Enterprise Software Pricing Guide

This is a full decision tree for how to price your SaaS product. We recently published an edition outlining some pricing considerations, and the demand for more pricing information was overwhelmingly positive. We wrote this edition to answer that call and build out a true pricing model decision tree, along with a full guide to help you determine which pricing structure actually fits your product, buyer, and market. One of the most common mistakes is starting with: “what should we charge?” The right question is: "how should customers pay us, and why?" At a very high level (full details in the comments), here's the decision tree: Step 1: Does value scale with users? → Seat-based. Simple, forecastable. Use this when each user gets clear, individual value and the product becomes more valuable as more people join (e.g. collaboration or workflow tools like Slack, Notion, Salesforce). It’s simple, familiar, and creates a clean expansion path as teams add users. . Watch out as AI reduces seats needed. Step 2: Does value scale with usage? → Usage-based. Use this when value scales directly with consumption, customers naturally use more over time, and the metric is simple and intuitive (e.g. API calls, messages, compute). It’s common in infrastructure, data, and AI products where cost and value rise in lockstep (e.g. Twilio, Snowflake). Step 3: Is value tied to a business outcome? → Outcome-based. Use this when you can directly tie your product to measurable outcomes (revenue, cost savings, risk reduction) and prove the impact with clear data. Intercom priced Fin at $0.99/resolved ticket and went $1M to $100M ARR. Step 4: Is the product a system of record? → Platform/tiered. Use this when your product becomes core infrastructure used across multiple teams, with growing workflows, data, and integrations that increase switching costs over time. It typically combines a base platform fee, tiered plans, and add-ons that unlock as customer needs mature (e.g. HubSpot’s free CRM → Starter → Pro → Enterprise). Their NRR improved from 101.8% to 105% after they overhauled structure. Most companies end up with a hybrid of the above. Hybrid pricing jumped from 27% → 41% adoption in just 12 months. Important: There is no “best” pricing model, only the one that best reflects how customers experience value. The right model depends on how value expands within an account (users, usage, outcomes, or platform adoption) and whether it matches your actual GTM motion and how deals close. From all the pricing workshops we've run, content we've curated, and conversations we've facilitated, the biggest piece of pricing advice is this: Treat pricing like a product: test, iterate, and refine it continuously. It’s a core part of your go-to-market, and what once had wiggle room is now a critical lever to get right. The full pricing model decision tree guide can be found in the comments. Hope it's helpful! How are you evolving your pricing model in 2026?

𝐈'𝐯𝐞 𝐣𝐮𝐬𝐭 𝐩𝐮𝐛𝐥𝐢𝐬𝐡𝐞𝐝 𝐦𝐲 𝐦𝐨𝐬𝐭 𝐢𝐧-𝐝𝐞𝐩𝐭𝐡 𝐚𝐫𝐭𝐢𝐜𝐥𝐞 𝐲𝐞𝐭 𝐨𝐧 𝐞𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐒𝐚𝐚𝐒 𝐩𝐫𝐢𝐜𝐢𝐧𝐠 𝐚𝐧𝐝 𝐝𝐢𝐬𝐜𝐨𝐮𝐧𝐭𝐢𝐧𝐠! After years in the trenches of SaaS pricing, I've seen firsthand how the wrong discounting strategy can turn today's big win into tomorrow's growth roadblock. With 70% of sales teams believing discounts are necessary and 77% pushing for 25%+ discounts, companies are eroding their own value. In this comprehensive guide, we dive deep into: ✔️ The hidden costs of early discounting that most founders overlook ✔️ 6 essential steps to set a bulletproof pricing strategy for long-term success ✔️ How to hold the line with your sales team (and the top 7 discount justifications you'll hear) ✔️ 5 common misconceptions about enterprise SaaS discounting (spoiler: freemium isn't the golden ticket) ✔️ Strategies to maintain pricing integrity while satisfying investor growth demands ✔️ Real-world tactics to compete against well-funded, price-cutting competitors But that's not all. We also tackle the tough questions: 💡 How do you handle internal conflicts over pricing strategy? 💡 What do you do when you realize your initial pricing was wrong? 💡 How can you overcome imposter syndrome when defending your product's value? If you're tired of leaving money on the table and ready to take control of your pricing strategy, this article is for you. Whether you're a SaaS founder working on your first big enterprise deal or a well experienced PM looking to optimize your pricing strategy, this article is your compass in the stormy seas of enterprise pricing. Let's stop the race to the bottom and start building value-based, profitable businesses. Subscribe to my newsletter for more insights on SaaS strategy, pricing, and growth. #SaaSPricing #EnterpriseGrowth #StartupStrategy #SaaSDiscounting

