10 Customer Segmentation Strategies for SaaS in 2026

Are you grouping all your customers together? If you are, you might be missing key opportunities to keep them happy and grow your revenue. Knowing your customers, who they are, what they need, and how they use your product, is the foundation of a successful SaaS business. But a single, broad view isn't enough. Different customer groups have different motivations and face unique challenges. This is where smart segmentation comes in.

By dividing your user base into smaller, more specific groups, you can personalize your communication, support, and product experience. For example, a power user with high engagement needs different messaging than a new trial user who is still exploring basic features. Treating them the same means you connect with neither. Effective customer segmentation strategies allow you to move beyond generic outreach and build relationships that drive retention and expansion. This approach helps product teams prioritize features, marketing teams craft relevant campaigns, and customer success teams provide proactive support.

This guide will walk you through 10 distinct customer segmentation strategies that you can apply to your SaaS business today. We will explore each method in detail, covering everything from behavioral and firmographic to needs-based and psychographic models. For each strategy, you will find clear definitions, benefits, real-world examples, and specific steps to put them into action using feedback tools like Surva.ai to get a clearer picture of your users. You will learn how to identify your most valuable customer groups and tailor your efforts to meet their specific needs.

1. Behavioral & Engagement-Level Segmentation

Behavioral segmentation moves beyond who your customers are to focus on what they do. This powerful customer segmentation strategy groups users based on their actions, usage patterns, and in-product interactions. When combined with engagement-level data (the frequency and intensity of those actions), SaaS companies gain a clear picture of how customers derive value from their product.

This unified approach allows you to identify distinct groups like power users, at-risk customers showing early signs of churn, and accounts ripe for expansion. By analyzing actions, you can stop guessing and start making data-driven decisions that directly impact retention and growth.

Why This Strategy Works

This method is highly effective because it’s based on actual product usage, which is a strong indicator of customer health and intent. A user who logs in daily and utilizes multiple features has different needs and a different relationship with your brand than someone who hasn't logged in for 30 days.

Key Insight: Actions speak louder than demographics. How a customer uses your product reveals more about their needs and potential future behavior than their job title or company size.

Implementation Examples:

• Churn Prevention: Isolate users who haven’t logged in for 30+ days or whose feature usage has suddenly dropped. Automatically trigger a Surva.ai re-engagement survey to ask what’s holding them back.
• Expansion Identification: Segment highly engaged accounts, for example, those using five or more features with multiple active team members. Mark these accounts as "expansion-ready" and have your customer success team reach out to discuss upgrades.
• Adoption Campaigns: Identify "power users" who are daily active users of core features. Target them with campaigns to introduce advanced features, turning them into your biggest advocates.

Actionable Tips for Implementation:

• Define Engagement Tiers: Create specific definitions for your product, such as "High Engagement" (daily login, uses 3+ core features) vs. "Low Engagement" (monthly login, uses 1 feature).
• Combine Data with Feedback: Use your behavioral data to identify a segment (e.g., low-engagement users) and then deploy a Surva.ai survey to ask why they exhibit that behavior. This gives you qualitative context. You can get more insights from our guide on how to measure customer engagement.
• Track Feature-Specific Usage: Monitor which features correlate most strongly with long-term retention. This helps you guide new users toward those "sticky" features during onboarding.
• Personalize Outreach: Change your survey questions and offers based on engagement segments. A power user should receive a different message than an inactive one.

2. Firmographic Segmentation

Firmographic segmentation is the B2B equivalent of demographic segmentation, grouping business customers by shared company-level attributes. This approach categorizes accounts based on characteristics like industry, company size, annual revenue, geographic location, and even technological stack. It is one of the foundational customer segmentation strategies for B2B SaaS.

This method allows SaaS teams to move beyond one-size-fits-all messaging and create specific experiences for different business profiles. Whether targeting a small startup or a global enterprise, firmographics provide the context needed to align your product, sales, and support strategies with the specific needs of each business segment.

Why This Strategy Works

This strategy is effective because a company's characteristics directly influence its purchasing decisions, pain points, budget, and compliance needs. An enterprise with over 500 employees has fundamentally different operational challenges and procurement processes than a 10-person startup, and your approach must reflect that reality.

Key Insight: The business you sell to is as important as the user you serve. Firmographics provide the blueprint for knowing an organization's context, priorities, and potential value as a customer.

