I pitched a recruitment agency owner a weekly list of companies likely to hire soon. $1,500 a month. He said no: "I just can't pay that for a maybe." Then he offered me 10% of whatever he bills those companies instead. His last fee would have paid me about 30k. That's 20 months of the price he turned down. He said yes to 10%, paid after he gets paid. Not signed yet. My guess: a monthly fee feels like a bill. A percentage feels free until it works. Would you have held the line on the monthly price, or taken the cut?

hi team! building out a tool that grades a pricing page on accessibility for agents. few principles so far: 1. discoverability --- llms can easily crawl site or convert into md files 2. completeness -- every plan has written overview (price if applicable, quotas/limits, triggers for upgrades / changes, overage behavior) 3. computability --- some formula or example on how to calculate a bill 4. edge cases --- definitions of specific terms, downgrades, comparisons etc 5. freshness -- changelog / version control of some sort what would you change?

Hi all, Curious to get your input on this. I'm working with a couple of vertical saas editors on their AI credit structure and I’ve been noticing an interesting shift in SaaS pricing in the AI era: companies seem to be moving away from explicit usage units (credits, tokens, number of tasks) towards more abstract notions of capacity or simply a consumption gauge. ChatGPT, Claude and Notion are interesting examples of this. Upsell in the pricing page is summarized to "more AI" or "x5 more usage", but there is no real unit/metric (at least not on the pricing page) I find it surprisingly opaque for the customer, but it solves a lot of the hassle on the editor's side, and simplifies the commercial effort if go to market is done correctly. Do you think this is an emerging pricing trend?

Howdy Pricing People! AI credits are everywhere right now, but almost nobody agrees on how to run them. On Wednesday, October 28 at 12 PM ET, we're hosting a Monetization Roundtable with three operators who have actually rolled out credits and are actively working on their models: - Rita Sherman, Sr. Director of Monetization at Gong - Jeff Curran, Head of Pricing and Packaging at Miro - Manu Mehra, Strategic Pricing Leader at Databricks We'll cover: - Why they moved to credits instead of seats or charging per outcome - How they set the price of a credit and decided what uses one up - Allowances, rollovers, and top-ups - What it took inside the company to launch, across billing, finance, sales, and support - What customers like and what they push back on If you're pricing an AI product, or about to, come with questions. Save your spot: https://tinyurl.com/2xmt6gao Hope to see you there! Rob

Hi everyone! Just joined this group and look forward to following the conversations. I am working on my second startup, bunny.com, which is billing optimized for B2B SaaS; quoting, self-service, revrec, analytics. Where other solutions like Stripe Billing are focused B2C and use cases where everyone pays the same, Bunny is optimized for custom pricing, quoting -> approval -> signature, amendments, renewals etc. (\_/) ( •,•) (")_(")