If you’re writing a pricing guide for an enterprise SaaS tool, and your entire article stops at, “𝘗𝘳𝘪𝘤𝘪𝘯𝘨 𝘪𝘴 𝘤𝘶𝘴𝘵𝘰𝘮, 𝘣𝘰𝘰𝘬 𝘢 𝘥𝘦𝘮𝘰” — you’ve already lost the reader. Let’s be honest: nobody clicked your article to be told what the pricing page already says. When I work on pricing guides, the goal isn’t to guess numbers or sensationalize them. It is to address: -> How do buyers actually think about cost before they ever speak to sales? Here’s what most pricing content misses and what writers should lead with instead: 𝟭. 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 > 𝗲𝘅𝗮𝗰𝘁 𝗻𝘂𝗺𝗯𝗲𝗿𝘀 Enterprise buyers aren’t hunting for a $7.99/month sticker. They want range, benchmarks, and relative cost. Approximate pricing, median contract values, and minimum deal sizes. This is what helps teams sanity-check budgets internally before a demo even happens. If you can’t give context, don’t write the article. 𝟮. 𝗥𝗲𝘃𝗲𝗿𝘀𝗲-𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗶𝗻𝘁𝗲𝗻𝘁, 𝗻𝗼𝘁 𝘁𝗵𝗲 𝗽𝗿𝗶𝗰𝗶𝗻𝗴 𝗽𝗮𝗴𝗲 Sales-led tools hide pricing for a reason. Your job isn’t to complain about it, it’s to explain how pricing is structured and what variables actually move the needle: user count, feature depth, contract length, support levels. That’s the real pricing story. 𝟯. 𝗗𝗼 𝘁𝗵𝗲 𝗺𝗮𝘁𝗵 𝗿𝗲𝗮𝗱𝗲𝗿𝘀 𝗮𝗿𝗲 𝗮𝗹𝗿𝗲𝗮𝗱𝘆 𝗱𝗼𝗶𝗻𝗴 𝗶𝗻 𝘁𝗵𝗲𝗶𝗿 𝗵𝗲𝗮𝗱𝘀 If pricing is per-user, per-month—spell it out. Show example calculations. Give scenarios for small, mid-sized, and large teams. This removes friction and builds trust fast. Readers want to know, “Are we talking 15K a year or 60K?” 𝟰. 𝗦𝗮𝘆 𝘄𝗵𝗮𝘁 𝘁𝗵𝗲 𝘀𝗮𝗹𝗲𝘀 𝗰𝗮𝗹𝗹 𝘄𝗶𝗹𝗹 𝘀𝗮𝘆—𝗲𝗮𝗿𝗹𝘆 Most articles avoid talking about minimum contract sizes, payment terms, or annual commitments because it feels “unofficial.” But buyers find out anyway… just later and with more frustration. Good pricing content prepares readers, not protects the vendor. 𝟱. 𝗖𝗼𝗺𝗽𝗮𝗿𝗶𝘀𝗼𝗻 𝗶𝘀 𝗰𝗹𝗮𝗿𝗶𝘁𝘆 Pricing never exists in isolation. The moment you show how a tool stacks up against competitors—cost-wise and feature-wise—you’ve shifted from surface-level SEO to actual decision support. That’s where pricing content stops being fluff and starts being useful. If you’re going to write pricing guides, understand buyer psychology. Kindly don't paraphrase a landing page. The best pricing content should not focus only on “How much does it cost?” But answers “Should I even keep considering this?” And that’s the bar. If your pricing pages or guides still feel vague and sales-heavy, I can help fix that. My DMs are open 💅

