Business Pricing Models

Every time a card payment is processed, 𝘁𝗵𝗿𝗲𝗲 main types of fees are involved. Here’s a simple breakdown of the Three Core Fees: 1️⃣ Interchange Fee This is paid by your acquiring bank (or payment processor) to the cardholder’s bank (the issuer). It’s set by the card networks (like Visa and Mastercard; sometimes regulated), and is designed to cover things like fraud, credit losses, and infrastructure costs. 2️⃣ Scheme Fee Charged by the card networks themselves, this fee covers the operation of the payment system (“rails” that process the transaction). 3️⃣ Acquirer Markup This is the fee your acquirer or payment service provider (PSP) charges you, the merchant. It includes their costs, risk management, and profit margin for processing and settling the payment. The total cost a merchant pays is called the Merchant Service Charge, which is the sum of these three components. The Main Pricing Models: ► Bundled Pricing All fees are grouped into one flat rate. This is very common with small businesses. It’s easy to understand but doesn’t provide insight into what you’re actually paying for. ► Interchange+ The interchange fee and the acquirer’s fee are shown separately, but the scheme fee is typically bundled with the markup. This model offers some transparency. ► Interchange++ Each fee—the interchange, scheme, and acquirer markup—is itemized separately. This is the most transparent model and is favored by larger or multi-country merchants who want to track costs precisely. Who Chooses the Pricing Model? Most acquirers and PSPs decide what pricing model you’re offered. Unless you negotiate or have significant transaction volume, you’re likely to get bundled pricing by default. Larger or more experienced merchants who understand payments often push for Interchange++ for its clarity and fairness. Smaller merchants often aren’t aware that alternatives exist or find it difficult to compare offers. How Interchange Fees Vary Globally: Some regions (like the EU, UK, China, and Brazil) cap interchange fees to lower costs for merchants and stimulate competition. The US regulates only part of the system—such as capping debit card fees for large banks (the Durbin Amendment)—while credit card interchange remains uncapped and usually higher. Other countries, like India and Brazil, regulate interchange as part of broader financial inclusion goals. In markets with stricter regulation, merchants often benefit from lower, more predictable fees, making it easier to accept cards. Where fees are higher and less regulated, issuers can offer consumers more rewards (like cashback), but those costs are passed back to merchants—and sometimes their customers. Every model shifts the balance of costs and benefits between banks, merchants, and consumers in different ways. More info below👇, and I highly recommend reading my complete deep dive article about Interchange Fee and what factors impact the rate: https://bit.ly/44T4VJA

Every card payment involves three core fees - yet most merchants don’t know where their money goes. Here is a break-down. 𝗧𝗵𝗲 𝟯 𝗳𝗲𝗲 𝘁𝘆𝗽𝗲𝘀: 1. Interchange – Paid from the acquirer to the issuer (the cardholder’s bank). Set by card networks, often regulated, and meant to cover fraud, credit risk, and infrastructure. 2. Scheme Fee – Charged by the card networks (Visa, Mastercard, etc.) for operating the rails. 3. Acquirer Markup – What the acquiring bank or PSP charges the merchant to process the transaction, handle risk, and settle funds. Together, these form the Merchant Service Charge. 𝗧𝗵𝗲 𝟯 𝗽𝗿𝗶𝗰𝗶𝗻𝗴 𝗺𝗼𝗱𝗲𝗹𝘀: 1. Bundled: All three fees are merged into one opaque rate. Common among smaller merchants. Simple, but lacks visibility. 2. Interchange+: Interchange and acquirer fee shown; scheme fee included in the markup. Partial transparency. 3. Interchange++: All three fees itemized. Full transparency. Preferred by larger or multi-market merchants. 𝗪𝗵𝗼 𝗱𝗲𝗰𝗶𝗱𝗲𝘀 𝘁𝗵𝗲 𝗺𝗼𝗱𝗲𝗹? - The acquirer or PSP typically offers the pricing model, and unless a merchant has the volume or experience to negotiate, they’re often placed on bundled pricing by default. - Larger merchants or platforms - who understand the mechanics and can estimate true costs - usually push for Interchange++ for its transparency and fairness. - Smaller businesses rarely ask, either because they don’t know the models exist, can’t easily compare offers, or assume it’s not worth the effort. 𝗜𝗻𝘁𝗲𝗿𝗰𝗵𝗮𝗻𝗴𝗲 𝗳𝗲𝗲𝘀' 𝗰𝗼𝗺𝗽𝗮𝗿𝗶𝘀𝗼𝗻: Some jurisdictions cap interchange fees (EU, UK, China, Brazil) to reduce merchant costs and promote competition. Others (US) regulate only parts of the system - e.g., debit under Durbin for large banks - while leaving credit cards uncapped. Why? It’s a mix of politics, lobbying, market structure, and regulatory philosophy: - In Europe, regulators treat interchange as  as insufficiently competitive and have imposed caps to bring more balance and transparency. - In the US, the market relies more on competition, resulting in higher fees. - Emerging markets like India and Brazil regulate interchange as part of broader financial inclusion efforts. - In regulated markets, lower and more predictable fees help merchants manage costs and often support broader payment acceptance. In unregulated markets, higher interchange allows issuers to fund consumer perks like cashback and rewards - but merchants may face higher costs, which can influence pricing or acceptance choices. Each model shifts value differently across the ecosystem, affecting how costs and benefits are distributed between banks, merchants, and consumers. What's your experience? Opinions: my own, Graphic sources: Paypr.work [ˈpeɪpəwəːk], Truevo, Panagiotis Kriaris 𝐒𝐮𝐛𝐬𝐜𝐫𝐢𝐛𝐞 𝐭𝐨 𝐦𝐲 𝐧𝐞𝐰𝐬𝐥𝐞𝐭𝐭𝐞𝐫: https://lnkd.in/dkqhnxdg