Implementation Examples:

• Custom Onboarding: Segment customers in the healthcare vertical and provide them with HIPAA-specific compliance documentation during onboarding, while financial services clients receive materials focused on SOC 2.
• Tiered Service Models: Assign dedicated account managers and offer premium support to your enterprise segment (e.g., companies with 500+ employees), while guiding smaller businesses to a self-service support model.
• Targeted Marketing: Create advertising campaigns and content specifically for the "manufacturing" industry segment, addressing common operational pain points that your software solves for that vertical.

Actionable Tips for Implementation:

• Enrich Your Data: Integrate your CRM with data enrichment tools like ZoomInfo or Apollo.io to automatically append firmographic data to new leads and existing customer profiles.
• Segment for Subscription Tiers: Use company size and revenue data to create segments that align with your pricing plans. Present targeted upgrade offers or plan recommendations in-app or via email.
• Create Industry-Specific Surveys: Develop Surva.ai survey templates that address vertical-specific challenges. Ask manufacturing clients about supply chain issues and tech startups about scalability problems.
• Pair with Behavioral Data: Combine firmographics with behavioral segmentation. This helps you identify high-value accounts (e.g., enterprise clients in the finance sector) that are showing early signs of churn risk based on low product usage.

3. RFM (Recency, Frequency, Monetary) Segmentation

RFM analysis is a quantitative method that segments customers based on three precise dimensions of their transaction history: Recency (how recently they purchased or engaged), Frequency (how often they do so), and Monetary value (how much they spend). Originating in direct mail marketing, this model has been adapted for SaaS to evaluate customer value and predict future behavior with remarkable accuracy.

It allows you to pinpoint your most valuable customers (your champions), identify promising mid-tier users, and spot at-risk accounts before they churn. By scoring customers on these three metrics, you can create highly targeted customer segmentation strategies that speak directly to their current relationship with your product.

Why This Strategy Works

RFM works because past transactional behavior is a strong predictor of future actions. A customer who recently signed up for a high-tier plan and logs in frequently is fundamentally different from one whose annual subscription is lapsing and hasn't engaged in months. RFM provides a simple yet powerful framework to classify and prioritize these distinct groups for maximum impact.

Key Insight: Not all customers are created equal. RFM helps you identify your best customers so you can learn from them and apply those insights to nurture others into becoming high-value champions.

Implementation Examples:

• Reward Champions: Segment customers with high scores across all three RFM categories. Target these "champions" with exclusive access to beta features or invite them to provide testimonials for case studies.
• Prevent Churn: Identify customers with low recency but previously high frequency and monetary scores. Automatically send them a re-engagement survey via Surva.ai to find out what's changed and offer assistance.
• Drive Upsells: Group mid-tier customers who are frequent users but on lower-value plans. Launch targeted campaigns showcasing the benefits of an upgrade, moving them into a higher monetary segment.
• Win-Back Lost Customers: Create a segment for "lost" customers with low RFM scores across the board. Use Surva.ai's cancellation flows to present them with a special win-back offer to reignite the relationship.

Actionable Tips for Implementation:

• Define Your Thresholds: Set RFM score thresholds that make sense for your SaaS model. For example, "high recency" might be a daily login for a B2C app but a monthly login for a B2B platform.
• Automate Survey Triggers: Use RFM segments to trigger different survey question sets in Surva.ai. A high-value customer might be asked about new feature ideas, while an at-risk user is asked about their challenges.
• Recalculate Scores Regularly: Customer behavior changes. Recalculate RFM scores on a consistent basis, like monthly or quarterly, to make sure your segments remain accurate and your outreach stays relevant.
• Prioritize Retention Efforts: Use the monetary value score to determine where to invest your retention budget. A high-monetary, at-risk customer warrants more immediate and personalized attention than a low-monetary, at-risk one.

4. Psychographic Segmentation

Psychographic segmentation moves beyond demographics and firmographics to group customers based on their psychological attributes. This customer segmentation strategy focuses on why customers make decisions by analyzing their values, beliefs, aspirations, lifestyles, and pain points. For SaaS companies, this provides important context that transactional data alone cannot offer.

This approach helps you find the motivations driving purchasing and product usage. By uncovering these deeper drivers, you can craft messaging, features, and experiences that resonate on an emotional level, building stronger brand loyalty and driving more targeted marketing campaigns.

Why This Strategy Works

This method is effective because it uncovers the "why" behind customer behavior. Two companies of the same size and industry (firmographics) might buy your software for completely different reasons. One may be driven by a need for cutting-edge innovation, while the other is primarily focused on security and compliance. Knowing these motivations allows for far more persuasive and relevant communication.

