7 Types of User Segmentation Explained (+Examples, Strategy, and More)

If there’s one underappreciated – yet vital – task that product managers must get right, it’s user segmentation.

Understanding that you cater to many different types of customers with different pain points, wants, and needs is critical for giving them the best possible experience.

In this article, we will explore seven types of user segmentation, explain when you might use them, and how you can leverage them within your own SaaS.

Types of user segmentation summary

• Customer segmentation is the process of splitting users into groups based on shared characteristics. There are many different ways to segment and define user segments.
• It’s important to define and execute a clear user segmentation strategy for a number of reasons: customer segmentation helps you personalize in-app experiences, improve retention, and drive product success.
• There are many types of user segmentation models to choose from.
• Demographic segmentation means segmenting users based on demographic information or their individual characteristics, i.e., age, gender, location, and more.
• Behavioral segmentation is all about creating a target segment based on product usage. Basically, how does a customer interact with your product or service?
• Psychographic segmentation is a user segmentation model based on shared psychological traits, like values and beliefs.
• Customer data segmentation is based on grouping users according to their usage history.
• Firmographic segmentation focuses less on individual attributes and more on information about the companies your users work for (i.e., size, industry).
• Technographic segmentation lets you target groups based on their usage of technology – the device they use, browser, device preferences, and more.
• Needs-based segmentation is based on grouping customers according to their underlying user needs.
• With so many different customer segmentation models to choose from, implementing them in your own SaaS might feel overwhelming. But there are some clear steps to follow regardless of the context.
• Start with defining what goal you’d like to achieve. You can use your objectives to define the customer segmentation type you’ll choose later on.
• The next step is about gathering the data you need to build a clear understanding of customer segments. You can gather data via product usage (i.e., feature and event tagging) or surveys.
• Once you’ve gathered your data, you’ll start to see the different customer segmentation types emerge.
• Next, you can dive into the analysis and comparison stage. Tracking how different groups of customers are behaving can help you identify power users and inactive ones.
• Finally, you can launch targeted experiments to figure out the impact of in-app messaging on different user segments.
• But the most important aspect of all of this? Putting what you learn into practice to optimize the customer experience.
• Segmentation can help you launch personalized onboarding experiences. By crafting bespoke journeys with relevant content, you give your users a faster route to value and get them off to a fast start.
• You can also use other forms of personalized messaging to boost engagement. Create content (i.e., relevant offers, helpful tooltips, and prompts) that will appeal to different segments at the right points in the journey.
• You can also use segmentation to help you identify and target at-risk users accordingly to reduce the churn rate.
• Finally, use segmentation to figure out who your ‘power users’ are and leverage their expertise for beta testing.
• If you want to build advanced user segments easily, give Userpilot a go. Book a demo to see its full functionality.

What is customer segmentation?

User segmentation is the process of dividing users into groups based on shared characteristics. These characteristics can be demographic, behavioral, or even psychographic.

For example, you might want to segment customers based on their age, location, interests, or spending habits. Segmenting customers can help your organization better tailor its products and run effective in-app onboarding to meet the needs of each group.

Why is it important to segment users?

User segmentation can be an incredibly powerful tool for improving customer satisfaction, boosting customer engagement, and driving growth. Here are some of the benefits of user segmentation:

• Customer segmentation forms the foundation for launching personalized experiences. Put simply, if you don’t understand your target audience down to a more granular level, it’s impossible to tailor the experience to their needs.
• When you segment customers and offer them personalized experiences, you massively increase the chances of retaining them – and eventually turning them into loyal customers.
• Segmentation has been proven to improve a vast range of product success metrics (not just sales efforts). For example, if you want to increase feature adoption, you could specifically target users who aren’t engaging with that particular feature using bespoke in-app messages.

7 types of user segmentation with examples

There are many customer segmentation models to choose from. We’re going to dive into seven of the most common types and explain how each is put into practice.

Hopefully, it’ll give you and your product teams some ideas about how to pick the right segmentation model and create segments accordingly.

1. Demographic segmentation

This type of user segmentation model is where you segment customers based on demographic factors, aka the characteristics of a person or population. It’s helpful for understanding the demographic makeup of your target audience.

Examples of demographic segmentation include:

• Age
• Gender
• Family makeup
• Education levels
• Where they live (geographic segmentation)

2. Behavioral segmentation

Behavioral segmentation is all about creating a target segment based on product usage. Basically, how does a customer interact with your product or service?

Examples of behavioral segmentation include:

• Product usage patterns (i.e., do they use a particular feature or not, volume, times of day, etc.)
• Common behaviors (i.e., always opening one feature first)
• Timing (how long does a particular user spend on distinct tasks)

3. Psychographic segmentation

Psychographic segmentation is based on shared psychological traits (i.e., rather than an attribute like gender or a behavioral pattern, this is about what people believe).

Examples of psychographic segmentation include:

• Values
• Interests
• Attitudes and opinions
• Lifestyle decisions

4. Customer data segmentation

This user segmentation type is focused on categorizing users based on real data: their usage history with your product. This type of analysis is very helpful for product teams to quickly improve performance metrics.

