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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 pricing strategy book, Price to Scale, there isn’t a one‐size–fits–all answer—it depends on your service’s cost structure, customer behavior, and desired revenue predictability. Here are the key points to consider:
• Directly charging per transaction (a linear or “pay-as-you-go” model) can be very intuitive for both you and your customers. It mirrors the service’s actual usage, and for payment-related SaaS where each transaction processes a similar level of value, this model is simple and easy to understand.
• Charging per dollar volume processed can more directly reflect the value your solution delivers. Larger customers or higher volume usage can benefit from volume discounts, and this approach aligns pricing more closely with the economic value derived from each transaction. It also allows for a flexible pricing structure—like our two-part pricing model—that combines a lower per-unit fee with a fixed platform fee, helping to stabilize revenue while still rewarding higher volumes.
• The book also emphasizes that pricing decisions should consider the difference between average cost and marginal cost. While the average cost might be high because of fixed expenses (such as development, infrastructure, and support), the marginal cost per transaction is often much lower. This means that a per-transaction model might overstate the cost of acquiring new customers if you’re basing decisions solely on average costs versus real incremental costs.
In summary, if simplicity and direct alignment with usage are paramount, a per-transaction pricing model can work well. However, if you want to capture the full value that high-volume processing offers while also building in revenue predictability, a two-part model (with components like a per dollar volume fee alongside a platform fee) may be more advantageous. As discussed in Price to Scale, closely understanding your cost structure and customer usage patterns is essential in choosing the best approach.