“So every single definition of an outcome or work changes per customer. You need a flexible platform to do that.”
Pricing & packaging
Where they agree
-
AI vendors have to translate usage and credit bills into concrete value or ROI, or buyers will focus on minimising spend.
4 independent voices · 2 shows4 new this month
On [Un]Churned, Kellie Woodin said Notion uses a calculator setting about 10 hours a week saved by an email agent against credits costing under $5 a day.
6 sources
Tokens should never be the unit agent builders charge on, because they are an internal measure that means nothing to the buyer. Listen
Manny says tokens vary by lab and are an internal measure of how LLMs are built. A host noted that two models can do the same task using different numbers of tokens, which Manny agreed with. He says agent builders, unlike the labs, have to show a measure of the value delivered to the customer.
“A token should not be a unit of value for charging because a token is really kind of like the inside secret.”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
Manny Medina describes a value ladder for agent billing: transparency first, then explaining the value of each piece of work, then customer-specific ROI. Listen
Step one is letting the buyer and their finance team see what the agent did, described in normal terms, like the old itemized phone bill where you went straight to the biggest line to check it. Step two is explaining the value, for example that a piece of research would have taken a human a long time, or that the agent produced a PowerPoint or an analysis. ROI comes last and depends on each customer's own equation. He says agents he works with are often failing at the first rung, and that once work is visible a buyer can question how artifacts were used, but cannot dispute that the work was done.
“So explainability is like the first rung in the ladder.”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
SaaS buyers never seriously asked what value seats delivered, and that the onus is now on agent builders to answer that question. Listen
Manny argues that seats felt so intuitive that nobody asked what 100 seats actually bought, and vendors answered with usage charts, which he dismisses. Buyers are now asking value questions of agents, which he considers proper. He says agent builders have to show buyers what they get for the agent.
“And the first chart that everyone wanted to show up is usage. And who gives a fuck about usage? Like you want value.”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
Consumption pricing puts 'good pressure' on CS to prove value, and Notion answers it with a calculator setting credit cost against hours saved. Listen
Kellie Woodin said product usage data doesn't tell the full story, so CS has to understand the actual time saved. Notion's internal 'custom agent hall of fame' includes a small calculator for what credits are worth. Her example takes hours an agent saves (about 10 a week for her email agent) times an hourly salary rate and compares that with credits that cost under $5 a day. Customers come to Notion for guidance on these calculations across their LLM and Notion credit usage, which she said positions CS as strategic.
“we've been able to include a small calculator of how to understand what the credits are worth.”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
AI vendors must build the ROI case for each rep, because otherwise buyers default to minimizing every AI bill. Listen
She said customers are anxious about AI bills and have started asking how to lock down credits rather than what value they receive for them. She suggested vendors should show how the bill maps to the value of the work done, and she argued that customers should consider the budget per rep. Mutiny focuses on enterprise sales because she sees the clearest ROI there.
“And so I do think it's important for companies like us to make our own ROI case and make it really clear, how should a customer think about the budget allocation for every single rep?”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
Slevin warns that companies rushing into usage-based pricing can become addicted to the spike in net retention it creates. Listen
He said this model is not new and that many companies have used it. When a host compared it with buying gas, he replied that with gas the buyer knows exactly what they are getting and can see a meter. He said usage pricing needs clear value, or customers get surprise top-up notifications and friction.
“And so I think that people rushing into consumption based pricing or usage based pricing, this isn't new. Like it's been around for, and there's tons of companies that have done this and they get addicted to this like spike in net retention.”
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-
Outcome-based pricing is the right model for AI products because it ties what the vendor earns to the value the customer gets.
5 independent voices · 4 shows2 new this month
On Grit, Bret Taylor said Sierra uses outcomes-based pricing and a forward-deployed agent development team because it wants to be accountable for whether deployments succeed.
5 sources
Paid charges customers a take rate on their revenue for the life of the contract instead of a software fee. Listen
Manny says customers have been open to the model. A host called it the cleanest form of outcome-based pricing, and Manny summed it up as 'you grow, I grow'. He later said a take-rate model is one reason he isn't worried about investor questions on growth.
“We take a percentage of revenue, so we always take a take rate.”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
Gainsight Atlas charges for a managed renewal outcome rather than for software, combining AI agents and human renewal managers to run a client's renewal book. Listen
Grant Clarke describes Atlas as an operational framework that combines an AI agent with a renewal rep to manage a renewal book on the client's behalf. The client pays for the outcome, not for the product or the software. Josh Schachter summarizes it as 'give us the keys,' with Atlas acting as the client's renewal managers and Grant calling it an extension of the client's team.