Key Insight: Customer motivations are as important as their actions. Finding a customer's core values and pain points lets you position your product as the ideal solution to their specific worldview.

Implementation Examples:

• Security-Conscious Enterprises: Segment organizations that list "data security" and "compliance" as top priorities in onboarding surveys. Target them with content about your security certifications, data encryption, and access controls.
• Innovation-Seeking Startups: Identify users who describe themselves as "early adopters" or value "cutting-edge technology." Offer them access to beta features and frame your product as a competitive advantage.
• Cost-Conscious SMBs: Group customers who express concerns about budget and ROI. Target them with case studies highlighting efficiency gains and send Surva.ai retention surveys focused on the financial value your product delivers.

Actionable Tips for Implementation:

• Ask About Priorities: Use Surva.ai post-purchase surveys to ask new customers to rank their priorities, such as speed, cost, innovation, or support.
• Analyze Churn Reasons: Include psychographic questions in churn surveys to see if a misalignment of values (e.g., they needed more simplicity, your product became more complex) caused cancellation.
• Build Richer Personas: Combine psychographic insights with firmographic and behavioral data to create detailed buyer personas that guide marketing and product development.
• Test Value Propositions: Deploy a Surva.ai survey to test different value propositions (e.g., "Save Time" vs. "Stay Ahead of the Curve") to see which resonates most strongly with different segments.

5. Needs-Based Segmentation

Needs-based segmentation groups customers according to their specific goals, challenges, and desired outcomes. This strategy moves past demographic or behavioral data to focus on the fundamental problem each customer is trying to solve with your product. It answers the question, "What job did this customer hire our product to do?"

This approach, popularized by the "Jobs to be Done" framework, enables highly relevant product positioning, onboarding, and feature development. By seeing the core need, you can change the entire customer experience to solve that specific problem, dramatically increasing perceived value and user satisfaction.

Why This Strategy Works

This method is powerful because it aligns your product directly with the customer's motivation. A global enterprise team needing multi-language support and compliance features has a completely different set of needs than a startup that prioritizes simplicity and a low price point. Addressing these distinct needs makes your solution feel custom-built for them.

Key Insight: Customers don't buy products; they buy solutions to their problems. Segmenting by the problem you solve for them is one of the most direct paths to product-market fit and customer loyalty.

Implementation Examples:

• Targeted Onboarding: Segment users who indicate their primary need is "improving team collaboration." Create a specialized onboarding flow that immediately introduces them to shared workspaces, commenting, and task assignment features.
• Feature Development: Discover that a large segment of e-commerce customers needs advanced inventory integration. Prioritize building this feature on your roadmap because you have data showing a clear, unmet need.
• Marketing Messaging: Create separate landing pages and ad campaigns for different needs. One campaign could target marketing teams by highlighting analytics and reporting, while another targets regulated industries by emphasizing security and audit trails.

Actionable Tips for Implementation:

• Ask Directly During Sign-up: Use a Surva.ai survey during the onboarding process to ask, "What is the main problem you are trying to solve with our product today?"
• Map Needs to Features: Create an internal matrix that clearly connects each primary customer need to the specific product features that solve it. This becomes a guide for your customer success and sales teams.
• Tailor Churn Surveys: When a customer cancels, use a needs-based segment to ask targeted questions. For example, "Did our reporting features fail to meet your marketing analytics needs?"
• Monitor for Evolving Needs: Continuously survey your segments to see if their primary needs are changing over time. A startup's need for simplicity might evolve into a scale-up's need for advanced integrations.

6. Lifecycle Stage Segmentation

Lifecycle stage segmentation is a time-sensitive approach that divides customers based on where they currently are in their journey with your product. This strategy recognizes that a customer's needs, questions, and goals change dramatically from their first day as a trial user to their first anniversary as a loyal advocate. It allows you to deliver the right message and support at precisely the right moment.

By mapping out key phases like onboarding, adoption, expansion, and potential churn, you can create a proactive engagement model. This is one of the most effective customer segmentation strategies because it moves you from a reactive support posture to a predictive, guidance-oriented relationship with your users, directly impacting their success and your retention rates.

Why This Strategy Works

This method is powerful because it is inherently contextual. It acknowledges that a brand-new user needs quick wins and foundational guidance, while a veteran user is looking for advanced value and efficiency gains. Communicating with customers based on their current stage prevents sending irrelevant messages, like pitching an upgrade to someone who hasn't even completed onboarding.

Key Insight: The most valuable customer interaction is one that meets them exactly where they are. Lifecycle segmentation makes this relevance possible at scale.

