.png)
Estd 4.22.2023
Introduction
In the competitive SaaS landscape, pricing strategy can make or break your business. While product features and customer experience remain critical, the right pricing model directly impacts your bottom line. A mere 1% improvement in pricing can yield an 11% increase in profits, according to research by McKinsey & Company. This powerful leverage explains why more SaaS executives are turning to price experimentation and A/B testing to optimize their revenue streams.
However, running effective pricing experiments requires measuring the right key performance indicators (KPIs). Without proper metrics, you risk drawing incorrect conclusions that could negatively impact your revenue and customer relationships. This article outlines the essential KPIs to track when conducting pricing experiments, helping you make data-driven decisions about your SaaS pricing strategy.
Revenue Metrics: The North Star of Pricing Experiments
Average Revenue Per User (ARPU)
ARPU serves as a fundamental metric when testing pricing variations. It's calculated by dividing total revenue by the number of users within a given period. When running pricing experiments, comparing ARPU between test groups provides immediate insight into which pricing strategy generates more revenue per customer.
For example, if your current pricing model yields an ARPU of $50, but your test variant produces an ARPU of $65, the new pricing structure shows promising results. However, ARPU alone doesn't tell the complete story—it must be evaluated alongside other metrics.
Monthly Recurring Revenue (MRR) and Annual Recurring Revenue (ARR)
For subscription-based SaaS businesses, MRR and ARR represent the lifeblood of the company. When testing pricing changes, monitor how each variant affects these metrics:
- MRR Growth Rate: How quickly is recurring revenue growing under each pricing model?
- Net New MRR: The additional recurring revenue from new customers
- Expansion MRR: Additional revenue from existing customers (upgrades, cross-sells)
- Contraction MRR: Lost revenue from downgrades
According to a study by ProfitWell, companies that regularly test and optimize pricing see 30% higher MRR growth compared to those that don't.
Customer Lifetime Value (LTV)
While immediate revenue impacts are important, pricing changes often have longer-term effects. LTV helps you understand the total revenue a customer will generate throughout their relationship with your company.
When analyzing pricing experiments, calculate projected LTV for each test group to assess long-term revenue implications. A higher price point might increase short-term revenue but decrease LTV if it leads to shorter customer lifespans.
Conversion and Acquisition Metrics
Conversion Rate
Perhaps the most telling metric when testing price points is conversion rate—the percentage of prospects who become paying customers. A dramatic drop in conversion rates after a price increase might offset any revenue gains from higher prices.
Track conversion rates at each stage of your funnel:
- Visit-to-trial conversion rate: Are prospects still signing up for trials?
- Trial-to-paid conversion rate: Are trial users converting to paying customers?
- Upgrade conversion rate: Are users moving to higher-tier plans?
Customer Acquisition Cost (CAC)
CAC measures the total cost of acquiring a new customer, including marketing and sales expenses. When evaluating pricing experiments, calculate the CAC-to-LTV ratio for each pricing variant to ensure profitability.
If your new pricing structure increases LTV without significantly affecting CAC, you've likely found a winner. Conversely, if higher prices increase CAC by requiring more intensive sales efforts, the net benefit might be minimal.
Retention and Customer Satisfaction KPIs
Churn Rate
Pricing changes often impact customer retention. Monitor both:
- Customer churn rate: The percentage of customers who cancel
- Revenue churn rate: The percentage of revenue lost from existing customers
According to data from Paddle, a 10% price increase typically leads to a 2-3% increase in churn rate for SaaS products with high perceived value. Tracking this metric helps determine if higher prices remain sustainable over time.
Net Promoter Score (NPS) and Customer Satisfaction
Price adjustments can affect how customers perceive your value proposition. Track NPS or customer satisfaction scores before, during, and after pricing experiments to gauge the impact on customer sentiment.
Salesforce found that customers who perceive they received fair value from a product are three times more likely to renew and five times more likely to recommend the product to others.
Feature Utilization
Customers who fully utilize your product features are typically less price-sensitive. During pricing experiments, measure feature adoption rates across test groups to understand if certain price points attract customers who engage more deeply with your product.
Segmentation Analysis
Segment Performance
Not all customer segments respond identically to pricing changes. Break down your analysis by:
- Customer size: Enterprise vs. SMB vs. startups
- Industry vertical: Healthcare, finance, retail, etc.
- Geography: Different regions may have varying price sensitivity
- Use case: Primary vs. secondary applications of your product
HubSpot's research indicates that segmented pricing strategies can increase revenue by up to 25% compared to one-size-fits-all approaches.
Plan Mix and Distribution
Track how pricing experiments affect the distribution of customers across your pricing tiers. If a price change pushes too many customers toward your lowest tier, you might be leaving money on the table.
Competitive Metrics
Win/Loss Rate Against Competitors
Pricing exists within a competitive context. Monitor how your pricing experiments affect win rates against specific competitors. According to Forrester, 65% of SaaS buyers compare at least three options before making a purchase decision, making competitive positioning crucial.
Price Perception
Conduct brief surveys to measure how prospects perceive your price-to-value ratio compared to alternatives. This qualitative data provides context for your quantitative metrics.
Conducting Effective Pricing Experiments
When implementing your pricing tests, consider these best practices:
Test one variable at a time: Change either the price point, pricing model, or packaging—not all simultaneously.
Ensure statistical significance: Use appropriate sample sizes and run tests long enough to achieve reliable results.
Account for seasonality: B2B SaaS purchases often follow quarterly or annual budget cycles that can skew results.
Consider grandfathering: To avoid disrupting existing customers, test new pricing only with new prospects.
Document everything: Record all test parameters, external factors, and market conditions that might influence results.
Conclusion
Effective pricing experimentation requires a holistic measurement approach that balances short-term revenue impact with long-term business health. By tracking this comprehensive set of KPIs—spanning revenue, conversion, retention, and competitive metrics—SaaS executives can make informed pricing decisions that drive sustainable growth.
The most successful SaaS companies view pricing not as a one-time decision but as an ongoing optimization process. According to OpenView Partners' SaaS Benchmarks Study, companies that run at least quarterly pricing experiments grow 30-40% faster than those that set and forget their pricing.
As you design your next pricing experiment, establish clear baseline measurements for these KPIs before making changes, determine what success looks like in advance, and be prepared to analyze results across multiple dimensions. With this disciplined approach, pricing optimization can become one of your most powerful growth levers.