“It does that in a way that we are delivering an outcome so the company pays for the outcome not for the product not for the software.”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
Sierra uses outcomes-based pricing and a forward-deployed agent development team because it wants to be accountable for deployment outcomes. Listen
Bret Taylor said the hard part of AI is deploying it successfully, which is partly human and partly technical, so Sierra wants to be accountable for the outcome. He said some clients want to do it themselves, while others need co-innovation, which he described as Sierra's sweet spot. He said the forward-deployed team is called agent development.
“It's why we have outcomes based pricing.”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
Crescendo charges based on outcomes rather than seats and does not charge customers who are not happy. Listen
Michelle described the model as charging customers based on outcomes, not seats, with no charge if the customer is not happy. She said the company is not focused on profitability right now even though it is profitable, and is going for a market share grab to win customers who want to grow with it.
“We're gonna charge you based on outcomes, not based on seats. If you're not happy, we're not gonna charge you.”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
Outcome-based pricing aligns go-to-market and FDE teams around resolutions and customer outcomes, Diego said. Listen
Diego said Intercom charges for outcomes rather than conversations or seats. He said comp plans, performance reviews and incentives for go-to-market and FDE teams are tied to resolutions and customer outcomes, and that Fin's ARR is related to how much work is done for customers.
“from comp plans to performance reviews to all the incentives that we built around all of our like go to market teams”
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-
Per-seat pricing is going away and is being replaced by platform fees plus usage or outcome charges.
3 independent voices · 2 shows1 new this month
On [Un]Churned, Ghazi Masood said Replit moved enterprise pricing from seats to a platform fee plus credits prebought for 12 months that anyone in the company can consume.
3 sources
Ann suggests bundling enterprise data access with a usage component, such as roughly 40 cents per query, because companies rarely buy enterprise licences priced on headcount. Listen
Ann says companies will not buy enterprise licences for software by reference to headcount, such as 500,000 or 200,000 employees. Her proposed alternative is a bundled price with a usage fee layered on top, for example paying 40 cents a query through an MCP.
“Companies will never buy enterprise licenses to anything normally because I've got 500 ,000 employees or I've got 200 ,000 employees.”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
The per-seat SaaS pricing model is dying and will go away, but he does not think SaaS itself is dead. Listen
He expects the enduring value of software to remain in regulated industries, using pharmaceuticals as an example, where he does not think companies will vibe code their software. For large mission-critical SaaS companies, he says survival depends on how well they shift what they deliver toward outcomes.
“The per-seat pricing model is dying and will go away.”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
Replit has moved enterprise pricing from seats to a platform fee plus credits that customers prebuy for 12 months and that anyone in the company can consume. Listen
Ghazi says the enterprise side was seat-based and is now evolving to a usage-based model. The platform fee depends on customer size and a small team starts with a smaller credit pool, while more teams committing means more credits. He says the model is easy to roll out and puts no handcuffs on who can use the product.
“you pre buy basically credits that you think you would need for the next 12 months”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
-
A cheap entry plan should be used to acquire users, with the real money made by upgrading them to much larger plans.
3 independent voices · 2 shows2 new this month
On Topline, Keith Peiris said Lightfield uses its low-cost PLG plan for lead generation and upgrades customers from $2K a year to $24K a year once they hit product-market fit.
6 sources
Mashrabov expects OpenAI and Google to demolish the $20/month prosumer subscription market, so Higgsfield focuses on upgrading users to over $1,000 a year. Listen
He calls this a contrarian bet and says horizontal products will absorb many verticalized $20-30/month tools; he agrees that much low-end consumer design work Canva served can now be done in OpenAI. He says Higgsfield will never win at $20 a month. Its priority is showing value fast enough to move a $20 subscriber to spending more than $1,000 a year.
“How can we make them to upgrade to over, to spend over $1 ,000 a year with us?”
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Lightfield uses its low-cost PLG plan as a lead-generation tool and upgrades customers from a $2K/year plan to a $24K/year plan once they hit product-market fit. Listen
Keith said pre-PMF companies need a simple system that collects everything, and they need 'something real' once they find PMF. Lightfield moves quite a few customers from the $2K plan to the $24K plan at that point. He describes the current ideal customer as having about 10 reps and growing toward 30, rather than companies still searching for product-market fit.
“we actually move quite a few people off of our like... 2k per year plan to the 24k one as soon as they hit PMF.”
