B2B software pricing and innovation trends

25% of B2B companies expect to use outcome-based pricing by 2028. That's a 5x increase from today's 5%, according to Kyle Poyar's latest research.   This will be a painful, but ultimately healthy transition.   Buyers never wanted software in the first place. They wanted solutions. As AI handles more work end-to-end, pricing migrates from inputs (seats, tokens, usage) to outcomes (cases closed, revenue recovered, risk reduced). Less "how much did you use?" More "did it actually work?"   Thought experiment: if code becomes a commodity and features ship instantly, value shifts from building features to guaranteeing execution. You’re not selling software—you’re selling outcome insurance.   Objections are real—attribution is messy, procurement habits are sticky, and buyers hate surprises. But these are solvable with instrumentation, shared definitions of success, and clear guardrails (Manny Medina). Over time, buyers will demand outcome-based pricing because it reduces their risk. Where outcome-based pricing already fits well: AI-enabled services. Services own end-to-end execution, so attribution is clean and incentives align. Mechanical Orchard is a great example—using AI to move mainframe workloads to the cloud, taking ownership of the entire journey. When you own the “last mile,” charging for success becomes straightforward.   AI customer support vendors have also been pioneers of this model. More vendor types are on the horizon.   If you’re a founder, here’s a simple path to test outcomes pricing: • Pick one mission-critical outcome your product directly influences. • Define a verifiable metric, baseline, and observation window with the buyer. • Cap downside (floor) and share upside (tiers/bonus) to build trust. • Instrument attribution now—event logs, holdouts, and third-party validation beat hand-waving later.   Start with one outcome. One customer. One measurable result you can guarantee. We're still early in this shift, but the direction is clear.   For those already experimenting with outcome-based pricing, what's been your biggest surprise? And for those that haven't yet, what's holding you back?

Back when the AI boom first kicked off, most startups defaulted to usage-based pricing: charging per token, message, or API call. Simple, familiar (like AWS), easy to ship. But as inference costs plummet this approach is becoming a dangerous race to the bottom. The reality is customers care about outcomes and business value. How you charge is becoming as important as what you build. We’re seeing 4 distinct pricing models as companies move away from pure consumption-based approaches: 1 - Activity-based pricing (pay per use): The default approach we've all seen, charging by tokens or compute usage. It mirrors cloud services but ultimately treats AI as a commodity. 2 - Workflow-based pricing (pay per workflow): Instead of raw usage, you price the completion of structured tasks. An AI drafting and sending an email might cost $0.10 regardless of tokens used. 3 - Outcome-based pricing (pay per result): Customers pay only when a desired outcome is delivered. Companies like Intercom and Zendesk are pioneering this with per-resolution pricing. 4 - Per-agent pricing (pay per "AI employee"): Bill an AI agent like a SaaS seat or virtual hire with a flat monthly fee. This brilliantly taps into headcount budgets, much larger pool than IT budgets (see Joanne’s “Software-as-a-Service”). The further you move from consumption-based pricing toward value-based models, the stickier your product becomes. Pricing strategy IS product strategy. Build it in early, not as a bolt-on later.