Three months running AI agents in production. Most questions I get are the same one. The right question is which tier, not which agent, and most teams get this backwards. In 2026, the market sorts into three groups. 1️⃣ Enterprise SaaS at the top: Salesforce, Microsoft, Google, AWS. 2️⃣ Open-source ready-to-run in the middle: OpenClaw, Hermes. 3️⃣ Frameworks at the bottom for engineering teams building from scratch.                                                                                   Most lean teams are looking at Tier 1 when the answer is almost certainly Tier 2.                                                                         The economics make the case quickly. Salesforce Agentforce runs $125 per user per month for internal agents. A self-hosted Hermes setup runs $6 per month for the server. That gap matters more than any feature comparison.                                                                                          Across Southeast Asia, 56% of Singapore firms and 51% of Indonesian firms are already scaling AI. Most of those experiments belong in Tier 2. Most of the budgets I see are pointed somewhere else. The tier mismatch is the most expensive mistake I watch teams make. One Gartner number shapes everything: over 40% of agentic AI projects will be cancelled by end of 2027. Cost overruns. Unclear value. Weak risk controls.                    The category is growing fast. So are the dead-end projects inside it. Since March I have been running Alex on OpenClaw and Nora on Hermes Agent. They started as executor and strategist. Three months later, the split has become Chief of Staff and cofounder. That was not the plan.                                                   Today I published the full field guide. Complete 2026 ecosystem map with all the players across each tier. Pricing breakdowns across all four enterprise platforms with the numbers that actually matter. Side-by-side on OpenClaw and Hermes with real server bills and API costs. Decision tree for one agent, two, or none. And the honest account of three months in production, including the things I have not figured out and am not pretending to. The map does not make the decision for you. It shows you which decisions are actually in front of you. https://lnkd.in/ec9tCRp3                                                                              Which tier is your team on today?                                                                              #AIAgents #FounderStack #SoutheastAsia

Selling to ENT without changing your pricing model is like showing up to a black-tie event in flip flops. MM pricing models don’t survive in enterprise sales. Why? Because selling 1,000 licenses to an enterprise isn’t 20x harder than selling 50 - but if you don’t adjust your pricing strategy, it will be 20x more painful. Enterprise buyers don’t think in per user terms. They think in budgets, forecasts, and cost centers. They want predictability, not a CPQ nightmare where they’re adjusting seat counts every quarter. If you’re moving upmarket, here’s how to avoid looking like a tourist at the grown-ups’ table: 1. Kill per-user pricing for large accounts. Enterprise CFOs see per-user models as a ticking time bomb...every new hire adds cost. Instead, sell in committed tiers, annual volume contracts, or all-you-can-eat licenses. - Instead of “$50 per user, per month,” structure it as, “$X for up to 1,000 users.” - Price for usage, not headcount - think storage, API calls, transactions, etc. 2. Enterprise doesn’t “expand naturally.” Build in expansion from day one. For MM, you can land small and grow. Enterprise doesn’t work that way. - Ramp pricing: Year 1 at 60%, Year 2 at 80%, Year 3 at 100%. Predictable growth, no CFO freak-outs. - Auto-expansion clauses: If usage exceeds X%, licenses auto-scale. Protects you from procurement pulling a “we’ll just add seats later” stunt. 3. Enterprise buyers expect to “win.” Give them a win - without losing. These buyers are trained to negotiate. They want a lower per-unit cost, but they’ll commit bigger dollars to get it. - Introduce an ENT Rate...lower per-unit cost, but higher minimum commit. CFOs love “efficiency,” and you get more ARR locked in. - Structure custom packaging that makes them feel special. Limited access to beta features, priority support, or bundled services. Want to win in enterprise? Stop selling like an SMB rep. Price for scale, control the expansion, and let procurement “win” on terms that make your CFO smile.

Enterprise pricing: Have MULTIPLE leverage points to use when negotiating. Founders: the conventional wisdom around pricing your product is to keep it simple. Unfortunately this works against you when you’re dealing with enterprise procurement teams. These team are the most sophisticated negotiators you will ever meet. They are single mindedly focused on extracting value for their company. If your pricing is too straightforward or simple, they will hone in on this and beat you down. And it will get worse with every renegotiation. As someone who, in his first PM job, ended up pricing his hardware product below Gross Margin after an enterprise negotiation, take it from me : you cannot go into an enterprise pricing negotiation with a singular point of leverage. You need complexity in the form of multiple leverage points. This is the only way to not give away your entire margin or profit pool. As an example, take a payment processing company selling to an enterprise. Their rack rate might be 2.5%, and they approach the enterprise with a seemingly great tiered deal, which the lowest tier being 1.8% above $100m in volume. (Their cost is 1.6%). Neat and clean, right? Not quite. A sophisticated enterprise negotiator will have a complete understanding of the processor’s cost basis, as well as what % of the processor’s business will be represented by the enterprise. Their counter will likely for their entire volume to be at or below cost. And they won’t budge, since their legacy payment processor offers them (a worse) product at 1.5%, so they have a good BATNA (best alternative to no agreement). The issue here is that the processor has left itself vulnerable by having a single leverage point - the payment processing rate. They tried to add a volume tier, but it’s not separate enough from the rate to use it effectively as a bargaining chip, not against enterprise negotiators. So what should the payment processor do? They must introduce a completely separate axis of negotiation. Essentially a new product or service. Here’s two examples: 1. “Sure thing, we will give you 1.6% for your entire volume. But this will necessitate significant support resources from us. you need to pay us $20k per month for enterprise support. “ Enterprises are perfectly happy to pay a predictable amount for support. This might work well for the first time negotiation. 2. Decompose the payment product into a bare bones payment product, and separate out premium features such as chargeback protection. “Ok, we will match your legacy processor on rate. But if you want chargeback protection, it’s $0.05 per transaction.” This might work as a backup to #1 above, or in the renegotiation after year 2. (Continued in comments)