Implementation Examples:

• Onboarding Success: Segment "Trial Users" and automatically send them a Surva.ai survey after 3 days asking about their primary goal, making sure they are on the path to their first "aha!" moment.
• Renewal Confirmation: Create a segment for customers whose renewal is in 30 days. Trigger a survey to gauge their renewal likelihood and uncover any last-minute friction points that could cause churn.
• Expansion Opportunities: Identify customers in the "Established" stage (e.g., active for 6+ months with high engagement). Target them with information about premium features that solve their next-level problems.
• Churn Deflection: A cancellation request automatically moves a user into an "At-Risk" segment. Instantly trigger a Surva.ai survey to find out their reasons and present an automated, relevant offer to stay.

Actionable Tips for Implementation:

• Define Clear Stage Gates: Establish specific criteria for moving from one stage to the next. This could be time-based (e.g., 90 days active), usage-based (e.g., invited 5 teammates), or a combination of both.
• Automate Stage Transitions: Use events within your product or CRM to trigger a stage change. For example, a "Subscription Upgraded" event moves a user from the "Active" to "Expansion" segment.
• Tailor Survey Length and Tone: A trial user should receive a quick, two-question pulse check. An at-risk user should get a more in-depth survey to capture the full context of their dissatisfaction.
• Map Product Milestones: Connect key product adoption milestones to your lifecycle progression. Reaching a milestone, like creating 10 projects, could be a trigger to move a user from "Onboarding" to "Adoption."

7. Value-Based Segmentation

Value-based segmentation categorizes customers by the economic value they generate for your business, both currently and in the future. This strategic approach groups accounts based on metrics like annual recurring revenue (ARR), customer lifetime value (LTV), and expansion potential. It allows SaaS companies to allocate resources more effectively, prioritizing high-value relationships.

This method helps you move from treating all customers equally to providing a tiered experience that reflects their contribution to your bottom line. By identifying your most profitable segments, you can focus retention efforts where they will have the greatest financial impact and change growth strategies to accounts with the highest upside.

Why This Strategy Works

This strategy is effective because it directly ties customer segmentation to financial outcomes. It acknowledges that not all revenue is equal; losing a $100K ARR enterprise client is far more damaging than losing a $50/month SMB account. It forces a disciplined approach to resource allocation for customer success, support, and marketing.

Key Insight: Your most valuable customers are not just your biggest spenders today; they are the accounts with the highest potential for long-term, profitable growth. Focusing on their needs protects your core revenue and fuels sustainable expansion.

Implementation Examples:

• Tiered Support Model: Assign dedicated account managers to enterprise customers (worth $100K+ ARR), while providing automated, self-serve support resources for your low-value SMB segment.
• Prioritized Onboarding: A high-potential startup with a strong growth curve receives a white-glove onboarding experience to maximize their success and future spending, even if their current ARR is small.
• Strategic Business Reviews: Mid-market accounts ($10K-50K ARR) receive quarterly business reviews with a customer success manager to identify expansion opportunities and solidify the partnership.

Actionable Tips for Implementation:

• Calculate LTV per Segment: Go beyond current ARR. Calculate the projected lifetime value for each segment to find its true long-term worth.
• Survey for Expansion Clues: Use Surva.ai to survey your high-value customers about their satisfaction and future business goals. This can reveal unmet needs and prime them for upsells.
• Monitor Churn by Value: Track your churn rate for each value segment. High churn in your top tier is a critical red flag that requires immediate investigation with targeted churn surveys.
• Personalize Growth Offers: Create expansion offers specifically for mid-value customers showing signs of growth. For more ideas, check out our guide on how to increase customer lifetime value.

8. Geographic Segmentation

Geographic segmentation groups customers based on their physical location, such as country, region, city, or even timezone. For SaaS companies with a global user base, this is a foundational strategy for providing relevant, compliant, and localized customer experiences. It influences everything from support hours and pricing to marketing messaging and product features.

This approach helps businesses navigate the different aspects of international markets. By knowing where customers are, you can change your operations to meet local expectations, adhere to regional regulations, and communicate in a way that resonates culturally, building trust and reducing friction.

Why This Strategy Works

This method is effective because location directly impacts a customer's needs and legal requirements. A user in the EU has different data privacy expectations (GDPR) than a user in North America, while a customer in the APAC region will require support at a completely different time of day. Ignoring these geographical differences can lead to poor user experience, compliance issues, and missed growth opportunities.

