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Frameworks, core principles and top case studies for SaaS pricing, learnt and refined over 28+ years of SaaS-monetization experience.
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Introduction
In the competitive SaaS landscape, finding the perfect pricing structure can be the difference between rapid growth and stagnation. Yet many SaaS companies approach pricing as a one-time decision rather than an ongoing optimization process. According to a study by Price Intelligently, a mere 1% improvement in pricing strategy can yield an 11% increase in profits—making it one of the highest-leverage growth levers available to SaaS businesses.
This is where experimentation platforms like Optimizely enter the picture. As a leading solution for A/B testing and experimentation, Optimizely provides SaaS companies with powerful tools to systematically test and refine their pricing strategies. Let's explore how you can leverage Optimizely's capabilities to transform your approach to SaaS pricing.
Why SaaS Pricing Demands Continuous Experimentation
Before diving into the specifics of using Optimizely for pricing tests, it's important to understand why SaaS pricing requires ongoing optimization:
- Market conditions evolve – Competitive landscapes shift, economic conditions fluctuate, and customer expectations change over time
- Value perception matures – As your product evolves, so does its perceived value
- Customer segmentation opportunities emerge – Different user segments often have varying willingness to pay
- Monetization models diversify – From usage-based to tiered to hybrid approaches, new pricing models continue to emerge
According to OpenView Partners' 2022 SaaS Benchmarks Report, companies that regularly test pricing are 25% more likely to exceed revenue growth targets compared to those that don't. Despite this, fewer than 15% of SaaS companies run systematic pricing experiments.
Key Pricing Elements You Can Test With Optimizely
Optimizely's experimentation platform enables you to test virtually every aspect of your subscription pricing strategy, including:
1. Price Points
The most straightforward test involves different numerical values for your plans. For example, testing a Professional plan at $49/month versus $59/month to determine price elasticity.
2. Pricing Structure
Beyond simple price points, you can test fundamentally different pricing models:
- Per-user pricing vs. flat-rate pricing
- Usage-based vs. feature-based tiers
- Annual vs. monthly billing options (with varying discount levels)
3. Feature Packaging
How features are bundled across different pricing tiers can significantly impact conversion rates:
- Testing which features serve as effective "step-ups" between tiers
- Evaluating the impact of moving specific features between plans
4. Visual Presentation
How pricing is displayed matters tremendously:
- Order of plans (placing the recommended plan in the middle vs. on the right)
- Highlighting specific plans as "recommended" or "most popular"
- Using different visual hierarchies to emphasize value propositions
Setting Up Pricing Experiments in Optimizely
Optimizely provides several approaches for implementing pricing tests, each with its own advantages:
1. Front-End Testing (Non-Transactional)
For initial explorations, you can test different pricing pages without actually charging different amounts:
// Simplified example of an Optimizely experiment setupvar variation = optimizely.get('variation', 'pricing_page_test');if (variation === 'control') { // Show original pricing showPricingTier('starter', '$29'); showPricingTier('professional', '$79'); showPricingTier('enterprise', 'Contact Us');} else if (variation === 'test') { // Show test pricing showPricingTier('starter', '$39'); showPricingTier('professional', '$89'); showPricingTier('enterprise', 'Contact Us');}This approach allows you to measure click-through rates and signup intentions before implementing actual price changes.
2. Full-Funnel Testing
For more robust insights, you'll want to test the entire purchasing funnel with real transactions:
- Create variations in Optimizely that modify your pricing page
- Ensure that selected prices persist through the checkout flow
- Implement backend logic to charge the correct amount based on the experiment variant
- Track both conversion rates and resulting LTV metrics
3. Audience Segmentation
One of Optimizely's most powerful features for pricing experimentation is audience targeting:
- Test higher price points with visitors from enterprise IP addresses
- Segment by geography to account for regional purchasing power differences
- Target different pricing for new visitors versus returning users
Measuring Success: Beyond Conversion Rates
While conversion testing is important, successful pricing optimization requires a more nuanced view of metrics:
Primary Metrics:
- Revenue Per Visitor (RPV) – The most holistic measure of pricing efficiency
- Average Revenue Per User (ARPU) – Evaluates your pricing strategy's effectiveness for converted users
- Conversion Rate by Plan – How different segments respond to various pricing tiers
Secondary Metrics:
- Activation Rate – Do users on different pricing plans activate key features at different rates?
- Retention Curve – How do different pricing cohorts retain over time?
- Net Revenue Retention – Do certain pricing structures lead to better expansion revenue?
According to data from Profitwell, companies that optimize for long-term metrics like LTV rather than short-term conversion rates achieve 14% higher growth rates on average.
Case Study: How Company X Used Optimizely for Pricing Optimization
A B2B SaaS company (anonymized) used Optimizely to test a fundamental shift in their pricing model with impressive results:
Original Model: Per-user pricing at $39/user/month
Test Variant: Base platform fee ($149/month) + reduced per-user fee ($19/user/month)
The experiment targeted new visitors to their pricing page over a 60-day period. The results were illuminating:
- Initial conversion rate decreased by 11% for the new model
- Average deal size increased by 32%
- 90-day customer retention improved by 18%
- Overall revenue impact was positive 24%
The company used Optimizely's results analysis to identify that the new model performed especially well with mid-market companies (50-200 employees) but underperformed with smaller companies. This led them to implement segment-specific pricing strategies.
Best Practices for SaaS Pricing Experimentation
Based on patterns observed across successful pricing optimization programs:
- Start with price sensitivity research before running experiments
- Test with new users first to avoid disrupting existing customer expectations
- Run tests for sufficient duration to capture full sales cycles (especially for B2B)
- Combine quantitative and qualitative data by interviewing prospects about their perception of tested pricing
- Consider second-order effects like support costs and retention that may impact long-term profitability
Avoiding Common Pitfalls
When using Optimizely for pricing experiments, watch out for these common mistakes:
- Testing too many variables simultaneously – This makes it difficult to determine which changes drove results
- Insufficient sample sizes – Pricing tests often require larger samples than UI tests
- Ignoring segment-specific impacts – A positive overall result might mask negative effects on valuable segments
- Short testing windows – Pricing tests need to run longer than typical conversion tests to account for decision cycles
- Neglecting to communicate value – Sometimes conversion issues stem from value perception rather than price sensitivity
Conclusion
Optimizely provides SaaS companies with a powerful platform for pricing experimentation, enabling data-driven decisions that can dramatically impact growth and profitability. By creating a systematic approach to testing price points, structures, packaging, and presentation, you can move beyond gut feelings and competitor benchmarking to develop truly optimized pricing strategies.
Remember that pricing optimization is not a one-time project but an ongoing process. As your product evolves, your market expands, and your understanding of customer segments deepens, continuous experimentation will help ensure that your pricing strategy remains aligned with both customer value perception and your business objectives.
The most successful SaaS companies don't just build great products—they also develop sophisticated approaches to capturing the value those products create. With tools like Optimizely, pricing optimization becomes a strategic advantage rather than an occasional guessing game.