What methods can we use to find out if our pricing is optimal (customer surveys, willingness-to-pay studies, A/B testing prices), and which of these have others found most useful?

Below is a summary of methods discussed in our SaaS pricing book, Price to Scale, to help determine whether your pricing is optimal:

• Direct Customer Feedback

The book recommends gathering unprompted, open-ended feedback through customer surveys. This might involve questions that ask customers to force-rank pain points and benefits or give impressions when shown a pricing metric. These methods help you understand whether prices are viewed as “too high” or “too low,” and they surface both qualitative and quantitative insights about perceived value.

• Probing and Scenario-Based Interviews

Instead of relying solely on surveys, the book suggests using structured, probing questions during in-person interviews or through guided questionnaires. By walking customers through multiple pricing scenarios, you can capture not only their immediate reactions but also build projections about how the market might respond to certain pricing levels.

• Simulated Pricing Experiments

More experimental methods—akin to A/B testing—are touched on, especially in consumer or small business settings. A/B tests can be particularly useful when you have access to a significant sample size to reliably measure the impact of a price change. However, our book notes that in enterprise settings where purchasing decisions are more complex, such quantitative tests may not yield the full picture.

• Willingness-to-Pay Studies

While the book primarily focuses on qualitative and scenario-based methods, willingness-to-pay studies naturally complement these approaches by providing structured benchmarks. These studies can help anchor your pricing assumptions with industry-standard values, although the book emphasizes the importance of translating these findings into real-world business metrics.

In practice, many find that combining these methods yields the best insights. For example, using customer surveys to gather initial feedback on price perceptions, followed by more detailed probing interviews or controlled experiments (like A/B testing when the conditions allow) creates a holistic view of price sensitivity. The book specifically highlights the value of “fixed trade-off screens” and probing questions to drive actionable insights, especially when exploring the upper and lower bounds of customer willingness to pay.

In summary, our book Price to Scale suggests:

Use qualitative methods (open-ended surveys and structured interviews) to capture nuanced feedback.
Apply quantitative experiments (A/B tests, willingness-to-pay studies) when sample sizes and the context (e.g., consumer vs. enterprise) allow.
Tailor the approach to your market segment—what works well for consumer products might not directly transfer to enterprise settings.

This blend of feedback, scenario analysis, and experimental validation is what many have found most useful in fine-tuning optimal pricing strategies.