Key Insight: Where a customer is located dictates their regulatory environment, cultural context, and practical needs. Changing your approach to geography shows you know and respect their local context.

Implementation Examples:

• Compliance and Data Residency: Create a segment for EU-based customers to make sure all data handling and privacy communications are GDPR-compliant. Similarly, you might create a separate instance for Chinese customers to meet local data residency laws.
• Localized Support: Segment users in the APAC region to provide dedicated customer support during their business hours (e.g., 9am-5pm SGT). This prevents customers from waiting overnight for help.
• Regional Payment and Language: Target a Latin American segment with Spanish-language onboarding materials and surveys. Offer local payment methods that are popular in the region to increase conversion rates.

Actionable Tips for Implementation:

• Localize Your Surveys: Use Surva.ai’s language localization features to send surveys to non-English speaking segments in their native language, significantly improving response rates.
• Adjust Communication Timing: Schedule email campaigns, feature announcements, and survey invitations to be sent during normal business hours for each major geographic timezone you serve.
• Create Region-Specific Templates: Develop customer communication and survey templates that address local holidays, cultural norms, and specific compliance concerns relevant to that area.
• Monitor Regional Trends: Analyze customer satisfaction, feature adoption, and churn rates by geography. This can reveal region-specific pain points or opportunities that require a targeted response.

9. Satisfaction and NPS-Based Segmentation

This segmentation strategy groups customers based on their expressed happiness with your product, most often measured through feedback mechanisms like the Net Promoter Score (NPS). By categorizing users into Promoters, Passives, and Detractors, you can transform direct feedback into a proactive system for retention, advocacy, and product improvement. It allows you to prioritize outreach where it matters most.

This approach gives you a direct line into customer sentiment, helping you see the "why" behind their behavior. Instead of just seeing that a user is inactive, you learn if their inactivity stems from dissatisfaction, a missing feature, or a poor support experience, allowing for a much more targeted response.

Why This Strategy Works

Satisfaction-based segmentation is effective because it relies on the customer's own voice. It provides a clear, quantifiable measure of loyalty and flags potential churn risks before they show up in usage data. A Detractor is an immediate churn risk, while a Promoter is a potential case study, giving you clear next steps for each group.

Key Insight: Customer feedback is not just a grade; it's a guide. Each NPS response provides a clear signal that can direct your customer success, marketing, and product development efforts with precision.

Implementation Examples:

• Prioritize At-Risk Accounts: Automatically flag all Detractors (NPS 0-6) for immediate follow-up by your customer success team. Trigger a Surva.ai survey to ask for specific reasons behind their low score.
• Activate Brand Advocates: Segment your Promoters (NPS 9-10) and invite them to join a beta testing program, write a review, or participate in a case study.
• Nurture the Undecided: Target Passives (NPS 7-8) with campaigns showcasing new features or offering additional training to convert them into enthusiastic Promoters.

Actionable Tips for Implementation:

• Ask "Why" Immediately: After a user submits an NPS score, immediately trigger a follow-up, open-ended Surva.ai survey asking for the reason behind their rating.
• Track NPS Trends: Monitor how NPS scores change over time for different segments (e.g., by plan type or user persona). A declining trend is a powerful early warning sign of future churn.
• Create Feedback Loops: Share insights from Detractor feedback directly with your product and support teams during monthly meetings to address root causes of dissatisfaction.
• Pair with Behavioral Data: Combine NPS scores with usage data. This helps you determine if low satisfaction is related to a lack of product engagement or a specific support issue. You can learn more about how to group customers from our guide about NPS Promoters and Detractors.

10. Account-Based Marketing (ABM) Segmentation

Account-Based Marketing (ABM) segmentation flips the traditional marketing funnel on its head. Instead of casting a wide net to capture individual leads, this strategy treats high-value accounts as individual markets. It involves identifying key target accounts and creating highly personalized campaigns that engage multiple stakeholders within those organizations.

This approach aligns sales, marketing, and customer success teams around a shared goal: winning and growing specific, high-potential accounts. It is one of the most resource-intensive but effective customer segmentation strategies for B2B SaaS companies focused on enterprise-level clients.

Why This Strategy Works

ABM is effective because it concentrates resources on the accounts that have the highest revenue potential. By personalizing the experience for the entire buying committee, from the CTO to the CFO, you address specific pain points and demonstrate a deep familiarity with their business challenges, which greatly increases conversion and retention rates.

Key Insight: In enterprise sales, you aren't selling to a person; you're selling to an organization. ABM recognizes this by creating a coordinated, account-wide experience that speaks to every key decision-maker.

