Howdy pricing people! Hope you're all having a great week before the holidays hit. We just published our latest collection, with 100+ add ons across product, services, and AI. John also built a slick AI Assistant so you can ask questions and find examples that are relevant to you. You can always download the PDF and feed it into your LLM as well 🙂 Grab the collection here → Question for this crew. Have you seen success with add-ons? Curious how you're all thinking about add-on strategy heading into 2026. Otherwise, hope you all have a relaxing holiday and get the chance to recharge over the break 🔋 Rob

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

Hey all! I’m looking for a small/boutique SaaS pricing consultant who can serve as an external ear on a monetization strategy I’m finalizing for FY26. This isn’t a “teach us pricing” project. The tactical stuff (user testing, billing experiments, packaging variants) is already underway. What I need is someone who can help stress-test the big picture and sanity-check the architecture. Specifically looking for help with: 1. Coherence check: does the strategy work as a system? 2. Blind spots: assumptions, hidden risks, unintended effects. 3. Pattern benchmarking: how our model maps to modern PLG + AI monetization patterns. 4. Narrative review - does it scale cleanly to C-level/board and down to PMs? 5. Sequencing risks - where rollout timing could break. 6. Edge-case audit - usage/plan boundaries, adoption cliffs, etc. If you know someone who fits this profile, or you’ve worked with a boutique firm that leans strategic (not just packaging projects), I’d love recommendations. Thank you!

I recently spoke with our research team at DoWhatWorks, and they shared a fascinating new trend they have uncovered. You have probably all seen a brand have a separate or de-emphasized pricing plan option below the regular plan cards. I have seen these alternative plans from dozens of SaaS, from Zoom to Shopify to Vidyard. Yet when brands A/B test these de-emphasized plans as separate plans, they nearly always test out of them. I included an image of an A/B test from Zoom where they test into just including the basic/free plan as part of the regular set of plans… I included another test from Typeform where they tested out of a de-emphasized enterprise plan, adding back in their enterprise plan to the main plan menu after testing it as a separate section… Back when I worked at Bonjoro, we tested out of having a separate Agency plan for our testimonial product, and we re-added that plan to the main plan cards after we saw a 5-6% drop in Agency plan selection with the de-emphasized option. It’s hard from the data to find a perfect number of pricing plans (although ElevenLabs going with 7 plans might be pushing it).... But the data does seem to show that when brands test having a separate, de-emphasized plan outside of the regular plan cards, they test out of it at a high rate. I share more depth on this and other issues of pricing on my Substack.

In 2019, I signed a pricing page contract with a public company. One primary challenge they wanted to address was their add-on positioning. Problem: They had high inbound traffic/trials, of which they felt roughly 25% could benefit from this additional adjacent add-on. Currently, they had ~3% adoption. The add-on was listed below each plan tier, but was primarily promoted in-app during the trial and via email. Some quick definitions when it comes to add-ons. Complementary add-on: If an add-on is directly connected to the main product line or widely applicable to the main audience, I call this a complementary add-on (I.e. you are an email marketing company, and you offer SMS as an add-on) Adjacent add-on: If an add-on is a distinct offering relevant to a smaller cohort of customers, say you do business accounting software, but have an HR suite add-on, I call this an adjacent add-on. Here are the things we tried that were effective and the things we tried that flopped. What worked… 1) We asked buyers on a multi-step intake if they had the problem that our adjacent add-on solved for. If they indicated yes, on the final sign-up step, we automatically added the add-on (with the ability for them to uncheck it). This led to a 3-4% upfront adoption lift. 2) We removed the add-on description/section from the main pricing plans and had a box for it separately down below. For complementary add-ons, I find it’s helpful to make it as turnkey as possible to add. Have a toggle or some basic option to add directly connected to the plans, “Email is $29/m -> Email + SMS is $39/m”. But for adjacent add-ons, because they are only relevant to a portion of your audience, this adds a lot of noise. 3) We added a sales-assist call. Their current add-on approach was nearly entirely marketing and product-driven. But when we identified the right fit folks and offered a complementary call to help them connect the adjacent add-on (remember this was now being added by default to the right fit folks), we saw a lift in adoption (and stickiness).