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Model companies subsidize individual usage heavily and then charge companies much more to reinvent their processes, which Tunguz says earns far more margin. Listen
Tunguz said there are heavy subsidies today because the company is educating users to bring AI to work. He said model companies charge a company a whole lot more than they can charge individuals and make a bunch more margin. He described the approach as looking at a business, deciding everyone should work a new way after AI, and reinventing the process and software for the customer.
“We charge a company a whole lot more than we can charge individuals and we can make a bunch more margin.”
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In PLG, reduce up-front friction so end users get real value, then monetize at the enterprise level. Listen
Mark Roberge describes Lauren Nemeth's view of PLG pricing. Friction up front stops users from feeling the power of the tool, and monetizing the end user is common but less ideal. The better model is to let end users go hog wild and monetize the business, through IT lockdown or CFO-controlled volume pricing.
“we let the end user really experience the tool and we monetize the enterprise.”
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Carta offers a free product to companies with fewer than 25 stakeholders that have raised under $1 million, and moves them to a paid plan once they convert. Listen
Jeff Perry said Carta sees around 400 to 500 new companies a month, potentially 600, and launched Carta Launch as a free product for those below the stakeholder and funding thresholds. Companies transition to a paid plan once they convert. He described the aim as getting companies onto the platform and helping them grow.
“we launch a free product called Carta Launch for companies that are less than 25 stakeholders and have raised less than a million dollars just to get them on the platform and help them grow.”
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In a product-led model, keep the entry price low and raise average contract value through expansion as customers see value. Listen
Mark Roberge says he likes the product-led growth approach of reframing price increases as raising average contract value through expansion, while keeping the opening price low-friction. He describes free as the extreme version, with price expanding as customers see value.
“let's raise average contract value for our customers and let's get there through expansion.”
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Ranked by how many independent voices make each point and how specific their evidence is. Co-hosts of a show count as one voice, and a point needs at least two shows to appear here.
Where they split
Outcome-based pricing is the right model for AI products because it ties what the vendor earns to the value the customer gets.
said Manny Medina (Topline), Grant Clarke ([Un]Churned), Bret Taylor (Grit), Michelle Donnelly (The Revenue Leadership Podcast), Diego Ballona ([Un]Churned)
5 sources
Paid charges customers a take rate on their revenue for the life of the contract instead of a software fee. Listen
Manny says customers have been open to the model. A host called it the cleanest form of outcome-based pricing, and Manny summed it up as 'you grow, I grow'. He later said a take-rate model is one reason he isn't worried about investor questions on growth.
“We take a percentage of revenue, so we always take a take rate.”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
Gainsight Atlas charges for a managed renewal outcome rather than for software, combining AI agents and human renewal managers to run a client's renewal book. Listen
Grant Clarke describes Atlas as an operational framework that combines an AI agent with a renewal rep to manage a renewal book on the client's behalf. The client pays for the outcome, not for the product or the software. Josh Schachter summarizes it as 'give us the keys,' with Atlas acting as the client's renewal managers and Grant calling it an extension of the client's team.
“It does that in a way that we are delivering an outcome so the company pays for the outcome not for the product not for the software.”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
Sierra uses outcomes-based pricing and a forward-deployed agent development team because it wants to be accountable for deployment outcomes. Listen
Bret Taylor said the hard part of AI is deploying it successfully, which is partly human and partly technical, so Sierra wants to be accountable for the outcome. He said some clients want to do it themselves, while others need co-innovation, which he described as Sierra's sweet spot. He said the forward-deployed team is called agent development.
“It's why we have outcomes based pricing.”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
Crescendo charges based on outcomes rather than seats and does not charge customers who are not happy. Listen
Michelle described the model as charging customers based on outcomes, not seats, with no charge if the customer is not happy. She said the company is not focused on profitability right now even though it is profitable, and is going for a market share grab to win customers who want to grow with it.
“We're gonna charge you based on outcomes, not based on seats. If you're not happy, we're not gonna charge you.”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
Outcome-based pricing aligns go-to-market and FDE teams around resolutions and customer outcomes, Diego said. Listen
Diego said Intercom charges for outcomes rather than conversations or seats. He said comp plans, performance reviews and incentives for go-to-market and FDE teams are tied to resolutions and customer outcomes, and that Fin's ARR is related to how much work is done for customers.