Last week I had conversations with 3 tech buyers at enterprise companies with valuations ranging from $8B to $20B. Here are the mandates that enterprise SaaS buyers have received about tech purchases in 2025: 1. Reduction in number of vendors: In 2025, Enterprises will try to reduce the number of vendors they work with. They will ask the remaining vendors to do more - this is a clear reversal of the best of breed approach. As this trend accelerates, we will see a rise in all-in-one platforms as vendors race to expand their offering. End point solutions with niche capabilities will be forced to evolve into a platform to remain relevant to enterprise clients. 2. Shrinking Budgets for SaaS: Enterprises are reducing their budgets, cutting costs and consolidating tech purchases. There is increased emphasis on ROI and heightened interest in usage or outcome based pricing. This shift is driving demand for low priced market substitutes. If this trend continues than we should expect significant disruption as cost effective solutions eat up the marketshare of premium solutions. 3. Multiple Buying Teams: We already knew that tech buying is not a single team decision and selling to one champion is not enough. In 2025, multiple buying teams will weigh in their decision to buy tech solutions. The era of single threaded sales is finally over. The number of champions will only grow and buying is about to get even more complex. 4. No Moat, No Loyalty: As software becomes easier to replicate and develop, the technology moat that many premium vendors enjoyed is rapidly eroding. Enterprises are responding with decrease in loyalty to existing solutions and are more willing than ever to switch. This shift signals a growing commoditization of software. Vendors can no longer rely on lock-ins. To stay ahead SaaS vendors will have to demonstrate pricing competitiveness and ROI. 5. Pricing: What started in 2024 as ChatGPT’s $20/user/mo experimental price is now quickly becoming the industry benchmark and the new normal. In 2025, we will see a lot of the SaaS user prices gravitate towards this new standard. This shift will be devastating for many vendors relying on high margin business and will be a major boost for companies that can operate profitably at $20/user/mo. Enterprises will only exasperate this shift with demands for reduced price. Usage or outcome based pricing will begin to disrupt several markets. 2025 will be the year when the commoditization of SaaS finally began. It will be the year we encounter and adapt to several new pricing strategies and innovation. It will be the year of transition and change for many. The ones that don’t reinvent, risk getting left behind. 

Everyone agrees usage-based pricing is the future of SaaS. But is it ACTUALLY delivering stronger performance? We dug into the 2025 Software Equity Group B2B SaaS report and layered in Monevate’s own pricing and segmentation data. Here’s what we found: 💡 Usage-based pricing is now more common than user-based (37 companies vs. 24 in the dataset). The shift is real. 📉 But the performance tells a more complicated story. Usage-based models show similar growth to user-based, but with significantly lower EBITDA margins. 🤔 However, valuation multiples for companies with each model are nearly identical. That disconnect suggests investor preference is inflating usage-based multiples beyond what fundamentals alone would justify. Does that mean usage-based pricing isn’t delivering? No—there’s a variant that is clearly a winner. 🔀 Hybrid pricing, combining elements of user-based AND usage-based models, is outperforming both. On ALL key performance metrics. ✔️ Higher growth. ✔️ Higher margins. ✔️ Higher valuation multiples. Often seen as “the best of both worlds,” hybrid pricing’s performance data suggests it might just be living up to that title. 👇  Seeing this in your own data or GTM shifts? Want the full findings? Drop a comment or DM me and I’ll send the full 10-slide deck + dataset. #SaaS #Pricing #HybridPricing #UsageBasedPricing #Valuation #SaaSGrowth #SaaSInvesting -- Hybrid pricing outperforms user- and usage-based models on growth, margin, AND valuation.

We're moving away from charging for *access* to software and toward a model of charging for the *work delivered* by a combination of software and AI agents. Let’s dive into what’s happening and what it means for you ⤵️ 1. The rise of disruptive AI pricing models Tech companies are realizing they can't solely rely on seat-based subscriptions in an age of AI, automation and APIs where value is disconnected with how many people are logging in. Perhaps Salesforce going all-in on Agentforce (and charging $2 per conversation) was the push the industry needed. Each product category has its own flavor of disruptive pricing. - Legal AI products might charge for a demand package generated by AI or an AI-generated summary. - Creator AI products might charge for the content that gets produced such as a video generation or amount of video created. - GTM products might charge for specific tasks completed or workflows executed by the AI. 2. Selling work, not necessarily success As a customer, I wish I only had to pay for software when it delivered results. But the reality is that true success-based billing won’t work for the vast majority of today’s products. Most products should charge for work output instead. The issue is attribution. You want the customer to get a fantastic outcome — and you want them to recognize that your product powered that outcome. As soon as you start charging for success, the customer begins to rethink the results. 3. Goodbye ARR as we know it? Shifting to these newer value-based pricing models isn't a simple pricing change you can just announce in a press release. It's a business model evolution that looks a lot like the shift from on-prem to SaaS in the first place. These new AI pricing models might mean greater volatility in both usage and spend. Variable margin profiles across products and customers. Seasonal revenue fluctuations. The potential for project-based, non-recurring use cases. Put simply, annual recurring revenue (ARR) continues to get dethroned. — Full post in today’s Growth Unhinged newsletter: https://lnkd.in/ea5eTrVD Things are about to get interesting 🍿 #ai #pricing #saas

