Pricing is one of the hardest things to get right as a business owner. Most of us start too cheap.Some go too expensive too fast.Others realize later they were undercharging for years. Looking back, my biggest lesson with pricing has been how much it affects who you attract, how profitable you are, and how seriously customers take you. So I’m curious from other operators here: What pricing mistake taught you the biggest lesson in business? Could be: • Charging too little• Raising prices too late• Not charging for something you should have• Overpricing early 👇 Drop your experience in the comments.

I just added this to a comment so sharing for visibility: The SaaS Monetization Tech Stack Billing has Stripe. Analytics has Amplitude. Feature flags have LaunchDarkly. Etc. But the system that decides when to upsell a user, what usage limit to enforce, or which paywall variant to show? That usually lives in a tangle of product code, feature flags, and duct tape... A few things that have came up: - The fragmentation problem is worse than most teams realize. Entitlement logic ends up duplicated across billing, product code, and feature flags. A simple pricing test that should take a day takes weeks because three systems need to stay in sync. My CTO (ex-Atlassian, Dropbox) is really good at explaining the risks/headaches from this "brittleness" to technical folks! - Mobile solved this years ago. RevenueCat and Superwall own the monetization layer for iOS/Android apps. Web SaaS has no equivalent — most teams are still stitching it together manually. The above content is really resonating with an ex-Revenue Cat guy who is now Head of Product at a web SaaS business. - The main benefit of getting it right (in-house or via tooling) is experiment velocity

Hey pricing people! We just published a new report with our friends at Nue.io. It's called PLG vs. SLG: What the Data Says About SaaS Growth in 2026. We analyzed 3,847 pricing, packaging, and product changes across 498 SaaS companies to figure out what's actually happening at the intersection of product-led and sales-led growth. Some of the most interesting findings: 1️⃣ Freemium strategy is bifurcating. Of the 40 companies that changed their free tier in 2025, roughly half tightened or eliminated it (Deputy, Plaid, Apollo GraphQL) and the other half expanded it (TravelPerk went fully free, Scratchpad loaded AI features into the free tier). There seems to be less interest in the middle. Companies are either going all-in on Freemium for activation, or pushing harder on monetization. 2️⃣ Trials are getting shorter. The median trial is heading from 30 days to 14. AI-native tools are already at 7. Voiceflow cut its trial in half while increasing AI tokens 150%. The bet: AI means users can hit value faster, so why give 30 days? 3️⃣ Credits are bridging the gap. 126% YoY growth in credit-based pricing. Monday, Figma, Miro, Notion, Hubspot - they've all implemented credit models. Credits are becoming the connective tissue between PLG and SLG — self-serve consumption that naturally creates sales conversations when pools run dry. Grab the full report here → We'd love your reactions. What matches what you're seeing? What surprises you? How are you thinking about a hybrid PLG + SLG motion right now? Drop thoughts and feedback in the thread 👇

I read this about SF moving agents back to seat-based licensing https://www.theregister.com/2025/12/05/salesforce_ai_pricing/ To me, this signals a gap in the value perception and it feels like they are admitting the customer doesn't know what the agent does and won't risk the variable bills. My assumption is that the flat-fee seats are a de-risking of the purchase for the buyer. Am I wrong? Would love to hear other takes on this ;)

Hey, community. Dealing with the (annual) challenge of price adjustment in a SaaS B2B company. Would like to know if someone could share successes and errors in choosing criteria to calculate adjustment. So far we consider inflation rate (I'm based in Brazil), taxes variation, US dolar variation and also a score built based on product's improvements in the last yar. Competitor analysis is a complement, but not very reliable since some make their adjustments after us. Hope to count on the group experience to improve my strategies. Thanks in advance!