Hi everyone, and happy holidays! I am kicking off Q1 with a revamp of my current company's enterprise offering structure, from packages to pricing structure. Like many others, we are looking to move away from user-based pricing. I am planning to run WTP research through qualitative interviews to help us better understand the value within our product for large enterprises and to validate the options we have for new metrics to bring into a value-aligned pricing structure. My ask: Does anyone have resources they have found particularly insightful in informing how to set up successful qualitative enterprise WTP studies? Any lessons learned that could help me here? Any input is appreciated! Additional context: We're a Series A SaaS/"on-prem" hybrid product with deep open-source roots (https://www.localstack.cloud/).

Howdy pricing people! As we wrap up 2025, I'm curious: What's one piece of pricing content that really landed for you this year? Could be a book, an article, a podcast, or even just an idea that you found and immediately had to share. Drop it in the comments. Would love to see what resonated across the community! I'll start: I love the concept of Value Literacy that I learned from @Mark Stiving. He defines Value literacy as the understanding of how buyers perceive value, evaluate tradeoffs, and decide what to pay. Highly recommend the full post to go deeper on the concept. I expect this to become even more important in 2026, especially as we enter the Credit Apocalypse. Look forward to seeing what you all recommend so I can load up my holiday reading list 🙂 Happy Holidays! Rob + John

OpenAI just made Projects free for all 800M ChatGPT users. I like the move for a few reasons: 1. Projects is habit-forming. A place to keep stray notes about all the topics you care about. 2. Projects deepens usage. Adding instructions and context requires a level of depth beyond simple prompts. 3. This combo of stickiness and deeper usage should drive more upgrades. Stickier product + more sophisticated usage means users will hit their usage limits more often (and maybe using Projects makes them curious about Tasks and Custom GPTs?). Even if they don’t upgrade, they're less likely to leave ChatGPT. What do y'all think?

Sometimes it's not what you say on your pricing page, it’s how you display that information. I looked at hundreds of A/B tests that have the exact same info, but try…. A grid vs. bullets More white space vs. less white space Bigger text vs. smaller text Image + Stats vs. just stats Although best practices vary depending on industry, location, company stage, and a slew of other factors (we help you navigate that at DoWhatWorks!). Here are two principles that apply to the vast majority of the winning results… → It is easier to read the key thing you want the prospect to see. That is often bigger font, more white space around stats/text, visuals to highlight the key stats etc.. When a page is visually cluttered (images or text), those versions almost always lose. Stripe has been fascinating as a case study here because recently I was going through their tests (I include one around their pricing in the visual deck on this post) and over 90% of their tests can be boiled down to “simplification” and “clarity”. The versions that are simpler and clearer win. → Expectation to reality matching. When I click this button, or tile, what happens next? Simple, clear CTA text wins. Also, helpful subtext below buttons or header/subheader framing can help contribute to clarity here. → Don't make your prospect do math. We find time and time again that the versions of pricing pages with the least required computation win (so the 2-months free, and then 70% off for the first year... yeah, don't do that) When I look at recent website updates from Stripe, Ramp, Cartra, and dozens of others, I find a lot of the same information, but displayed in ways that are far more digestible.

I have spent a lot of time digging into our DoWhatWorks database of A/B tests from the top brands in the world to answer this question. It's a complicated one, with variance by industry and many other variables. That being said, in general, here are a few takeaways from the data... - 4 pricing plans seem to be a sweet spot that performs well for most brands and wins against 1, 2 or 3 plans - 2 pricing plans, seems to have a slight edge over 1 or 3 pricing plans. - 5 pricing plans often wins over 1, 2 or 3 pricing plans. Below you see a test from DirectTV where they tested into 4 pricing plans over 2. Again, there is a lot of nuance here, but some interesting directional guidance.