From selling access to selling work (and what it means for you)

Is it time to say RIP to ARR?

👋 Hi, it’s Kyle Poyar and welcome to Growth Unhinged, my weekly newsletter exploring the hidden playbooks behind the fastest-growing startups.

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Annual recurring revenue (ARR) is the building block of SaaS metrics. And it's the main basis of SaaS valuation multiples.

It's (usually) high margin, predictable and growing. Which means SaaS companies are (usually) on track to become highly profitable at scale.

AI throws this off. What's not classic software ARR:

• Charging per successful AI resolution of a support ticket

• Charging per photo edited by AI

• Charging per task completed by the AI agent

• Charging per conversation held by an AI agent

• Charging per input/output token to access an LLM

We're moving away from charging for access to software and toward a model of charging for the work delivered by a combination of software and AI agents. Let’s dive into what’s happening and what it means for you.

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The rise of disruptive AI pricing models

The interest in next generation pricing models has been truly wild.

Technology companies are realizing they can't solely rely on seat-based subscriptions in an age of AI, automation and APIs where value is disconnected with how many people are logging in. Perhaps Salesforce going all-in on Agentforce (and charging $2 per conversation) was the push the industry needed.

I’ve been tracking some of the most disruptive AI pricing models announced so far; a subset are included in the graphic below.

Intercom was a first-mover last year with their Fin AI customer support agent and pricing model of $0.99 per resolution. In Intercom’s words, “this ensures that you only pay when Fin does what you care about most; resolving a customer’s question.”

Zendesk followed with a similar pricing model based on the number of successful autonomous resolutions by its AI agents. Customers can opt for a flexible pay-as-you-go plan or receive discounts for an upfront commitment.

Each product category has its own flavor of disruptive pricing.

• Legal AI products might charge for a demand package generated by AI or an AI-generated summary.

• Creator AI products might charge for the content that gets produced such as a video generation or amount of video created.

• GTM products might charge for specific tasks completed or workflows executed by the AI.

In many cases there’s a notion of AI “credits” where more advanced workflows cost more than basic ones. (Some, like workflow task automation provider Bardeen, are also getting creative with how they help customers predict credit consumption.)

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Selling work, not necessarily success

In many ways, these disruptive models are a spin on usage-based or consumption-based pricing where customers pay for a product based on how much they use it. But there are important nuances at play.

Folks are increasingly selling units of work completed rather than selling access to the software (seat licenses) or consumption of the software (usage). With the software and the service associated with the software now bundled together, there’s the potential for a lower total cost of ownership (TCO) for the customer along with greater pricing power for the vendor.

Putting this in context, the early iteration of software pricing was the on-premise model. All of the financial risk was on the customer. They paid upfront to own the software — and then were pretty much left on their own until there was a new version to sell.

Shifting to subscriptions lowered the upfront cost — buyers rented rather than owned software — and lowered the risk since customers could cancel if they didn’t see value. This made software more accessible, but it didn’t necessarily make software cheaper from a lifetime value perspective (I’d argue that this was part of the appeal to investors).

In my experience, subscription SaaS products capture about 10-15% of the estimated economic value they claim to deliver to their customers. Those with success-based billing can capture closer to 20-30% because there’s a more direct correlation between the product and the result. Output-based pricing, where customers pay for units of work delivered, falls somewhere in between.

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The dark side of success-based pricing