8 Essential Customer Segmentation Models for SaaS.

Every successful product-led growth plan is built on data. While mind-reading is out of reach, customer segmentation models are the next best thing. These frameworks allow you to move beyond a ‘one-size-fits-all’ approach by grouping users into actionable categories based on how they actually use your product.

In this guide, we’ll break down the 8 essential models you need to master to stop guessing and start delivering the personalized experiences your customers expect.

TL;DR

• Customer segmentation models are ways of dividing customers into groups with shared traits to effectively tailor your product and marketing efforts. While a customer segmentation strategy defines your high-level business goals, a model provides the specific framework to reach them.
• Here are some benefits of user segmentation models:

1. Tailoring in-app content and features enhances engagement through personalized experiences.
2. Targeted marketing based on customer segments improves campaign effectiveness and conversion rates by addressing specific needs and preferences.
3. Behavioral segmentation identifies upselling opportunities by tailoring offers to users’ needs and usage patterns.
4. Personalized interactions based on customer segments enhance satisfaction, build customer loyalty, and encourage brand advocacy.

• There are eight different customer segmentation models:

1. Behavioral segmentation groups users by in-app interactions and usage patterns.
2. Psychographic segmentation categorizes users by psychological traits.
3. Demographic segmentation groups users by factors like age, gender, or income.
4. Geographic segmentation groups users by location.
5. Technographic segmentation categorizes users by the technology they use.
6. Firmographic segmentation categorizes customers by company-specific characteristics.
7. Value-based segmentation groups users by their economic value for the company.
8. Needs-based segmentation categorizes users by specific needs, preferences, or pain points.

• Here are three customer segmentation tools to help you improve the customer journey:

1. Userpilot enables personalized in-app experiences by tailoring user journeys to different segments, driving product growth.
2. HubSpot facilitates customer segmentation for personalized email campaigns, allowing targeted communications based on behavior, demographics, and content interactions.
3. Sprout Social enhances social media marketing by enabling targeting for different audience segments.

To learn how to turn these models into a plan of action, follow our 6-step guide to building a customer segmentation strategy.

If you need help creating customer segmentation models, Userpilot can help. It can automatically track user behavior, analyze customer data to create new segments, and implement A/B testing to see the most effective approaches for each segment. To learn more, book a demo now.

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What is a customer segmentation model?

A customer segmentation model is a categorical framework that divides your user base into distinct groups based on shared characteristics.

It is important to distinguish the model from the strategy:

• The strategy: The high-level plan and business goals (e.g., “We want to reduce churn by 10%”).
• The model: The specific lens through which you view your data to achieve that goal (e.g., “Using a Behavioral Model to identify inactive users”).

By selecting the right model, you can ensure your product and marketing efforts are tailored to the specific needs of each user cohort.

Benefits of customer segmentation models

Here are some benefits you can gain from using customer segmentation models to organize your user data.

1. Personalized in-app experiences

By identifying distinct segments within your user base using specific models, you can tailor in-app content and experiences to meet each group’s preferences. This level of personalization enhances user engagement and customer satisfaction, increasing the likelihood of user retention.

For example, segmenting users of a project management tool based on their roles allows the app to present relevant features tailored to each framework. Project managers might see detailed task overviews and team performance analytics. Meanwhile, team members could receive simplified task lists and collaboration tools.

2. Precision in targeting

Understanding the characteristics of each customer segmentation model allows you to create highly relevant interactions that resonate with your users. Tailoring your messaging to align with these specific data frameworks can significantly improve conversion rates.

Suppose you’ve recently rolled out a new feature, and you notice a segment of users who frequently engage with similar existing features but haven’t yet tried the new one. You can use a behavioral model to create a targeted campaign for this group, showing how the new feature adds value to their specific workflow.

3. Upselling opportunities

Selecting models that track usage limits allows you to identify clear opportunities for upselling.

For instance, let’s say you’ve identified a segment of customers who have reached a limit of 15 created reports in your app. These users are highly engaged but may be approaching a point where they need a higher-tier plan. By using a value-based or behavioral model, you can trigger personalized in-app ads or emails that encourage them to upgrade at the right moment.

4. Improved customer loyalty and overall satisfaction

When you utilize specific models to tailor your interactions with personalized messaging, users feel more valued and understood. This structured approach to data boosts satisfaction and turns users into loyal customers.

Core data inputs for customer segmentation models

Here are different ways of segmenting customers:

Behavioral segmentation

Behavioral segmentation is a customer segmentation model input that groups users based on their behaviors, interactions, and usage patterns.

Best for: Identifying active vs. inactive users and driving feature adoption.

Strategic use case: Triggering a re-engagement email to a segment of users who haven’t logged in for 7 days.

For example, a SaaS might segment customers based on actions such as the frequency of logins or features used. This segmentation allows you to identify active and inactive users. Then, you can create strategies to re-engage inactive users and target active users with personalized content based on what they engage with.

Psychographic segmentation

Psychographic segmentation is a customer segmentation model that categorizes users based on their psychological characteristics, such as their values, attitudes, or interests.

Best for: Personalizing brand messaging and tone of voice.

Strategic use case: Customizing onboarding copy based on whether a user’s motivation is “personal productivity” or “team collaboration.

Segmenting customers based on psychographic data, such as whether they identify as extroverts or introverts, can lead to more personalized and effective marketing strategies. For example, for extroverted users, you could highlight features that encourage social interaction.

Demographic segmentation

This is a customer segmentation model that groups users based on age, gender, occupation, or income.

Best for: B2C products and high-level market positioning.

Strategic use case: Recommending different content tiers based on a user’s reported job title or income level.

