitable, or under-engaged. 

Ask questions like: 

• Which customer types are currently driving the least or most revenue?
• What behavioral trends are tied to churn or conversions?
• What common traits appear among low- or high-value users? 

The answers will help you uncover natural breakpoints for segmentation. Also consider if you’re going to use hot or cold data. 

Hot data 

Hot data is real-time, in-session data generated during a user’s visit. Using hot data enables real-time personalization and behavioral targeting. 

Examples of hot data include: 

• Behavioral signals like browsing journey or time on site
• Contextual data like geolocation or weather
• Technical details like device or browser type 

Cold data
Cold data is the opposite. It’s historical or stored data. 

It’s typically saved with your CRM, CDP, or analytics tools. Because it shows past behavior or known characteristics, it helps build richer, longer-term customer profiles. 

Examples of cold data include: 

• Demographic attributes, like age, gender, or occupation
• Purchase history, frequency, recency, or order value
• Email engagement
• Loyalty status 

Here’s a visualization of how you might choose to segment by hot or cold data:

As you might imagine, the most effective segmentation strategies don’t rely on hot or cold data alone. Instead, they combine both together to build meaningful, actionable customer segments that align with business goals.

One great aspect about Kameleoon’s AI Copilot is it combines hot and cold data to dynamically segment users, even on their first visit. 

In fact, without any historical user data, Kameleoon’s AI can immediately assess conversion likelihood and trigger highly relevant personalized content or offers in real-time. 

This dynamic approach enables businesses to deliver tailored experiences from the very first interaction, enhancing engagement and improving conversion rates. 

4. Develop your segmentation strategy 

After you’ve defined your audience and the data points you plan to use, you need to build a segmentation strategy that aligns with your business goals. 

For example, an online grocery site might have the goal to improve user retention by increasing member login rates. 

Hot and cold data analysis might reveal that users who login daily are 3 times less likely to churn. 

In this case, it would be wise to segment users by login frequency. 

Behavioral insights could then be applied to tailor messages or features to specific user segments to reinforce shopping habits across product categories. 

Here’s a visual of how this segmentation strategy could work:

5. Apply segments in targeting 

Once you’ve defined your user segments, the next step is to activate them across your different marketing and product touchpoints. 

Here are some of the most effective ways to bring such segmentation to life: 

• Personalize advertising by serving tailored ad creatives and high-converting copy to specific segments, based on what you know works through past browsing behavior, purchase history, or segment-specific traits.
• Tailor discounts and incentives by offering personalized promotions to different user segments based on their behavior or relationship status, like new visitors or VIP customers, to increase conversions and customer loyalty.
• Enhance email workflows by triggering automated campaigns for key segments like cart abandoners, one-time buyers, or high-value repeat customers.
• Customize web journeys by adapting headlines, offers, or content blocks dynamically, in real time, to align with specific demographics, geographies, or audience interests.
• Segment product offerings and present different versions or bundles of a product based on customer needs, preferences, or price sensitivity.
• Inform product roadmap decisions and identify high-impact segments and shape features, or prioritize roadmap improvements, based on audience insights.

By applying segmentation to your different marketing channels, you can increase customer relevance, and drive more leads or sales. 

Here’s a summary 5-step checklist to help you achieve segmentation success:

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7  Predictive segmentation with AI Copilot

There’s no doubt about it: market segmentation is powerful. But properly implementing it can be incredibly complex. 

In fact, 72% of marketers report challenges translating their visitor data into actionable insights. 

Furthermore, 62% say they struggle to create personalized content at scale. 

That’s where predictive segmentation steps in, and where Kameleoon’s AI Copilot delivers a game-changing solution. 

What is predictive segmentation? 

Predictive segmentation does the busy work for you. 

It uses machine learning to analyze real-time visitor behavior. It then assigns users to the most relevant audience segment, even on their very first visit. 

Rather than relying on static rules, predictive algorithms adapt to continuously identify patterns and correlations that inform more intelligent targeting. 

Over time, the AI becomes increasingly accurate at determining which visitor belongs to which segment, enabling real-time personalization at scale. 

How AI Copilot elevates segmentation 

Kameleoon’s AI Copilot enhances both rule-based and behavioral segmentation with predictive capabilities that: 

• Analyze behavior in real time
• Dynamically group users based on evolving patterns
• Create self-optimizing segments for A/B tests and personalized experiences 

These capabilities unlock high-performance experimentation and personalization without manual setup or predefined criteria. 

When to use predictive segmentation 

• Predictive targeting is especially useful when you want to:
• Segment groups that are ambiguous or constantly changing
• Understand complex, multi-dimensional data that can’t be modeled manually
• Personalize experiences for first-time visitors without historical data 

In these cases, predictive algorithms provide deeper insight and broader reach than a priori segmentation can. 

Here’s a visualization showing how effectively predictive segmentation can identify potential buyers, compared to other models:

Case study: predictive segmentation in action 

Predictive segmentation has been used to help many Kameleoon clients. Here’s a real-life case study example that helped one client achieve double-digit conversion rates: 

Challenge:

• An online tire retailer wanted to identify and target their high-value “power user” segment
• They identified their most important user segment as motorists who drove over 24,000 km per year or owned multiple vehicles

Solution: 

Using AI Copilot, the brand implemented predictive targeting to estimate each visitor’s likelihood of being a power user. The algorithm analyzed: 

• Hot data: Browsing journey, tire preferences, geolocation, referral source, session duration, visit frequency
• Cold data: CRM details like buyer type (individual vs. professional), purchase history, and form data 

Results: 

By using AI Copilot, the brand was able to: 

• Identify 48% more power users, compared to manual segmentation
• Achieve a 16% increase in average cart value 

These compelling results show how predictive segmentation can empower brands to instantly go beyond assumptions and adapt to real user behavior. 

When combined with Kameleoon’s web experimentation platform, AI Copilot creates a self-optimizing growth engine.

8  Why market segmentation is your cross-functional superpower

Predictive segmentation can be your secret weapon. But it doesn’t just need to be closely guarded by marketers. 

It can also be your cross-functional team’s strategic advantage. 

In addition to using segmentation to increase conversion and retention rates, product teams can also use it to prioritize features and personalize onboarding. 

Additionally, engineering teams can use it to build dynamic experiences by cohort. 

With Kameleoon, segmentation can easily transform into a company-wide growth lever.

Ready to get started with market segmentation?

Segmentation is no longer a nice-to-have feature. It’s the core of modern personalization and experimentation. 

Whether you’re optimizing funnels, building better products, or delivering real-time relevance, the right segmentation strategy will get you there faster. 

Start building smarter segments now. Click here to start building smarter segments with Kameleoon’s real-time personalization platform.