The recent interest in hybrid, usage-based and outcome-based pricing is on 🔥. Here's the thing: successfully going usage-based is way more than a pricing change. It's a hard pivot, and you might not be ready for it. What to look out for: 1. Pure usage-based or pay-as-you-go pricing really isn't for every product. The challenge is finding a metric that buyers accept (the feeling of predictability is key) & that makes more $$. Look for metrics that grow quickly within an account, aren't susceptible to huge swings, and that are *outputs* of getting value rather than *inputs*. Or consider a workaround like putting a usage limit on a subscription plan or adding a fair usage policy to protect against heavy users. 2. In a usage-based business, there's no room for shelfware. The hard work *starts* at contract close. Everyday the customer is making a purchase decision about whether to adopt your product. This means everyone plays a role in customer success. 3. Sales incentives need to evolve to embrace land-and-expand. It's better to close deals quickly, then let usage grow over time. Commission structures can't over-index on the initial commitment. 4. Overage isn't a bad thing to penalize. Your customer grew their business and wants to consume more of your product. That's fantastic, celebrate it! 5. There are ways to make usage models more palatable to the enterprise. This usually means getting into the weeds with contract structures like:  - Annual draw-down: Customers flexibly draw down their usage over 12 months like a gift card. If they use the product faster than expected, they have time to plan & budget before renewal.  - Roll-over: Give customers the option of rolling over unused usage credits *if the next commit is larger than the last*. This helps reduce hoarding.  - Grace periods: After the grace period, customers can either re-up their contract at a higher commit or pay for the one-time flex spend. 6. Usage-based revenue isn't necessarily ARR. But that doesn't necessarily mean it's de-valued by investors. Folks want to see that usage revenue *acts* like ARR -- that it's highly re-occurring, grows over time in the average account, isn't project-based, and has high gross margin. 7. Forecasting your business is about to get way more complicated. It becomes a data science exercise more than a pipeline exercise. Finance teams are building models looking at individual customers & cohorts, factoring in criteria like the use case, ramp time, commitment, etc. What could go wrong 🙃 --- Adopting usage-based models isn't easy. But there aren't many better alternatives for AI, automation, API and FinTech products.