Enterprise pricing. Most founders don't have a game plan beyond throwing up a "Contact Sales" button on the site. When I was first starting out as the co-founder of WayUp at 23 years old, I remember making all the pricing mistakes in the playbook in the early days. A quick anecdote to show just how naive I was with pricing – When we signed our first enterprise customer (a Fortune 100), as a hiring platform, we had them pay us at the end of the month based on how many applicants they received in the prior 30 days. They paid us $2K in Jan, $4K in Feb, $3.2K in March. By April, they asked us, “Can you just charge us at a flat rate for the next year, and we’ll sign a 12 month contract?” At the time I thought — “Holy crap. They’re just gonna pay us upfront?” I thought I’d come up with an innovative new business model. Then I looked it up and realized: oh, that’s just SaaS 🤣 After 7+ years building WayUp and working with hundreds of founders now as an investor, here’s a few bits of Enterprise pricing advice I wish I’d gotten back in 2014: 1) In the early days, try to stick to a pricing model/framework that resembles how your customers are used to buying software. For example, my customers were used to paying LinkedIn per seat for a flat fee per year. 2) Do pricing discovery before you give a quote. It’s very normal to ask your customer about their budget. And on that note… I don’t always agree with the generic advice to keep raising your prices until you hear from prospects that it’s too high. In my experience that misses a key nuance: Enterprise pricing isn’t one-size-fits-all. Two enterprise companies can have different budgets and spending philosophies (think Lockheed Martin vs. famously frugal Amazon). 3) What I found was effective (but it only works for certain businesses) was to let the customer determine their own pricing. For example, I’d give a pricing calculator spreadsheet where prospects could manipulate certain cells based on what they wanted to buy, so they could see how the price would change based on the # of seats or modules they want, the discounts they’d get for longer contracts, etc. This way, I never felt like I was negotiating against a customer – instead, they were negotiating with themselves. (Leave a comment if you’ like for me to DM you a link to a sample pricing calculator spreadsheet!) 4) For flat fee subscription contracts, if your goal is to sign multi-year contracts, give the client 3 options, where they get a higher discount for a longer duration. 5) Is a client insisting on a free trial? Try signing them on for a 12 month contract where they can terminate for any reason within the first 2 months, and where they can pay on day 61. 6) I strongly advise companies against raising the price dramatically at renewal. Too many startups start low, only to 8X the price one year later, which turns customers off and loses their trust. These are just a few tips. Any pricing principles you had to learn the hard way?