Examples of customer data segmentation include:

• Preferences
• Spending history and propensity to upgrade
• Seasonal trends in usage (i.e., a fitness app will spike in new users in January)

5. Firmographic segmentation

Firmographic segmentation focuses less on individual attributes and more on information about the companies your users work for. It shows that the segmentation process can also be ‘groups based’ (i.e., organization) rather than personal (i.e., of individual users).

Examples of firmographic segmentation include:

• Industry
• A company’s size (number of employees or customers)
• Growth stage
• Geographic location
• Financial information (i.e., gross revenue)

6. Technographic segmentation

Technographic segmentation lets you target groups based on their usage of technology. It can help you work out early adopters (i.e., those willing to try new technologies), and perhaps more ‘legacy’ users (who still use an outdated operation system, for example).

Examples of technographic segmentation include:

• Devices used
• Browser (i.e., Chrome vs. Firefox)
• Preferences (i.e., mobile or desktop)
• Operating system

7. Needs-based segmentation

Needs-based segmentation is focused on splitting users into groups based on the problems they need to be solved.

Examples of needs-based segmentation include:

• Price-focused (primarily concerned with costs)
• Quality (need the best experience and are willing to pay top dollar for it)
• Service-based (prioritize customer service)
• Partnership-focused (highest importance on trust and reliability on your team)

How to create a customer segmentation strategy for your SaaS?

With so many different customer segmentation types to choose from, implementing them in your own SaaS might feel overwhelming.

However, you’ll typically see a set of common steps that you can follow to define a customer segmentation strategy that’ll work for early adopters and returning customers, businesses large and small, power users, or casual ones.

Determine your business objectives and priorities

Start with why – what are you trying to achieve with segmentation? Once you’ve clearly defined your objectives, it makes prioritizing your efforts simpler as you’ll know where to focus your efforts.

You can use your objectives to define the customer segmentation model you’ll build later on.

For example, if your goal is to improve the onboarding experience, you may want to focus on technographic segmentation (i.e., to help you optimize usability on different device types).

Collect customer data to create user segments

Without customer data, you’ll just be relying on guesswork. This step is about gathering the information you need to build a clear understanding of customer segments within your product.

The choice of data you’ll gather depends on the priorities you set in the first step. You can collect data in a number of ways:

• Product usage data (through feature and event tagging)
• Surveys (i.e., welcome surveys to gather demographic info, or NPS surveys to collect customer satisfaction data)
• Customer interviews

Segment users based on priorities and data collected

Now that you’ve set your goals and gathered the data you need, you can start to create and define your customer segments.

You’ll need a powerful product analytics tool to help you out with this. One such tool is Userpilot which can be used to create detailed segments with multiple conditions.

Analyze customer segments and compare them with one another

Once you’ve got your segments, you can dive into the next stage: analysis and comparison.

Tracking how different groups of customers are behaving can help you identify power users, segments that are at risk of churning, and users that are inactive.

Identifying differences and similarities from one specific group to another is a great way to allocate your resources effectively (i.e., you can target improvements where they’re needed – perhaps in one geographic location or for new customers).

Conduct experiments and measure the impact on segments

A culture and mindset of experimentation will leave you in the best possible position to deliver value to your customers on a consistent basis.

There’s no limit to what you can test: different versions of product experiences, marketing campaigns, in-app notifications, and more.

You want to understand how certain segments will respond, figure out what’s working and what isn’t, and apply what you’ve learned from one specific target segment to the next.

How to use segmentation to optimize customer experiences?

We’ve explained what segmentation is, the various types of segmentation you might want to use, and how to conduct segmentation within your product.

But the most important aspect? Putting what you learn into practice.

Let’s unpack how you can use segmentation to improve the customer experience.

Create a personalized onboarding process for different segments

Onboarding is critical for helping users unlock value from your app quickly.

You can personalize the experience using data you’ve gathered from welcome surveys. You can then tweak what distinct segments see or do based on their needs.

A great example of that is Canva’s onboarding: it’ll ask what you’re using Canva for (teacher, student, personal) and recommend appropriate, relevant templates to help users off to a fast start.

Trigger personalized messaging to improve user engagement

Segmentation gives you enough knowledge of different user groups to trigger personalized messaging at key points in their respective journeys. You can create content (i.e., relevant offers, helpful tooltips, and prompts) that will appeal to different chunks of your customer base at the right points in the journey.

For example, a group of users might have expressed an interest in a new feature. You can trigger an engaging message to let them know once it’s launched.

Target customers likely to churn to retain them

If you can’t keep hold of your customers, your whole business model is at risk.

To boost customer retention, first, you need to identify inactive users (segmentation helps with that). You can then reach out to your users via in-app surveys or messages to help diagnose their issues, generate ideas for solutions, and ultimately increase your chances of retaining them.

Identify power users for beta testing

Segmentation can also help you build better products by figuring out who your power users are and then leveraging their expertise.

Simply create a segment of your most active users, and offer incentives to recruit them for beta testing. Because they use your product so much, they’ll be in the best possible position to provide pragmatic, actionable feedback that can help improve the product.

Conclusion

Hopefully, you now have a solid understanding of the different types of user segmentation to choose from, how to deploy them in your own SaaS, and most importantly, how to use the insights to optimize the user experience.

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