This article is based on Ismail Madni’s brilliant talk at the Product Marketing Summit in Austin. As a PMA member, you can enjoy the complete recording here. For more exclusive content, head over to your membership dashboard. 

More and more AI capabilities are being added to product roadmaps every single day. Even companies that aren’t using true AI are still incorporating increasingly advanced capabilities into their product. 

As product marketers, this gives us a golden opportunity to rethink how we price our offerings and the story behind that pricing – and that’s what I’m excited to talk to you about today.

A brief history of software pricing models

Let's start by taking a quick look at the history of software pricing models. 

We need to understand not just pricing and packaging, but also the storytelling around it. However, back in the 80s and 90s, there really wasn't much of a pricing story to be told. It was mostly one-time, large upfront purchases for on-premise software. You'd have some annual maintenance fees too. The story was just “this is the cost versus the value.”

In the late 90s and early 2000s, we saw the rise of cloud products with subscription models like Salesforce – monthly, annual, or multi-year recurring payments. It was cheaper upfront and the products were constantly updated, so there was real value there. But the pricing story didn’t evolve much – it was just “it's cheaper to buy with a subscription.”

Today, we see a lot of subscription and usage-based pricing models. I'm a big fan of usage-based pricing because it directly ties the cost to the value the customer receives – the actual outcomes you're providing them. It's much more of a pay-as-you-go approach. 

Subscription and usage-based examples. Per seat: Salesforce. Per task: Zapier. Per event: Eventbrite. Per resource: Snowflake.

There are tons of examples of usage-based pricing in B2B – examples like Zapier (per task/zap), Eventbrite (per event), Snowflake, and AWS (per resource). Their pricing directly ties to the outcomes being delivered. It's a win-win – vendors have to keep providing value, while customers only pay for what they actually use. 

How to tell a story with usage-based pricing

AI capabilities fit beautifully into the usage-based approach and the stories you can craft around it. As product marketers, we're storytellers. We tell stories about our products, their amazing outcomes, the problems they solve, and the jobs they help customers get done. 

With AI, we now have an opportunity to tell another chapter in that story through our pricing model and the messaging around it.

The usage metrics you select as pricing inputs can directly shape that narrative. Are you creating new workflows and saving time? Are you making people more efficient? Broadly speaking, AI is going to do one of those things – help users move faster, be more productive, save money, or enable new ways of working. 

Usage pricing metrics will drive the message on your pricing model Value Drivers –> Value Metrics –> Pricing Metrics

Your value drivers dictate the value metrics, which in turn suggest the pricing approach. If your product enables new workflows, you can price based on that workflow enablement. If it helps coding or copywriting happen faster, you can price accordingly – per article or line of code, for instance.

How to craft compelling messaging around your pricing strategy

To see how you can use your pricing model as the foundation of a story that resonates with buyers, let’s look at a couple of real-world examples – one from Intercom and one from GitHub.