Hi Everyone, I'm Gary, based out of Connecticut, and I work with some of the Upper mid-market private equity funds to gather competitive information on pricing, product, packaging and positioning. It's been a long road getting to this point, but I'm pretty embedded in half a dozen funds, where we've turned elements of the traditional pricing consultancy model on its head. Essentially, we map the market, reverse engineer what best in class looks like, and spot the gaps in what's being offered to customers by the marketplace today. Look forward to getting to know you all, and happy to answer any questions if there are any. Cheers, Gary

Howdy pricing people! Hope your week is off to a great start. In two weeks, we're hosting a private event with Scott Woody, CEO of Metronome. Scott is one of my favorite thinkers on SaaS and AI pricing, and past Office Hours sessions have been jam-packed with insights. We're looking for a short list of leaders at Enterprise SaaS and AI companies to join the session to discuss: - Designing Pricing & GTM for AI - Building a Monetization Operating System - Open Floor: AI Pricing Challenges You're Facing We'll be keeping attendance to this one limited. If you'd like to attend, apply at the link below: https://luma.com/z6cw0f54 Otherwise, have a great week! If you're in the US, happy Thanksgiving 🦃 Rob

We’re deploying an AI agent on a large e-commerce website with 1M+ monthly visitors, and expect around 5% to engage with the chat. The agent will handle support, product recommendations, cross-sell, and guided shopping. The backend runs on Voiceflow, and the client will be on our subscription, meaning we carry the credit usage cost — which is the core pricing challenge. We’re trying to structure a model that: - Keeps us safely profitable - Protects us from usage spikes - Feels predictable for the client - Optionally includes a success fee (% of revenue generated through the chat) Current ideas: - One-time setup fee - Monthly base fee - Usage-based tiers or cost pass-through - Small performance % on AI-driven conversions Would love to hear how you’d structure this and what’s worked for you in high-volume deployments.

Okay, so the Pokemon catchphrase 'Gotta catch 'em all' sums up this problem: Some pricing models inhibit the natural expansion volume of the customers - e.g.: - We sell factory locations, but customers start with 1 factory and grow slowly from there. - We sell 10 users... but every customer have 100+ potential users. - We price per patient... but only get to handle patients of type A, not types B and C. The simple example-fix is to price per number of employees (a volume outside the control of the customer) instead of per user (a volume controlled and reduced by the customer)... but what other ways have you guys used to solve the share-of-wallet problem? Asking for a friend 😉

Howdy Pricing People 👋🏼 There's a fundamental tension in SaaS I can't stop thinking about: Every SaaS company wants an AI story right now. To have a credible AI story, people need to be using your AI features. If people are using your AI features at scale, your margins will take a hit. Nobody wants margin erosion because we're still valuing SaaS companies on metrics built for the previous generation. The short-term playbook says protect your margins. The long-term playbook says invest in AI or get left behind. They don't reconcile. I'm genuinely curious how you're all thinking about this: - What should SaaS companies be doing right now? - Seemingly everyone is turning to credits as a hedge to both tell the AI story and maintain margin control. Are there other strategies SaaS companies should consider? - Does something fundamental need to change in how we evaluate these businesses? Drop your thoughts below. I'll be digging into this in this week's newsletter, and would love to share perspectives from this group. 🫡 Rob