“from comp plans to performance reviews to all the incentives that we built around all of our like go to market teams”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
True outcome-based pricing is hard to put into practice, so most companies end up pricing on effort or output instead.
said Manny Medina (Topline), Katie Bullard (Topline), Seong Park (Revenue Builders)
3 sources
True outcome-based pricing depends on autonomy and attribution, and because attribution is hard, most agents today are priced between effort and output. Listen
Manny frames two boundary conditions: whether the agent did the work without a human (autonomy) and whether the work can be attributed entirely to the agent (attribution). He says outcome pricing is visible in support, inventory management, procurement and accounts payable, where the agent completes the transaction itself. Most other use cases lack real attribution, so pricing sits between effort (a little above token consumption) and output (a produced artifact such as a presentation or email), or a combination of both.
“Attribution is really hard. So this is why true outcome-based pricing is going to take some time.”
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Outcome-based pricing has long been a goal that companies rarely manage to implement. Listen
She recalls that at her first tech company the team wanted ROI-based pricing and had better ROI models because of it, but could never actually change the price each year. She says maybe now there is a better way, but she is sceptical anyone is doing it yet. She also says outcome-based pricing is less predictable than seat-based pricing.
“Like the dream was to be able to price based on ROI and we never could do it.”
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Outcome-based pricing sounds attractive but is hard to execute because outcomes vary widely across customers Listen
Seong says customers like the idea of paying for outcomes rather than tokens, but outcomes differ by industry, maturity, people, process and tools. He says consumption pricing will likely stay for a while because it exposes whether value is being delivered. He calls his view early and says it is only his current view.
“Unfortunately, I think outcomes for customers are going to be wildly different, right?”
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Supporters mostly sell agents whose work is autonomous and easy to attribute, such as support resolutions, while sceptics look at use cases where attribution is murky.
From one operator's experience
What one named guest described doing or seeing. Each is a single account, not a point several operators agree on.
“we probably would have figured out much sooner where to focus uh if we had uh uh started charging sooner.”
“So there is a door open to do your price adjustment, do them quickly and let the others follow, especially if you are in a market leader position.”
“Palantir pioneered a model where the FDEs were free, subsidized by really expensive software.”
“remember that first deal that you sold your soul to get like you know 98 % discount, but they're public Reference you can use their logo.”
Cassie Young, General Partner at Primary Venture Partners said on The Revenue Leadership Podcast · 7 May 2026
With AI features carrying inference costs, underpricing means subsidising customers while overpricing hands share to competitors.
“if you charge too little, you are functionally paying customers to use your product.”
What to do
- Following Keith Peiris (Topline), put the predictable core on a seat or platform fee and meter only work with visible ROI, such as list building or complex automations.
2 sources
Lightfield tried pure seat pricing and pure consumption pricing before landing on a hybrid, because pure consumption made customers stop using the product. Listen
Seats plus a platform fee was easiest to get through procurement, but usage at the edges ranged from 10% to 100,000%. Pure consumption backfired, with customers feeling there was a meter on every button. The seat and platform fee now covers the predictable core: AI CRM, call recorder, transcription, filling out fields, tasks and the data model. Consumption covers work with visible ROI, such as pipeline generation (list building, LinkedIn messages) and AI workflow automations like complex lead scoring.
“It's like going to a store where everything's really expensive, that our customers didn't touch anything.”
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Replit has moved enterprise pricing from seats to a platform fee plus credits that customers prebuy for 12 months and that anyone in the company can consume. Listen
Ghazi says the enterprise side was seat-based and is now evolving to a usage-based model. The platform fee depends on customer size and a small team starts with a smaller credit pool, while more teams committing means more credits. He says the model is easy to roll out and puts no handcuffs on who can use the product.
“you pre buy basically credits that you think you would need for the next 12 months”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
- Before selling usage, give finance controls. Use Manny Medina's (Topline) caps, limits, wallets and assignments, or Replit's 12-month prebought credit pool described by Ghazi Masood ([Un]Churned).
3 sources
Buyers' concerns about budget predictability under usage-based agent pricing can be handled with caps, limits, wallets and assignments. Listen
When a host raised CFO concerns about managing budgets and forecasting spend under consumption pricing, Manny called it a totally fair question. He listed caps, limits, wallets and assignments as the mechanisms. He treats this as the second question after showing value.
“There's caps. There is limits. There is wallets. There's assignments.”
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Replit has moved enterprise pricing from seats to a platform fee plus credits that customers prebuy for 12 months and that anyone in the company can consume. Listen
Ghazi says the enterprise side was seat-based and is now evolving to a usage-based model. The platform fee depends on customer size and a small team starts with a smaller credit pool, while more teams committing means more credits. He says the model is easy to roll out and puts no handcuffs on who can use the product.
