How to Run a Gabor-Granger or Van Westendorp Pricing Test for Your SaaS

Discover evidence-based pricing methods that eliminate guesswork and maximize revenue potential for your SaaS business.

Introduction: Why Gut-Feel Pricing Is Costing Your SaaS Money

Setting prices based on intuition is one of the costliest mistakes SaaS founders make. While competitor analysis and cost-plus pricing provide starting points, they ignore the most critical factor: what customers are actually willing to pay.

Consider this scenario: You launch your project management SaaS at $49/month because it feels reasonable compared to competitors at $39 and $59. Six months later, you discover through customer interviews that 40% would have paid $79/month for your feature set. That “reasonable” pricing just cost you 38% of potential revenue.

This isn’t uncommon. Research by ProfitWell shows that only 2% of SaaS companies spend significant time on pricing optimization, despite pricing having 4x the impact on profitability compared to customer acquisition improvements.

The solution lies in research-based pricing methodologies that quantify customer willingness-to-pay before you set prices. Two proven approaches stand out for SaaS applications: Gabor-Granger pricing analysis and the Van Westendorp Price Sensitivity Meter.

These methodologies transform pricing from guesswork into data-driven decision making. They reveal not just what customers will pay, but how demand changes across price points, enabling you to optimize for different business objectives—whether maximizing revenue, profit, or market penetration.

For SaaS founders serious about pricing optimization, understanding and implementing these research methods is essential. This guide provides practical frameworks for running both tests, interpreting results, and translating insights into actionable pricing strategies.

Section 1: Gabor-Granger Pricing Explained

The Methodology Behind Gabor-Granger

The Gabor-Granger method, developed by economists André Gabor and Clive Granger in the 1960s, measures price elasticity by presenting respondents with different price points and capturing their purchase intent at each level.

Here’s how it works for SaaS:

Step 1: Price Point Selection Start with 5-7 price points spanning your expected range. For a SaaS priced around $50/month, test points like $29, $39, $49, $59, $79, $99, $129. Include prices both above and below your current thinking.

Step 2: Sequential Presentation Present prices individually to respondents, asking: “At [price point], how likely would you be to purchase this software solution?” Use a 5-point scale from “Definitely would buy” to “Definitely would not buy.”

Step 3: Demand Curve Construction Calculate the percentage of respondents indicating purchase intent (typically “definitely” plus “probably” would buy) at each price point. Plot this data to create your demand curve.

Step 4: Revenue Optimization Multiply purchase intent percentages by price points to identify the revenue-maximizing price. This becomes your optimal price point from a pure revenue perspective.

Sample Size Considerations for SaaS

Sample size requirements vary based on your SaaS maturity and precision needs:

Early-Stage SaaS (Pre-Product Market Fit): 100-150 respondents provide directional insights for initial pricing decisions. Focus on recruiting prospects who match your ideal customer profile rather than achieving statistical perfection.

Growth-Stage SaaS: 200-300 respondents enable more precise demand curve modeling and support A/B testing different pricing approaches across customer segments.

Enterprise SaaS: Smaller samples (50-100) may suffice given the concentrated nature of enterprise markets, but ensure respondents have actual purchasing authority.

Statistical Note: For results within ±5% margin of error at 95% confidence, target 385+ respondents. However, practical business decisions often require less precision, making smaller samples actionable for most SaaS applications.

Pros and Cons of Gabor-Granger for SaaS

Advantages:

• Simplicity: Easy to design and implement compared to conjoint analysis or other advanced methods
• Clear Output: Produces intuitive demand curves that stakeholders readily understand
• Revenue Focus: Directly identifies revenue-optimizing price points
• Segment Analysis: Enables comparison across customer segments or use cases
• Quick Turnaround: Results available within days rather than weeks

Limitations:

• Purchase Intent vs. Actual Behavior: Stated intentions don’t perfectly predict real purchasing decisions, particularly for complex B2B sales
• Context Absence: Evaluates price in isolation without considering competitive alternatives or feature trade-offs
• Single Product Focus: Less effective for SaaS with multiple plans or complex packaging decisions
• Price Anchoring: Sequential presentation can bias responses as respondents anchor to previously shown prices

SaaS-Specific Considerations:

Gabor-Granger works best for SaaS companies with relatively straightforward value propositions and clear target markets. It’s particularly valuable for:

• Initial pricing decisions for new products
• Evaluating price increase tolerance among existing customers
• Comparing pricing across geographic markets or customer segments
• Quick validation of pricing hypotheses before more complex research

Section 2: Van Westendorp Price Sensitivity Meter

The Four Critical Questions

The Van Westendorp Price Sensitivity Meter, developed by Dutch economist Peter Van Westendorp in 1976, approaches pricing from a psychological perspective. Rather than measuring purchase intent at specific prices, it identifies price thresholds where customer perceptions shift.