𝗦𝗲𝗮𝘁 𝗽𝗿𝗶𝗰𝗶𝗻𝗴 𝗵𝗶𝗱𝗲𝘀 𝘄𝗮𝘀𝘁𝗲. 𝗧𝗼𝗸𝗲𝗻 𝗽𝗿𝗶𝗰𝗶𝗻𝗴 𝗵𝗶𝗱𝗲𝘀 𝗿𝗶𝘀𝗸. 𝗢𝘂𝘁𝗰𝗼𝗺𝗲 𝗽𝗿𝗶𝗰𝗶𝗻𝗴 𝗵𝗶𝗱𝗲𝘀 𝗰𝗼𝗺𝗽𝗹𝗲𝘅𝗶𝘁𝘆. And that’s why most teams pick the wrong model, not because the math is hard, but because the trade-offs are invisible. ➮ 𝗦𝗲𝗮𝘁-𝗕𝗮𝘀𝗲𝗱 𝗣𝗿𝗶𝗰𝗶𝗻𝗴 (𝗨𝘀𝗲𝗿 / 𝗟𝗶𝗰𝗲𝗻𝘀𝗲 𝗠𝗼𝗱𝗲𝗹) · You pay per user or per agent, no matter how much they use it. · Great for predictable teams and stable workflows, but it breaks when licenses sit unused or adoption depends on humans showing up. ➮ 𝗧𝗼𝗸𝗲𝗻 / 𝗖𝗼𝗻𝘀𝘂𝗺𝗽𝘁𝗶𝗼𝗻 𝗣𝗿𝗶𝗰𝗶𝗻𝗴 (𝗣𝗮𝘆-𝗣𝗲𝗿-𝗨𝘀𝗲) · You pay only for what the system consumes - tokens, executions, inference calls. · Perfect for experimentation and scaling AI workloads, but risky when prompts get inefficient or usage becomes unpredictable. ➮ 𝗢𝘂𝘁𝗰𝗼𝗺𝗲-𝗕𝗮𝘀𝗲𝗱 𝗣𝗿𝗶𝗰𝗶𝗻𝗴 (𝗣𝗮𝘆-𝗳𝗼𝗿-𝗩𝗮𝗹𝘂𝗲) · You pay only when the AI delivers a measurable business outcome. · Ideal for ROI-driven teams, automation cases, and exec-level reporting - but hard when outcomes aren’t clearly defined. ➮ 𝗛𝗶𝗱𝗱𝗲𝗻 𝗧𝗿𝗮𝗽𝘀 𝘁𝗼 𝗪𝗮𝘁𝗰𝗵 𝗙𝗼𝗿 ‣ 𝗦𝗲𝗮𝘁 𝗧𝗿𝗮𝗽: Paying for licenses people never use. ‣ 𝗧𝗼𝗸𝗲𝗻 𝗧𝗿𝗮𝗽: Budget spikes from inefficient prompts or runaway execution. ‣ 𝗢𝘂𝘁𝗰𝗼𝗺𝗲 𝗧𝗿𝗮𝗽: Misalignment on what counts as a successful outcome. ➮ 𝗪𝗵𝗲𝗻 𝗘𝗮𝗰𝗵 𝗠𝗼𝗱𝗲𝗹 𝗪𝗶𝗻𝘀 ‣ 𝗦𝗲𝗮𝘁 𝘄𝗶𝗻𝘀 𝘄𝗵𝗲𝗻: Adoption is stable and usage doesn’t swing wildly. ‣ 𝗧𝗼𝗸𝗲𝗻 𝘄𝗶𝗻𝘀 𝘄𝗵𝗲𝗻: You’re early in the journey, workloads are variable, and cost must track usage. ‣ 𝗢𝘂𝘁𝗰𝗼𝗺𝗲 𝘄𝗶𝗻𝘀 𝘄𝗵𝗲𝗻: Automation is clear, value is measurable, and leadership needs ROI proof. Pricing isn’t a finance decision, it’s a workflow decision. Pick the model that matches how your teams actually work, not how you wish they worked. Follow Vaibhav Aggarwal For More Such AI Insights!!

AI Agents are killing traditional SaaS - and that's Good News The $3 trillion SaaS industry is about to experience its biggest disruption since cloud computing. The catalyst? AI agents - and they're completely breaking the traditional per-seat pricing model that's dominated enterprise software for decades. Here's why this matters: Per-seat pricing only works when your users are human. As AI agents increasingly become the primary users of enterprise software, the entire model collapses. You can't charge an agent for a seat. But this isn't just about pricing - it's about a fundamental shift in how businesses evaluate technology investments. CFOs aren't comparing software costs against other software anymore. They're measuring the combined costs of software licenses plus human labor against pure outcome-based solutions. Think about it: - Customer support: Per resolved ticket vs. per agent + seat - Marketing: Per campaign outcome vs. headcount - Sales: Per qualified lead vs. rep costs The smart players are already adapting. Intercom's AI agent Fin charges $0.99 per resolved conversation. Salesforce's Marc Benioff sees this "Digital Labor" expanding their market into the trillions. Even traditional vendors are scrambling to adjust. The winning strategy? Give the platform away free? Let AI agents handle workflows through existing systems. Once you control the data flows, you become the new system of record. While incumbents defend their subscription revenue, newcomers can capture the entire value chain. Yes, enterprises still prefer predictable costs over usage-based pricing. But when individual leaders see 10x efficiency gains, they'll find ways around traditional procurement processes. This isn't just another wave of enterprise software. It's a generational reset in how businesses operate. Zero upfront costs, pure outcome-based pricing - that's not just a pricing model. That's the future of business. The winners will be those who recognize this isn't about squeezing more margin from the old model. It's about completely reimagining how enterprise software creates and captures value in an AI-first world. The question isn't whether this transformation happens - it's whether you'll be leading it or playing catch-up. #SaaS #AI #FutureOfWork #Enterprise #Innovation #Technology #DigitalTransformation