"How should you monetize AI?" NEW data from Kyle Poyar for you PMMs: Kyle just published a new essay "Tremont | Growth Unhinged State of B2B Monetization report" with data from more than 240 software companies. Six takeaways for you: "1. Seats & flat-rate pricing are increasingly under threat. The rise of AI, and AI agents in particular, means value gets decoupled from customers needing to buy more seats. And the costs of delivering AI means software companies need a mechanism to protect themselves if & when AI usage spikes. 2. As AI continues to gain traction, hybrid has become the ‘it’ pricing model. Seats and flat-rate pricing are being replaced by hybrid pricing, i.e. combinations of subscriptions and usage. Hybrid pricing is up from 27% to 41% adoption (!) in the last 12 months. Software and AI are becoming inseparable. More than half of survey respondents said they include AI capabilities as part of their core software product offering. 3. There are a seemingly infinite number of ways to structure hybrid pricing. Choose wisely (or support multiple models). Software founders used to tell me their pricing was inspired by Salesforce or maybe Slack. Now they tell me they were inspired by Clay. Clay's hybrid model has multiple routes to expand customers while keeping pricing (relatively) simple: more features (subscription packages) and more usage (credits). 4. Outcome-based pricing is seen as the 'holy grail'. It's still out of reach for 95% of the market. A mere 5% said their pricing model is outcome-based right now. But 25% said they expect to have outcome-based pricing by 2028. 5. The shift toward pricing transparency seemed inevitable. This isn’t playing out. My two cents: many software companies, especially early-stage and AI companies, don't have pricing totally figured out. And as soon as they publish pricing, it gets way harder to adjust. 6. Pricing models keep evolving. Most of the market is unprepared to keep up. Be careful to avoid pricing ‘no-man’s land’ -- this happens between $5-20M ARR when ownership often falls through the cracks." -- 👋 P.S. What's your take PMMs? Pricing isn’t just about revenue — it’s about positioning. Learn how top PMMs lead pricing strategy inside Product Marketing Alliance >> https://lnkd.in/ewN_pgWY

My latest in today's print edition of The Wall Street Journal: No One Knows How to Price AI Tools. With businesses unwilling to drop top dollar on unproven AI tools, AI software vendors are getting creative on new strategies to convince them to buy. ‘It’s the wild west,’ said one CTO. More than two years after the public debut of ChatGPT, software companies still haven’t found a compelling way of charging for AI tools, CIOs say. Now they’re trying new strategies. In the last couple years, vendors have typically charged a monthly fee per user for AI features, assistants and copilots, much like they price other software as a service. But AI’s high compute demands meant they needed to charge eyebrow-raising prices to cover the cost of delivering the service. For example, some chief information officers balked at paying $30 per user per month to add Microsoft’s AI Copilot to its 365 productivity suite, a 60% premium to the top level of 365 without AI. “A year ago everything was way overpriced,” said Greg Meyers, chief digital and technology officer of Bristol Myers Squibb. “Most companies overestimated how much more we would be willing to pay for an AI feature.” The emergence of models like DeepSeek AI’s R1, which the Chinese company said it trained for a fraction of the cost of leading U.S. models, could help drive AI costs down over time. But in the meantime, CIOs remain in a tough spot. “We’re in a place where prices are high and simultaneously companies are trying to understand how to drive value out of it,” said United Airlines chief information officer Jason Birnbaum. When it comes to general-purpose tools like Copilot that are charged on a per seat basis, Birnbaum added, “We’re not really ready to deploy it on a broad basis.” Now vendors like Microsoft, Google and Salesforce are making changes to how they price in an attempt to gain more users and more adoption. What are your thoughts? Do you think these tools are worth the super high prices? Read the full story here for more from Principal Financial Group CIO Kathy Kay, Nationwide CTO Jim Fowler, New York Life chief data and analytics officer Don Vu, Microsoft's chief marketing officer of AI at Work, Jared Spataro, and Salesforce EVP of Corporate Strategy Bill Patterson: https://lnkd.in/ei7aJdDc