The methodology centers on four carefully worded questions presented to respondents after they understand your SaaS offering:

Question 1 – Too Cheap: “At what price would you consider this software so inexpensive that you would question its quality or capability?”

Question 2 – Cheap/Good Value: “At what price would you consider this software to be priced as a bargain—a great buy for the money?”

Question 3 – Expensive/Getting Costly: “At what price would you consider this software starting to get expensive, so that it’s not out of the question, but you would need to think twice before buying?”

Question 4 – Too Expensive: “At what price would you consider this software to be so expensive that you would not consider buying it?”

Interpreting the Optimal Price Range

Van Westendorp analysis produces several key price points by plotting cumulative response curves:

Marginal Cheapness (MC): Where “too cheap” and “not expensive” curves intersect. Below this price, more people consider the product suspiciously cheap than acceptably priced.

Marginal Expensiveness (ME): Where “too expensive” and “not cheap” curves intersect. Above this price, more people find it prohibitively expensive than reasonably priced.

Optimal Price Point (OPP): Where “too cheap” and “too expensive” curves intersect. This represents the price with minimum resistance—the sweet spot where fewest people have strong negative reactions.

Indifference Price Point (IPP): Where “cheap” and “expensive” curves intersect. Equal numbers consider it a bargain versus getting costly.

The Acceptable Price Range: Between MC and ME lies your acceptable pricing range. Within this band, more respondents find pricing reasonable than unreasonable.

Practical Application for SaaS

For a hypothetical project management SaaS, results might look like:

• Marginal Cheapness: $31/month
• Indifference Point: $52/month
• Optimal Price Point: $58/month
• Marginal Expensiveness: $87/month
• Acceptable Range: $31-$87/month

This suggests pricing between $52-$58/month optimizes for broad market acceptance while avoiding quality concerns.

Pros and Cons of Van Westendorp

Advantages:

• Psychological Insight: Reveals underlying price perceptions and quality assumptions
• Range vs. Point: Identifies acceptable pricing ranges rather than single price points
• Brand Positioning: “Too cheap” responses help avoid pricing that undermines brand perception
• Market Boundaries: Clearly defines maximum sustainable pricing levels
• Versatile Application: Works across B2B and B2C contexts

Limitations:

• No Revenue Modeling: Doesn’t predict actual purchase behavior or revenue impact
• Assumption Dependencies: Assumes rational price-quality relationships that may not hold for innovative SaaS solutions
• Survey Fatigue: Four questions require more respondent engagement than simpler methods
• Complex Analysis: Curve plotting and intersection identification requires statistical software

SaaS-Specific Applications:

Van Westendorp excels for SaaS companies needing to understand:

• Market price expectations for new categories or innovative solutions
• Quality perception thresholds for premium positioning strategies
• Pricing boundaries for different customer segments or geographic markets
• Brand perception risks from aggressive pricing strategies

Section 3: Applying Tests in SaaS Context

Designing Surveys for Enterprise Buyers

Enterprise SaaS pricing research requires careful consideration of B2B buying dynamics and decision-making processes.

Respondent Qualification: Enterprise buyers differ significantly from individual consumers. Screen for:

• Job function and seniority level
• Budget authority or influence
• Company size and industry
• Current solution usage and satisfaction
• Purchase timeline and decision-making process

Example screening question: “In your organization, what role do you play in selecting and purchasing business software solutions like project management, CRM, or analytics tools?”

Context Setting: Enterprise buyers evaluate solutions within existing technology ecosystems and budget constraints. Provide sufficient context:

“Imagine your organization is evaluating project management software solutions. The solution includes features like task management, team collaboration, reporting dashboards, and integration with tools like Slack and Office 365. Implementation includes onboarding, training, and ongoing support.”

Question Adaptation: Modify standard question language for B2B contexts:

Instead of “At what price would you not consider buying?” ask “At what monthly cost per user would this solution exceed your department’s software budget allocation?”

Multiple Decision Makers: Enterprise purchases involve multiple stakeholders. Consider surveying:

• End users (who evaluate functionality and usability)
• IT administrators (who assess security and integration requirements)
• Budget holders (who evaluate cost-benefit and ROI)
• Procurement teams (who negotiate contracts and terms)

Survey Platform Selection and Setup

SurveyMonkey: Best for straightforward implementations with built-in Van Westendorp templates. Offers good respondent targeting options and basic analysis tools. Pricing starts at $25/month for professional features.

Prolific: Ideal for reaching high-quality B2B respondents. Pre-screened participant pools include verified professionals. Expect $5-15 per completed response for business decision-makers.

Artificial Societies: Specialized platform offering advanced pricing research methodologies. Includes sophisticated analysis tools and expert consultation. Premium option at $2,000+ per study.

