Diversifying Monetization Strategies for SaaS Companies in the Era of AI

SaaS companies have been increasingly exploring the integration of generative AI, large language models (LLMs), and custom AI/ML models to provide added value to their customers. However, while developing these products, it is crucial not to overlook the monetization aspect and treat it as an afterthought. In fact, it may be helpful to draw an analogy to the California Gold Rush – don’t show up without a shovel!

Two years ago, the shift to metered pricing for SaaS was predicted, although the catalyst for this shift was unknown at the time. Fast forward to today, and it is evident that AI has become the catalyst for this transformation. However, it’s important to note that this is not just a simple pricing change but a fundamental shift in business models.

Traditional SaaS pricing has revolved around a per seat model, but with AI as a consumption vector, accurate metering and usage-based pricing models are essential. Several companies have already successfully monetized AI through usage-based pricing, such as OpenAI, Twilio, Snap, Quizlet, Instacart, and Shopify. This model allows for fair and transparent pricing that scales accordingly, considering the variability in prompt/output sizes and resource consumption.

Generative AI poses unique challenges for monetization. The length of prompts and outputs may vary, and the resource consumption is directly related to the size of the prompt. Additionally, customer usage patterns will differ, leading to varying cost footprints. To address these complexities, usage-based pricing is a natural fit. Services like ChatGPT already utilize this model, making it an ideal choice for tools leveraging generative AI.

To effectively implement usage-based pricing, SaaS companies should focus on metering both front-end usage and back-end resource consumption. By accurately tracking the usage calls made to AI infrastructure, companies can gain visibility into the underlying cost footprint, enabling them to establish fair pricing and ensure healthy margins.

In summary, as SaaS companies explore the integration of AI technologies, it is crucial to consider monetization strategies from the outset. Shifting towards usage-based pricing models can promote transparency, scalability, and provide a fair exchange of value between companies and customers.


What is usage-based pricing for SaaS?

Usage-based pricing is a model where customers are charged based on their actual usage of a product or service. This pricing approach allows for greater flexibility and fairness, as customers only pay for what they use, rather than a fixed fee.

Why is usage-based pricing suitable for generative AI?

Generative AI poses challenges in terms of varying prompt/output sizes and resource consumption. Usage-based pricing takes these factors into account and provides a fair and scalable pricing model that aligns with the variability of generative AI usage.

How can SaaS companies implement usage-based pricing?

To implement usage-based pricing, SaaS companies should focus on accurately metering both front-end usage and back-end resource consumption. This involves tracking usage calls made to AI infrastructure to understand the underlying cost footprint and establish fair pricing structures.