Best practices for Generative AI packaging and pricing

In our recent, Global Pricing Study we established that 40 to 60% of innovations fail to meet financial targets or fail entirely. We also find mixed signals about profitability of highly innovate AI companies (e.g., Anthropic’s 50-55% margin), which shows that a point raised by Andreessen Horrowitz in 2020 that AI gross margins are often 10-20 p.p. lower than SaaS peers remains relevant.

As SaaS companies strive to innovate and deliver more value to their customers, the integration of Generative Artificial Intelligence (Gen. AI) features presents a unique opportunity. By harnessing the power of Gen. AI, the technology provides unique opportunities to unlock revenue growth. In our recent Global Software Study, 73% of SaaS executives expect Generative AI to lead to more than 10% increase in revenue. Yet, for many companies there is no clear plan on how to realize this. Given all we know about lower margins and pitfalls for new innovations, how can SaaS companies create a sustainable business?

We know from our experience working with SaaS and AI-native companies that a good monetization strategy is key. In our previous article, we discussed considerations between giving the added value of Gen. AI features away for free (anticipating future gains) versus pricing these features and monetizing them directly. This article dives deeper into the world of direct monetization and provides six practical packaging and pricing best-practices for Generative AI. 

Best practice 1: Understand the feature’s role in the packaging line-up

The foundation of a successful monetization strategy begins with a comprehensive understanding of the feature’s role within the product. For this, two questions are relevant: “1) How many (prospective) customers would use this feature?” and “2) To what extent would customers that use this feature be ready to pay a large (or small) price premium?”. By answering these questions, businesses can assess the feature’s potential to drive revenue and categorize it as a leader (high interest and willingness to pay), filler (high interest, but low willingness to pay), add-on (low interest, but high willingness to pay), or killer (low interest and low willingness to pay).