For example, a streaming service might segment its users by age, offering different content recommendations. Teenagers might be shown the latest trending shows, while older viewers could receive recommendations for classic films.

Geographic segmentation

Geographic segmentation is a customer segmentation model that groups users based on their physical location, such as country, region, city, or even climate.

Best for: Localizing currency, language, and regional compliance.

Strategic use case: Displaying GDPR-compliant privacy banners only to users located within the European Union.

For example, an e-commerce company selling outdoor gear could segment its customers based on climate. It could promote winter gear to users in colder regions and summer equipment to those in warmer climates.

Technographic segmentation

Technographic segmentation is a customer segmentation model that categorizes users based on their technology, such as the device, browser, or operating system.

Best for: Optimizing UI/UX and prioritizing product integrations.

Strategic use case: Identifying a segment of users on a specific browser to troubleshoot a reported display bug.

For example, segmenting users based on their device type (desktop or mobile) allows you to create targeted ads that emphasize features specific to each device.

Firmographic segmentation

This is a customer segmentation model primarily used in B2B contexts, where businesses divide companies into groups based on company industry, number of employees, revenue, etc.

Best for: B2B Sales, Account Based Marketing (ABM), and tiered support.

Strategic use case: Assigning a dedicated account manager to segments with over 500 employees.

For example, a SaaS provider might segment its customers based on company size—small businesses, mid-sized companies, and large corporations. Small businesses might be offered cost-effective, scalable solutions, while large corporations are targeted with enterprise-level features.

Value-based segmentation

Value-based segmentation is a customer segmentation model that groups users based on the economic value they bring to a business.

Best for: Maximizing Customer Lifetime Value (LTV) and ROI.

Strategic use case: Inviting your “Top 10%” highest-paying customers to a VIP beta-testing group for new features.

For example, you can create a segment of users on an enterprise plan and target them with exclusive offers, early access to new features, and personalized account management services to enhance their loyalty.

Needs-based segmentation

Needs-based segmentation is a customer segmentation model that categorizes users based on their specific needs, preferences, or pain points.

Best for: Product-led growth and solving specific user problems.

Strategic use case: Triggering a specific “how-to” guide for users who have created an invoice but haven’t yet sent it.

For example, you may segment users who have created an invoice and then offer them tailored features such as advanced invoicing and personalized support to improve their billing process.

How to implement customer segmentation models using Userpilot

Once you’ve selected a model, implementation involves mapping your user data to these frameworks. While our customer segmentation strategy guide explains the high-level planning, implementing the models requires setting up the right tracking events and user properties within your product growth platform

Set goals and KPIs for your strategy

Goal setting provides direction and purpose, and KPIs give measurable progress indicators. Some examples of goals could be increasing engagement with a particular feature or improving conversion rates.

KPIs you can measure include segment-specific conversion rate, product engagement score (PES), etc.

1. Define your user properties and events

To build a model, you first need the right data points. Use Userpilot to track specific user properties (like industry for firmographic models) or custom events (like ‘feature used’ for behavioral models). This ensures your models are fueled by real-time data.

2. Create segments based on your chosen model

Once your data is flowing, use the segment builder to group users. You can add multiple attributes to refine your model. For example, a ‘Power user’ behavioral model might include users who have logged in more than 15 times in the last 30 days and completed at least one core event.

3. Analyze segment behavior and trends

After creating your segments, use analytics to see how each group interacts with your product. Trend analysis allows you to see if your models are accurate, for example, checking if your “High-value” segment is actually engaging with your premium features.

4. Trigger personalized flows for each model

The final step in implementing your model is taking action. Based on the data, you can trigger specific in-app experiences. For a needs-based model, you might trigger a specific onboarding flow that addresses the unique pain point that user identified during their first session.

5. Refine your models based on performance

Models aren’t static. As your product evolves, you should analyze how your segments respond to different tactics and refine the criteria for your models to ensure they remain accurate and effective for your current user base.

Customer segmentation tools you can use to improve the user journey

Here are three of the best customer segmentation tools to help you streamline the implementation of your models.

Userpilot

Best for: real-time behavioral and technographic model implementation

Userpilot is a product growth tool that can help you create personalized in-app experiences through effective customer segmentation. Here’s what you can do with it:

• Add properties and conditions to create advanced segments.
• Analyze the behavior of each segment with analytics reports and dashboards.
• Auto-capture clicks, text inputs, and form submissions of different segments.
• Launch surveys tailored to each segment.
• Create custom flows for different segments.
• Do A/B testing to understand how different segments respond to the same flow.

HubSpot:

Best for: creating personalized email campaigns

HubSpot can help you launch personalized email marketing campaigns. With HubSpot, you can segment your audience based on various criteria, such as lifecycle stage, demographics, and interactions with your content.

By integrating HubSpot with Userpilot, you can leverage the customer segments you’ve already defined in Userpilot to send even more targeted emails. This integration allows you to align your in-app experiences with your email marketing efforts. Pretty neat, huh?

Sprout Social:

Best for: creating personalized social media marketing campaigns

Sprout Social can help you improve your Facebook and LinkedIn strategy with its Audience Targeting feature. On Facebook, you can target the posts based on the audience’s interests, gender, age, location, relationship status, etc.

On LinkedIn, Sprout Social allows you to segment the audience based on company size, industry, function, seniority, etc.

Conclusion

Hopefully, you now know how different customer segmentation models can improve your product and marketing efforts.

Getting started with customer segmentation models can’t be any easier. Userpilot lets you create segments based on in-app behavior and surveys, automatically capture their behavior, and launch personalized product experiences. Book a demo now to learn more.

Try Userpilot and Take Your Personalized Product Experiences to the Next Level

Get a Demo

• 14 Day Trial
• No Credit Card Required