How to Test Your SaaS Pricing for Optimal Results
Discover effective strategies to test your SaaS pricing, improve unit economics, and optimize revenue without alienating existing customers.
Dec 13, 2024
As a SaaS founder, testing your SaaS pricing is essential.
You might realize your current pricing isn't optimizing your margins or revenue. A higher price or a new pricing model could improve your unit economics.
But changing pricing is tricky. You want to test your SaaS pricing without upsetting existing customers.
You're also concerned the new pricing might lower your conversion rate. Testing helps reduce this risk.
How can you test your SaaS pricing safely?
It depends on your goals—whether you're testing price points or pricing models.
It also depends on the resources you have available.
What does testing your SaaS Pricing mean?
To test your SaaS pricing effectively, start with two key questions:
What pricing parameter do you want to test?
What unit economics do you want to optimize?
1. Pricing parameters to test:
Price points: Adjust the price without changing the pricing model. Will a higher or lower price improve your target metrics? For example, increasing prices may boost ARPA, while lowering them could optimize LTV by reducing churn.
Pricing tiers: Adjust feature entitlements for each pricing tier, changing whether a feature is enabled on any given plan or the usage limit on the plan.
Pricing model: Make changes to the structure. This might include moving an add-on into an existing plan, adjusting feature entitlements, or entirely redesigning the model.
If you want a clear definition of what a feature entitlement is, checkout this article.
2. Unit economics that you can impact:
ARPA: Average revenue per account.
MRR: Monthly recurring revenue.
LTV: Lifetime value of a customer.
Churn: Customer retention rate.
Conversion rate: From sign-up to paying customer.
Margin: Profitability after costs.
These metrics are interconnected.
For instance, increasing ARPA can also raise MRR and LTV.
When you test your SaaS pricing, choose one primary metric to target and ensure changes don’t harm others.
For example, aim to increase ARPA by X% while maintaining gross margin.
Leveraging data to test your SaaS pricing
There are three main ways to test your SaaS pricing:
Conduct customer surveys
Analyze usage data to assess potential revenue impact
Test your SaaS pricing by combining willingness-to-pay analysis with data analysis
1. Test your SaaS pricing with customer surveys
Willingness-to-Pay (WTP) surveys
Use case: Testing price points.
How it works: A WTP survey helps to gauge how much customers are willing to pay for your product. While your initial pricing is a starting point, you won’t know the upper limit until you ask.
How to launch:
For frequently used SaaS products, you can launch the survey in-app using a banner.
For less frequently accessed products, you can send the survey via email to your customer base.
Conjoint Analysis
Use case: Testing price points and pricing tiers.
How it works: Show customers different versions of your plans, with varying prices and features. Let them choose the most appealing version. Repeated combinations help identify the most preferred plan.
How to launch: Use survey tools like OpinionX, Typeform, or Tally. Embed the survey in your product or send it via email.
Example of a conjoint analysis survey
Important Note: Surveys can provide valuable insights, but results are often biased. Customers only predict what they might pay, which differs from real-world purchasing behavior. Keep this in mind when testing your SaaS pricing.
That being said, while surveys might not pinpoint the exact price point, assessing WTP can still provide valuable insights. Comparing current WTP results with a survey from a few years back can help confirm whether it's time to adjust and improve your pricing.
2. Analyze usage data to assess potential revenue impact
Use case: Testing new pricing tiers or a new pricing model
When reshuffling features across pricing tiers, you can use customer usage data to predict what plan each of your customer would opt for.
For example, if a customer currently uses your public API, you can simulate that they’ll opt for a plan offering this feature. You can refine predictions by factoring in usage accross all your features. For instance, you can consider that if a customer uses 70% of a plan's features, they are likely to select that plan.
The same applies to switching pricing models.
For instance, if you move from a license-based model to a usage-based model (like Livestorm did in 2022), you can estimate the MRR impact by analyzing customer usage data.
Aggregate the data to determine which plan each customer might choose under the new model.
If your simulation shows an MRR increase, it's a positive sign that you may be in the right direction.
Important note: These simulations assume customers will pay for a plan simply because they use most of its features. Actual behavior might differ based on pricing perception.
3. Test your SaaS pricing by combining willingness-to-pay analysis with data analysis
Use case: Testing new pricing tiers, pricing models, and price points
If you have access to WTP (Willingness to Pay) data, you can incorporate it into your pricing simulator.
For example, you could assume that a customer will choose a plan if:
They currently use 70% of the plan’s features.
The plan’s price is within 10% of their WTP.
Note: When using WTP data from a Van Westendorp survey, you can rely on responses to the question: "At what price is the product too expensive?” to guide your analysis.
Opting for a sales-driven approach to test your pricing
Data-driven pricing tests often come with biases:
Survey responses are skewed.
Pricing simulators rely on assumptions that may not reflect real-life scenarios with prospects.
A practical way to test your SaaS pricing is to present the new offer directly to prospects through your sales team.
This approach may require adjustments in sales team incentives and operational processes, but it provides concrete insights:
Are prospects willing to pay the new price?
Do they frequently negotiate the pricing?
Do they understand the new pricing offer, especially for hybrid or usage-based models?
If the new pricing involves limits or feature entitlements, don’t implement these limits initially. Instead, have your sales team monitor new customers’ usage to ensure it aligns with their contracts.
For example, at Livestorm, when transitioning to a usage-based pricing model, we introduced limits on the number of registrants per month.
However, these limits weren’t enforced in the product at first. Instead, the sales team was notified when a customer exceeded their limits.
This allowed them to reach out and upsell effectively.
This method is especially useful when testing a new pricing model.
Beyond validating the price point, it helps determine whether customers understand the new offer and how it works.
Leveraging software specialized in testing SaaS pricing
Some software can help you test at scale different pricing offers. Note that the results that these tools enable to get are only relevant when you have enough data to test new pricing offers.
Tweaking feature flag management tools
Feature flag management tools like LaunchDarkly or Tggl let you control feature access for different customer segments.
These tools are perfect for testing new feature breakdowns in plans to increase revenue or implementing a usage-based pricing model without limiting feature access.
They allow you to adjust feature availability easily and even run A/B tests to compare results.
The best part? You can do all this without relying on your technical team.
Using specialized tools in pricing experimentations
New tools have emerged to help decentralize pricing logic from code, making it easier to test your SaaS pricing.
This is one of the top five best practices for implementing pricing, and these tools make it simple to execute.
Schematic and Stigg integrate with Stripe Billing to fetch your plans. They also allow you to configure feature flags, similar to tools like LaunchDarkly or Tggl. With these tools, you can map features to plans and instantly adjust feature configurations for specific customer segments—all without technical support.
Stigg makes it easy to experiment new pricing offers without relying on developers
For optimizing price points, tools like Corrily and 1Price.co are ideal. These platforms enable A/B testing of different price points on your pricing and checkout pages. By analyzing customer responses across varied price ranges, you can identify the price point that maximizes conversion rates based on robust data.
