.png)
Frameworks, core principles and top case studies for SaaS pricing, learnt and refined over 28+ years of SaaS-monetization experience.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Price elasticity testing in SaaS measures how demand changes when you adjust prices, using the formula: Price Elasticity = (% Change in Quantity Demanded) / (% Change in Price). SaaS companies maximize revenue by testing elasticity through A/B tests, analyzing demand curves, and finding the optimal price point where marginal revenue equals marginal cost.
For SaaS executives navigating pricing decisions, understanding your price elasticity isn't optional—it's the difference between leaving revenue on the table and capturing your product's true value. This guide breaks down the science behind elasticity testing and provides a practical framework for revenue maximization.
What is Price Elasticity in SaaS Pricing?
Price elasticity measures how sensitive your customers are to price changes. In the SaaS context, it quantifies the relationship between a price adjustment and the resulting change in new subscriptions, upgrades, or churn.
Elastic demand means customers are highly price-sensitive. A 10% price increase might cause a 20% drop in conversions. This is common for SaaS products in crowded markets with many alternatives.
Inelastic demand means customers are less price-sensitive. A 10% price increase might only reduce conversions by 5%. Products with strong differentiation, high switching costs, or mission-critical functionality typically exhibit inelastic demand.
Understanding where your product falls on this spectrum determines whether you should optimize for volume (lower prices, more customers) or margin (higher prices, fewer but more valuable customers).
The SaaS Price Elasticity Formula Explained
The core SaaS price elasticity formula is straightforward:
Price Elasticity (E) = (% Change in Quantity Demanded) / (% Change in Price)
Let's work through a practical example:
Your project management SaaS currently prices its Pro tier at $49/month with 1,000 new sign-ups monthly. You test raising the price to $59/month and observe 850 new sign-ups.
- % Change in Price: ($59 - $49) / $49 = 20.4%
- % Change in Quantity: (850 - 1,000) / 1,000 = -15%
- Elasticity (E) = -15% / 20.4% = -0.74
Interpreting elasticity values:
- E < -1 (Elastic): Demand drops faster than price increases. Price increases reduce total revenue.
- E = -1 (Unit Elastic): Percentage changes are equal. Revenue stays constant regardless of price direction.
- E > -1 (Inelastic): Demand drops slower than price increases. Price increases boost total revenue.
In our example, E = -0.74 indicates inelastic demand. The price increase would actually increase revenue despite losing some customers.
Understanding Demand Curves for Software Pricing
A demand curve visualizes the relationship between price points and customer acquisition rates. Building yours requires systematic data collection.
Mapping your demand curve:
- Gather historical data from past price changes, promotions, or regional pricing variations
- Plot price points (X-axis) against conversion rates or new subscriptions (Y-axis)
- Identify the curve's shape—linear, convex, or with distinct "cliff" points
Optimal pricing zones appear where small price movements cause minimal demand changes (flat sections of the curve). Avoid "cliff" zones where small increases trigger dramatic demand drops.
For many SaaS products, demand curves reveal psychological pricing thresholds—$99 to $100 might lose 2% of buyers, but $99 to $109 might lose 25% due to the three-digit barrier.
Setting Up Price Elasticity Tests in SaaS
Rigorous testing methodology separates actionable insights from misleading data.
A/B testing approach:
- Define cohorts: Split new visitors randomly between control (current price) and test (new price) groups
- Calculate sample size: Use statistical power calculators—typically need 1,000+ conversions per variant for reliable results
- Set test duration: Run for at least 2-4 weeks to capture weekly buying patterns
Testing tools:
- CPQ systems (DealHub, Salesforce CPQ) for quote-based pricing tests
- Subscription management platforms (Stripe, Chargebee) for self-serve pricing experiments
- Custom feature flags combined with analytics for granular control
Critical consideration: Test with new customers only. Changing prices for existing customers introduces churn variables that contaminate elasticity measurements.
Analyzing Elasticity Data for Revenue Maximization
Once you've collected elasticity data, calculate revenue impact across price points to find your revenue-maximizing price.
Revenue calculation example:
Using our earlier data:
- At $49: 1,000 customers × $49 = $49,000 MRR
- At $59: 850 customers × $59 = $50,150 MRR
Despite 15% fewer customers, revenue increases by $1,150 monthly (2.3% gain).
Finding the revenue-maximizing price:
Revenue is maximized where elasticity equals -1 (unit elastic). Test multiple price points to map your elasticity curve, then identify where E approaches -1.
Balancing volume and margin:
Revenue maximization isn't always the goal. Consider:
- Customer acquisition cost (CAC) at different volumes
- Lifetime value implications of different customer segments
- Market share objectives versus profitability targets
Common Pitfalls in SaaS Elasticity Testing
Seasonality errors: Testing during Q4 budget cycles or summer slowdowns skews results. Compare against same-period historical baselines.
Segment blindness: Enterprise buyers and SMBs often have dramatically different elasticity profiles. Test segments separately rather than blending results.
Insufficient duration: Statistical significance requires adequate sample sizes. Ending tests early produces unreliable coefficients that lead to poor decisions.
Ignoring churn effects: Price changes affect retention, not just acquisition. Factor in 3-6 month churn data for complete revenue impact analysis.
Applying Elasticity Insights to Your Pricing Strategy
Transform elasticity data into strategic action:
Tier optimization: If your entry tier shows elastic demand but your premium tier is inelastic, consider lowering entry pricing to maximize acquisition while raising premium prices to capture more value.
Dynamic pricing opportunities: B2B SaaS with inelastic demand during budget season but elastic demand in Q1 can implement time-based pricing strategies.
When to increase prices:
- Elasticity coefficient between 0 and -1 (inelastic)
- Strong feature differentiation from competitors
- Low churn and high NPS scores
When to decrease prices:
- Elasticity coefficient below -1 (elastic)
- Market share growth is the priority
- High customer acquisition costs need volume leverage
Real-World SaaS Elasticity Case Studies
Case 1: Analytics Platform
A B2B analytics tool tested raising their growth tier from $199 to $249/month. Results showed E = -0.45 (highly inelastic). They implemented the increase, boosting revenue 18% while losing only 9% of sign-ups. Annual revenue impact: +$340,000.
Case 2: Collaboration Software
A team collaboration tool in a competitive market tested a $12 to $15 price increase on their per-user plan. E = -1.8 (elastic). The price increase would have reduced revenue by 12%. Instead, they held pricing and focused on feature differentiation before revisiting.
Case 3: Vertical SaaS
A healthcare-specific SaaS discovered extreme inelasticity (E = -0.2) in their niche. They implemented three consecutive 15% annual increases over 30 months, growing revenue 52% with only 8% cumulative customer loss.
Download our SaaS Price Elasticity Testing Framework and Calculator to start measuring your pricing sensitivity and optimize for maximum revenue.