Implementation Examples:

• Targeted Onboarding: For your top 50 enterprise accounts, create a custom onboarding flow with dedicated support specialists and documentation changed to their specific industry and use case.
• Account Playbooks: Develop strategic playbooks for each key account that outline their business challenges, key stakeholders, and personalized messaging, making sure every team member is aligned.
• Buying Committee Surveys: Deploy tailored Surva.ai surveys to different roles within a target account. Ask the CFO about ROI, the CTO about integration capabilities, and the end-users about feature needs.
• Custom Retention Plans: For strategic accounts, build proactive retention plans that include specific expansion milestones, exclusive feature previews, and personalized offers to drive long-term growth.

Actionable Tips for Implementation:

• Map the Buying Committee: Use your CRM to identify and map all key stakeholders within your target accounts. Create separate contact lists for each role to facilitate personalized outreach.
• Create Role-Specific Surveys: Use Surva.ai to design surveys that address the unique priorities of each stakeholder. A CFO's feedback on budget will be different from a Head of IT's feedback on security.
• Inform QBRs with Feedback: Collect account-specific feedback through surveys before a Quarterly Business Review (QBR) to guide the conversation and demonstrate your commitment to their success.
• Document Account Strategy: Maintain a centralized document for each target account that outlines the strategy, key contacts, recent feedback, and next steps. Share this across sales, customer success, and support teams.

10-Point Customer Segmentation Comparison

Putting Your Segmentation Plan into Action

You have now explored ten powerful customer segmentation strategies, from the data-driven precision of RFM analysis to the human-centric insights of psychographic and needs-based models. We've seen how behavioral segmentation can spotlight user engagement patterns, while firmographic data provides a clear picture of your ideal business customer. Each model offers a distinct lens through which to view your customer base.

The true breakthrough, however, comes when you stop viewing these strategies as isolated options. The goal is not to pick one perfect model but to layer them, creating a rich, multi-dimensional profile of your users. This is where abstract data points transform into actionable intelligence.

Consider the practical implications. An enterprise client (Firmographic) with high lifetime value (Value-Based) but recent low product usage (Behavioral) is a clear churn risk. This combination of segments flags an account that needs immediate, high-touch intervention from your customer success team. On the other hand, a user from an SMB (Firmographic) who recently upgraded their plan (Behavioral) and gave you a Net Promoter Score of 10 (Satisfaction-Based) is a prime candidate for a case study or a referral program. Without combining these models, you would miss the full context behind their actions.

From Theory to Tangible Results

Moving from knowing these strategies to implementing them requires a clear plan. Avoid the common pitfall of trying to implement all ten at once. This approach often leads to analysis paralysis and diluted efforts. Instead, start with a focused objective.

• If your goal is to reduce churn: Begin by combining Behavioral, Satisfaction (NPS), and Lifecycle Stage segmentation. This will help you identify at-risk users, find out their frustrations, and intervene at the most critical moments.
• If you want to increase expansion revenue: Focus on Value-Based, RFM, and Needs-Based segmentation. This combination reveals your most valuable customers, identifies who is ready to buy more, and clarifies what specific problems they are trying to solve next.
• If you are launching a new feature: Use Behavioral and Psychographic segmentation. This helps you target a beta group of power users who are most likely to provide insightful feedback based on their habits and motivations.

The Power of Asking "Why"

Quantitative data from your CRM or product analytics tells you what your customers are doing. You can see who logs in, which features they use, and when they last made a purchase. This is the foundation of effective customer segmentation. But it is only half the story.

To build truly effective strategies, you must also find out why they are doing it. Why did a seemingly happy customer suddenly stop using a key feature? What unmet need prompted a user to seek out a new solution? This is where qualitative feedback becomes indispensable.

Platforms like Surva.ai are built to bridge this gap. By deploying targeted, in-app surveys to specific segments, you can collect the qualitative context needed to enrich your quantitative data. Ask your low-engagement enterprise users what is holding them back. Ask your high-NPS SMB users what they love most about your platform. The answers will transform your segments from simple groups into living, breathing customer personas you can build for, market to, and support with precision. By systematically combining robust data analysis with direct user feedback, you move beyond just grouping customers to genuinely knowing them.

Ready to uncover the "why" behind your user behavior? Start building a deeper, more actionable understanding of your customers by gathering targeted feedback. Use Surva.ai to deploy in-app surveys to your newly defined segments and turn insights into growth. Get started with Surva.ai today.