UserInterviews: Excellent for recruiting enterprise buyers through professional networks. Higher cost ($50-200 per respondent) but superior participant quality for high-value pricing decisions.

Survey Design Best Practices:

1. Mobile Optimization: 40% of B2B respondents complete surveys on mobile devices
2. Progress Indicators: Show completion progress to reduce abandonment
3. Logic Branching: Skip irrelevant questions based on previous responses
4. Attention Checks: Include validation questions to identify inattentive respondents
5. Incentive Alignment: Offer results summaries or industry benchmarks as participation incentives

Translating Results Into Price Tiers

Most SaaS companies implement tiered pricing rather than single price points. Here’s how to translate pricing research into multi-tier strategies:

Step 1: Identify Segment Demand Curves Run separate analyses for different customer segments:

• Small business vs. enterprise
• Different industries or use cases
• Geographic regions
• Current vs. prospective customers

Step 2: Map Features to Price Sensitivity Combine pricing research with feature preference studies to understand:

• Which features justify premium pricing
• Where feature limitations are acceptable for lower tiers
• How to structure good-better-best progressions

Step 3: Design Tier Architecture Use research insights to structure tiers:

Starter Tier: Price at lower end of acceptable range (near MC from Van Westendorp or low purchase intent from Gabor-Granger). Include core features with meaningful limitations.

Professional Tier: Price near optimal points from both methodologies. Include features most important to mainstream buyers.

Enterprise Tier: Price at upper end of acceptable range. Include advanced features and services that justify premium pricing.

Example Implementation: Based on project management SaaS research showing acceptable range of $31-87/month:

• Starter: $35/month (5 projects, 3 team members)
• Professional: $65/month (unlimited projects, 15 team members, advanced reporting)
• Enterprise: $125/month (unlimited users, API access, dedicated support, custom integrations)

Step 4: Validate and Iterate Implement initial pricing and monitor:

• Conversion rates across tiers
• Customer feedback and price objections
• Competitive responses and market dynamics
• Usage patterns and upgrade behavior

Use A/B testing to refine prices within researched ranges and gather real behavioral data to validate survey insights.

Advanced Applications and Considerations

Seasonal and Market Timing: B2B purchase patterns vary significantly by quarter and industry. January-March often sees higher willingness-to-pay as new budgets become available, while Q4 may show deal-hunting behavior as budget deadlines approach.

Geographic Variations: Price sensitivity varies dramatically across markets. Consider separate research for major geographic regions, adjusting for local purchasing power and competitive landscapes.

Freemium Integration: If offering freemium models, research helps determine:

• Where to set upgrade friction points
• Premium feature pricing that encourages conversion
• Free tier limitations that don’t cannibalize paid plans

Usage-Based Pricing: For SaaS with consumption-based models, modify questions to focus on:

• Per-transaction or per-user pricing tolerance
• Volume discount expectations
• Pricing model preferences (flat rate vs. usage-based vs. hybrid)

Conclusion: From Research to Revenue Growth

Pricing research transforms SaaS pricing from expensive guesswork into confident, data-driven decisions. Both Gabor-Granger and Van Westendorp methodologies provide valuable insights, but serve different purposes in your pricing toolkit.

Use Gabor-Granger when you need clear revenue optimization guidance and direct purchase intent data. It’s particularly valuable for established SaaS companies with defined markets and straightforward value propositions.

Choose Van Westendorp when entering new markets, launching innovative solutions, or needing to understand price-quality perceptions. It excels at revealing psychological price barriers and acceptable pricing ranges.

The most successful SaaS companies often combine both approaches: Van Westendorp to establish broad pricing boundaries and understand market psychology, followed by Gabor-Granger to optimize specific price points within those boundaries.

Implementation Roadmap:

1. Start Simple: Begin with Van Westendorp to understand your pricing landscape
2. Test Often: Conduct pricing research quarterly or before major product releases
3. Segment Smartly: Run separate analyses for distinct customer groups or use cases
4. Validate Behavioral: Follow survey research with small-scale pricing tests or A/B experiments
5. Monitor and Adjust: Track actual buying behavior against research predictions and refine approaches

Remember: pricing is not a one-time decision but an ongoing optimization process. Markets evolve, competitors respond, and customer needs shift. Regular pricing research ensures your pricing strategy evolves with your market.

The investment in proper pricing research—typically $5,000-15,000 for professional implementation—pays dividends through improved conversion rates, higher average revenue per user, and reduced price objections during sales processes.

Most importantly, research-based pricing builds confidence throughout your organization. Sales teams sell more effectively when they understand price justification. Marketing messaging becomes more compelling when aligned with customer value perceptions. Product decisions improve when feature development considers pricing implications.

Pricing is not guesswork. Start simple, test often, and adjust based on data rather than intuition. Your customers—and your revenue—will thank you.