The era of per-seat software pricing is rapidly fading. We are witnessing a major shift as AI forces vendors to evolve beyond simple user counts toward models that actually make sense. Here is how the pricing landscape is transforming: - From Seats to Usage: Vendors are now measuring capacity, tokens, and data volume rather than just logins. - The Value Pivot: We are moving toward pricing based on business impact, like actual cost savings or efficiency gains. - Outcome-Based Models: You pay for the result achieved, not just the tools used to get there. This shift finally aligns the vendor’s success directly with yours, which is a massive win for everyone involved. How has your company adjusted its software budget to keep up with these new AI-driven pricing models? #ArtificialIntelligence #AgenticAI #IntelligenceBriefing

Services-as-Software is breaking old services pricing because enterprise buyers aren’t rational, they’re human. Tony Filippone shares key insights into the emerging pricing for SaS models: ➡️ Kill the anchors: Decades of FTE/hourly habits lock buyers to the past. Set outcome anchors from the start (“risk reduced,” “contracts successfully reviewed per week”). ➡️ Make it feel fair: Share AI efficiency gains transparently. Price to shared value and quality, not opportunistic margin grabs. ➡️ Remove the taximeter pain: Hourly and per-transaction fees feel punitive, especially when AI is doing the work. Shift to fixed/subscription so cost is predictable and “pain-free.” ➡️ De-risk the bet: Executives fear losses more than they value equivalent gains. Use minimum fee + performance guarantees (“no success, no fee”) to accelerate adoption. ➡️ Bottom line: Anchor on outcomes, prove fairness, decouple price from consumption, and de-risk with guarantees. That’s how you win trust... and the Services-as-Software era. HFS Research Saurabh Gupta Ian Maher Nigel Edwards #ServicesAsSoftware #Pricing #AI #Behavioraleconomics #GBS #GCC #HFSResearch #pricing #innovation #agentic

No one has been able to crack AI pricing yet. Here's what's happening & why you should care👇 Today, every software company is investing heavily in AI and reinventing products completely. But AI products are not like traditional SaaS. They incur costs every time customers use them. That makes pricing one of the most important strategic decisions here. And so far, nobody has figured it out. Four examples that prove it: 1. Salesforce changed Agentforce pricing 3x in 1.5 years. 2. Microsoft introduced consumption-based pricing with Copilot Chat. 3. Cursor shifted Bugbot from monthly $40/seat to usage-based pricing at $1–1.50 per run. Companies are continuing to experiment with different pricing to find the best match. The way I see it, three models are taking shape: • Per seat: A fixed fee regardless of usage. • Usage/credit based: Pay as per consumption. • Outcome-based: Pay only when AI produces results. Everyone wants outcome-based pricing. It aligns perfectly with how customers think about value. The challenge is that most AI platforms aren't reliable enough to guarantee results yet. My guess: the industry ends up in a hybrid setup. Something fixed, something variable, depending on what actually gets used. What do you think? --- Today, I run these 2 private communities that might help you: → SaasRise: for founders scaling from $1M to $100M → GrowthRise: for B2B Sales and Marketing leaders Also see our upcoming AI coding bootcamp (link in comments).