AI companies underwent multiple rapid pricing iterations to find the optimal monetization model that balances value, growth potential, and cost. Here is a summary of this journey: 💲 Pay-As-You-Go Pricing The purest form of usage-based pricing mirrors how we pay for essentials like gas, water, and electricity. What does this pricing model solve? - Enables organic account growth - Covers vendor costs (if bills are paid) - Works well with Product-Led Growth (PLG) and self-service models Why is this pricing model challenging? - No upper limit on cost liability for customers - High vendor upfront costs since usage is billed in arrears - Lack of long-term customer commitment - Revenue is affected by seasonality - Customers struggle to predict their bills To enable upfront revenue, enterprises typically charge for annual pre-purchased commitments in advance and provide discounts in return. 💲 Credit-Based Pricing Credit-based pricing is the self-service version of pre-purchased commitments. Customers can purchase credits on demand. What does this pricing model solve? - Covers vendor upfront costs - Facilitates organic account growth - Aligns with PLG and self-service approaches - Establishes hard spending limits for customers Why is this pricing model challenging? - Running out of credits can cause outages - Customers often struggle to forecast usage accurately 💲 Recurring Prices With Usage-Based Components Usage-based and credit-based pricing are often combined with seat-based or recurring prices to ensure baseline revenue. What does this pricing model solve? - Guarantees a baseline revenue stream for vendors - Works well with PLG and self-service models Why is this pricing model challenging? - Seasonal customers may end up with unused credits - Running out of credits mid-cycle can cause service disruptions 💲 Progressive Billing Vendors set invoicing thresholds, and customers are billed as soon as these limits are reached. What does this pricing model solve? - Encourages organic account growth - Keeps vendor upfront costs low - Works effectively with both PLG and PLS approaches Why is this pricing model challenging? - Limited customer commitment - Seasonality and trends impact revenue - Customers face difficulty predicting their costs 💲 Success-Based Pricing Most AI companies charge for work rather than outcomes. Success-based pricing flips this approach, aligning costs with value. What does this pricing model solve? - Aligns price with delivered value - Supports organic account growth - Works well with PLG and self-service models - Simplifies cost forecasting by tying it to business outcomes Why is this pricing model challenging? - Defining and measuring success can be complex and subjective What's Next? Current AI pricing models favor vendors, leaving customers with limited control over cost. As customers seek stability and value-aligned pricing, we can expect more innovative monetization models to emerge.

I've reviewed 100+ payment processor contracts in the last year. Most founders are getting quietly robbed by "simple" pricing. Here's what they're hiding: Blended Pricing Is a Shell Game Stripe charges you 2.9% + $0.30 flat. Sounds simple. But it hides where your money actually goes. Here's the actual breakdown: 1. IC = Interchange (The Unavoidable Tax) This goes directly to the card-issuing bank. Visa sets it. Mastercard sets it. You can't negotiate it. 2. IC+ = Interchange + Scheme Fees Now you're also paying the card networks (Visa/Mastercard). Cross-border fees. Assessment fees. Network access fees. Brand usage fees. Can easily add ~0.15% on top of interchange. 3. IC++ = The Real Cost Structure Interchange + Scheme Fees + Processor Margin. This is how sophisticated businesses pay. Processors love Blended Pricing because they make more when you use expensive cards. If 60% of your customers use US debit (1.2% IC), but you're paying 2.9% flat, they pocket 1.7%. Understanding this breakdown allows businesses to know exactly where their money is going and make a change. What fees are you paying?

