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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 the thinking in our saas pricing book, Price to Scale, the answer depends on two main factors:
• Cost Correlation – Choose a metric that aligns closely to your underlying costs. If your infrastructure’s cost structure is more directly affected by the compute required to process data (for example, due to significant operational expenses or scaling pressures), then basing your pricing on the data processed might be more appropriate. On the other hand, if most of your costs are associated with storage (such as S3 storage fees in a cloud model), then a storage-based pricing model may be a better match.
• Customer Perception and Market Acceptance – Select a metric that your customers can easily understand and that aligns with how they traditionally purchase similar services. As discussed in Price to Scale (see Chapter 3 on pricing metrics), when customers are trained to think in terms of a particular usage metric (like how Office 365 customers count employees or storage usage), deviating too much can lead to confusion or even resistance.
In practice, the book recommends evaluating your cost drivers and the customer’s buying habits together. If data processing is a direct driver of cost and is more volatile, you might choose it for its accuracy and granularity (especially in rapidly growing environments). However, if data storage is more predictable and familiar to customers, then it could simplify adoption.
Summary: Base your pricing on the metric that both reflects your actual cost behavior and resonates with your customer’s traditional purchasing patterns. This balanced approach is what Price to Scale advocates for a successful usage-based pricing model.