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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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Based on our saas pricing book, Price to Scale, cohort analysis can indeed be a very useful tool in understanding the long-term impact of pricing experiments—especially in settings where you have a significant sample size, such as consumer or small business software situations.
Here are some key takeaways from the book:
• Cohort analysis helps you track how different groups of customers (or trials of a pricing experiment) behave over time. This is particularly valuable when assessing the long-term effects such as retention, revenue growth, and price sensitivity.
• As noted in the book (see Page 221), while the method works very well in consumer environments and even small business settings, its effectiveness can be limited in enterprise software contexts. This is mainly due to smaller sample sizes and more complex buying processes in such B2B settings.
• Using cohort analysis in tandem with other data collection methods (like conjoint studies and fixed trade-off screens mentioned in our book) can provide a rounded view of market reactions and help in projecting long-term revenue impacts.
In summary, cohort analysis is a powerful technique for pricing experiments, allowing you to observe customer behavior over time. However, it’s important to consider your specific setting since its utility may vary between consumer/small business and enterprise environments. This layered approach, as discussed in Price to Scale, helps in making more informed pricing strategy decisions.