"Seat-based pricing is dead." I keep hearing this at every SaaS conference, in every blog, on every LinkedIn "hot take". But you know, most have an angle. So I decided to look at the data and form my own opinion. I analyzed 25+ enterprise B2B companies across AI, CRM, support, productivity, and L&D to see what's actually happening with pricing in the AI era. Here's what I found: Credit-based models grew 126% YoY in 2025 (35 to 79 companies in the PricingSaaS 500 Index). That's real momentum. But when you look at how the AI companies themselves price their enterprise products, it tells a very different story. Anthropic (Claude): $25-60/seat/month OpenAI (ChatGPT): $25-30/seat/month Glean: $45-50/seat/month Microsoft Copilot: $30/seat/month Harvey (AI legal, $11B valuation): $1,200/seat/month Hebbia (AI finance, $700M valuation): $3K-10K/seat/year Every single one sells seats to enterprises. If the companies building AI can't find a better model than seats for their own products, that's the strongest signal the market offers. Does outcome pricing work? Yes, but only in specific verticals. Customer support (Sierra, Zendesk, Intercom, Ada) works because the task is binary, the causal chain is short, and it directly replaces headcount. Developer tools (Cursor, Replit) use credits because inference costs are real and variable. But for platforms serving persistent human users with complex, long-causal-chain workflows? Seats persist. Not because companies are behind. Because the economics demand it. The real finding: your vertical determines your pricing model, not whether you use AI. Three things CFOs keep telling us: 1. Predictability is the #1 friction point when buying AI tools (McKinsey & Company) 2. 87% rank AI as critical to operations, but they want it in a budget they can forecast (Deloitte) 3. Credits suppress adoption; when every interaction has a cost, users self-censor I put together a full analysis covering all five pricing buckets, the AI-native wildcards (Sierra, Harvey, Cursor, EvenUp), and what this means for enterprise SaaS strategy. Carousel attached with the key insights. What pricing model is your company betting on? I'd love to hear what you're seeing in the market. Carousel is a summary. The full analysis available, comment or DM me to have access to it. #SaaS #AI #Pricing #Enterprise #B2B #ProductStrategy

Cursor just proved something most AI founders refuse to believe. Enterprise customers will pay 75x more than freemium users. But not for the reasons you think. Tomasz Tunguz's latest breakdown shows their $1,500 tier generates 32% of revenue from just 3.8% of users. (Article in comments) During a private meeting with Private Equity Investor yesterday, he revealed about why his portfolio companies chose the enterprise tier. "We don't pay for features. We pay for guarantees." Here's what most AI founders miss about enterprise pricing psychology: Enterprises don't buy your AI because it's smart. They buy it because it's predictable. Your brilliant model means nothing if it fails during their quarterly board presentation. The real enterprise value isn't in your algorithms. It's in your infrastructure promises. When a bank deploys AI code generation, they need 99.9% uptime guarantees. When a manufacturer uses AI for production planning, they need consistent response times. When a healthcare company implements AI diagnostics, they need audit trails and compliance. Your freemium users care about capabilities. Your enterprise users care about consequences. This is why the "land and expand" strategy breaks for AI companies. You can't land with a smart demo and expand with enterprise promises. The infrastructure gap is too wide. Most AI founders build for the 96% who pay $20. Winners build for the 4% who pay $1,500. Three questions every AI founder should answer: If your biggest customer needed 10x more capacity tomorrow, could you deliver it? When enterprise buyers ask about your disaster recovery plan, what do you show them? Are you selling AI features or business guarantees? Companies like SimplAI are building the infrastructure enterprises actually buy. I'm seeing success stories everyday with Sandeep Dinodiya and team. What's your experience with freemium vs enterprise AI pricing? Does the 75x multiplier match what you're seeing?

I've seen various websites pop up claiming to offer the prices that other users pay for enterprise SaaS software. https://www.vendr.com is a new one that's making the rounds. The price an enterprise pays for high AOV SaaS, like a commerce platform, is next to impossible to reverse engineer. Enterprise SaaS pricing depends on some combination of: - How much do you use the product? A retailer selling $25k watches and $2 pencils may have the same GMV at the end of the year but dramatically different product usage patterns. We have internal gross margin targets and try to peg our pricing to that - How successful do we think you'll be? We as a vendor don't want failed implementations out there. They're expensive for us to fix and cause reputational damage. If we think you're going to ignore our guidance, we may charge you a premium. We want to partner with our customers: https://lnkd.in/guFDHQtC - Will you do referencing for us? If we as a vendor can have you do a mainstage keynote or speak to other prospects on our behalf, that's worth a lot to us - What's the cross-sell and up-sell potential? Can we make you so successful that you'll end up using us for other use cases, geos, etc? - Can we kneecap a competitor? Starving a specific competitor in a geo or for a specific use case is valuable for us on occasion - Do you help us as a vendor enter a new geo? Having a flagship customer in a new country or geo is valuable - Can you help us as a vendor enter a new vertical? Having a flagship customer in healthcare, or government, for example is worth a discount - Do you have a reputation for not paying bills? The CFO of a certain midwestern retailer was famous for having a sign on his office door titled "25 reasons not to pay a vendor invoice." No thanks - Are you at risk of bankruptcy, PE takeover, or some other big event that could impact your strategy and/or your ability to pay? For smaller ticket SaaS, like an Office or Slack subscription, different rules apply. But for something as consequential as a commerce platform - the above considerations can definitely impact the price you pay.