Seat-based pricing is slowly dying... but was THE pricing strategy of the past 10 years. It made sense: (1) Customers always grew their teams, so their software spend grew too. (2) Collaboration was the core value driver, and more seats meant more collaboration. (3) SaaS margins were high, so unlimited usage was viable. But that model is breaking down. Teams aren’t growing like they used to. Some are shrinking. AI features come with real costs—every query has a price tag. Subscription fatigue is real, and companies are scrutinizing every dollar. That’s why usage-based and hybrid pricing models are taking over. We’re seeing: -Credits (prepaid usage that depletes over time) -Subscription + overages (pay a base fee, plus per-unit costs) -Outcome-based pricing (pay per successful result, not per seat) Many companies are shifting to a more usage-based and less seat-based model (even if payment still happens as a subscription). The challenge? The most common billing systems weren’t built for this level of flexibility. Every company measures usage differently, which makes implementing new pricing hard. That’s why we’re building Lago—to make modern pricing models easier to implement, so you’re never stuck in a legacy billing system that slows you down. If you want to read our full breakdown, check out our latest Substack post here: https://lnkd.in/e3VZ6FdE

The Dirty Little Secret Behind Gen AI Functionality Pricing... Vendors are quietly abandoning per-seat or per-module licensing. And they're hoping you won't notice until it's too late.... Here's what's really happening: Gen AI burns through "compute" like nothing you've seen before. That "simple" chatbot query? Could cost pennies... Or dollars! Depends on the model, complexity, and how many times Chat GPT, Claude, Gemini or Copilot is called behind the scenes... Traditional "per-user" pricing would mean capped $ per seat for heavy AI users... So vendors are pivoting to "outcome-based pricing" to hide the true costs. The shift happening right now: Old Model (being killed quietly): → Fixed cost per user/month regardless of usage → Predictable budgets → Vendors eat the variable costs New Model (being pushed hard): → "Pay for results achieved" → Costs scale with your "success" → You absorb all the usage risk Sounds customer-friendly, right? Here's the dirty secret: Most vendors proposing "outcome-based pricing" haven't figured out how their AI usage actually improves your bottom-line... They're essentially asking for "usage-based pricing" for those Gen AI functionalities that look so cool! The questions you should be asking: → Which specific AI models are you using? → What's your cost per API call? → Can we switch to cheaper models for basic tasks? → Do you have a non-Gen AI version of this process? → What happens when OpenAI/Anthropic raises prices? How to protect yourself? SHOULD COST ANALYSIS! → Demand full transparency on underlying AI costs → Negotiate caps based on your actual usage patterns → Include model substitution rights in contracts → Define "outcomes" in measurable business terms, not AI metrics This is the same as working out the costs of your raw materials... The bottom line: Outcome-based pricing CAN work. But only when both parties understand the true economics. Unfortunately, most businesses are not ready for "outcome-based pricing". It will just be a fancy word for "pay per use..." So, don't infuse Gen AI in a process unless the ROI is clear! Or the invoice will be a nasty surprise... Have you been approached with "AI outcome-based pricing" lately? What questions did you ask? Let me know in the comments 👇 ______________________ P.S. Next Thursday @ 9:45am ET, I'm exposing more of these AI pricing tricks on a webinar with Michael Keller from Vertice. We'll cover the contract clauses vendors use to shift risk, how to spot AI-washing in pricing models, and the questions that make vendors squirm. Sign up here: https://lnkd.in/eujmPpzh

Seat-Based Pricing is Dead. Here’s Why: Seat-based pricing had its moment, but it’s a relic in the age of intelligent agents. Why should businesses pay for "seats" when the work isn’t tied to how many people log in but to the outcomes they deliver? The old model is rigid, outdated, and disconnected from what really drives value. A study by Gartner indicates that 70% of businesses prefer usage-based pricing over per-seat pricing for SaaS applications. This preference stems from the flexibility and cost-effectiveness that usage-based models offer, aligning expenses more closely with actual consumption and value derived. At SuperAGI, we’ve ditched the deadweight. Our pricing isn’t about how many users you have; it’s about what your agents do. It’s built on outcomes and agent actions—because that’s where the real ROI lives. Every action an agent takes, every task completed, every dollar of value created—that’s the foundation of our model. Outcome-driven pricing models have been shown to reduce operational wastage by 15–20% annually, ensuring that businesses pay for value, not headcount. Also automated systems managed through outcome-driven models just like ones at SuperAGI have been shown to achieve 40% faster task completion rates compared to seat-based systems dependent on user logins. But we get it: businesses still need predictability. So, we tier it out. Structured pricing gives you clarity and control without sacrificing flexibility. 👉 Pay for What Matters: Pricing tied to actual agent activity and outcomes. No fluff, no wasted dollars. 👉 Predictable Tiers: Simple, transparent plans that scale with your needs. Budget-friendly without sacrificing performance. 👉 Aligned Incentives: When our agents deliver results, you win—and so do we. That’s how pricing should work. Seat-based pricing is for the past. With a significant shift towards usage-based models, SuperAGI’s outcome-driven approach is how companies will scale into the future. It’s smarter, fairer, and built for where work is headed—not where it’s been. ( All research quoted is in comments )