“you pre buy basically credits that you think you would need for the next 12 months”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
Credit-based usage pricing is hard for CFOs to accept because it can get out of control quickly. Listen
The speaker says outcome-based pricing is marketing fodder right now, and that CFOs want predictability and are wary of credit usage getting out of control. As an example of the issue, they note that Claude Business at $150 a month gives four times less usage than Claude personal at $200 a month. They tie this to the margin challenge AI companies face.
“I want predictability. I am really getting a little skeptical and hesitant about this credit usage because things can get out of control really fast.”
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- Ship value proof with the bill. Use an itemized log of agent work (Medina, Topline), a credits-versus-hours-saved calculator (Kellie Woodin, [Un]Churned) and a per-rep budget case (Jaleh Rezaei, Topline).
3 sources
Manny Medina describes a value ladder for agent billing: transparency first, then explaining the value of each piece of work, then customer-specific ROI. Listen
Step one is letting the buyer and their finance team see what the agent did, described in normal terms, like the old itemized phone bill where you went straight to the biggest line to check it. Step two is explaining the value, for example that a piece of research would have taken a human a long time, or that the agent produced a PowerPoint or an analysis. ROI comes last and depends on each customer's own equation. He says agents he works with are often failing at the first rung, and that once work is visible a buyer can question how artifacts were used, but cannot dispute that the work was done.
“So explainability is like the first rung in the ladder.”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
Consumption pricing puts 'good pressure' on CS to prove value, and Notion answers it with a calculator setting credit cost against hours saved. Listen
Kellie Woodin said product usage data doesn't tell the full story, so CS has to understand the actual time saved. Notion's internal 'custom agent hall of fame' includes a small calculator for what credits are worth. Her example takes hours an agent saves (about 10 a week for her email agent) times an hourly salary rate and compares that with credits that cost under $5 a day. Customers come to Notion for guidance on these calculations across their LLM and Notion credit usage, which she said positions CS as strategic.
“we've been able to include a small calculator of how to understand what the credits are worth.”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
AI vendors must build the ROI case for each rep, because otherwise buyers default to minimizing every AI bill. Listen
She said customers are anxious about AI bills and have started asking how to lock down credits rather than what value they receive for them. She suggested vendors should show how the bill maps to the value of the work done, and she argued that customers should consider the budget per rep. Mutiny focuses on enterprise sales because she sees the clearest ROI there.
“And so I do think it's important for companies like us to make our own ROI case and make it really clear, how should a customer think about the budget allocation for every single rep?”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
- Reach outcome pricing in stages as AJ Bruno Bruno ([Un]Churned) plans: prove savings on a flat platform fee first, then propose outcome terms from each customer's data, and build a reusable catalog of outcome definitions as Medina describes for Sierra.
3 sources
QuotaPath plans to reach outcome-based pricing by first proving cost savings on a flat platform fee, then proposing outcome-focused changes using that customer's data. Listen
AJ Bruno describes a crawl-walk-run pricing approach: start by showing QuotaPath can run comp and save customers money on a flat platform fee. Once that works, review the customer's data and propose doing things differently next year to test further savings or gains. He says comp has always been about being a performance driver.
“let's just prove out that we can do this and save our customers money on a flat, go ahead and call it a platform fee. Once we're able to do that we can go back and look at that look at the data for those customers and then say like look let's do it this differently next year test this out.”
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Agent pricing should be customized to each customer's definition of value, citing Sierra's catalog of outcomes as the model. Listen
Manny says Sierra went to outcome-based pricing from the start and, rather than debating what counts as an outcome, keeps a catalog of outcomes already tallied for other customers; he says their margins are great as a result. He rejects a host's suggestion that this only works in support. He describes the belief that pricing must fit in one standard box as a limiting belief.
“you should make your pricing way more customizable, depending on what your customer value is.”
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The definition of an outcome changes for every customer, so agent metering has to be configurable per customer. Listen
Manny's examples for a support resolution: the agent answered and the customer went away; the customer went away and didn't return within a week, which means keeping a window open to watch for the signal; or the case was escalated but a human responded within two minutes. He says this flexibility in understanding what the agent did became Paid's differentiator.
“So every single definition of an outcome or work changes per customer. You need a flexible platform to do that.”
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- Never charge on tokens. Medina (Topline) says they are an internal measure that varies by model and means nothing to the buyer.
1 source
Tokens should never be the unit agent builders charge on, because they are an internal measure that means nothing to the buyer. Listen
Manny says tokens vary by lab and are an internal measure of how LLMs are built. A host noted that two models can do the same task using different numbers of tokens, which Manny agreed with. He says agent builders, unlike the labs, have to show a measure of the value delivered to the customer.
“A token should not be a unit of value for charging because a token is really kind of like the inside secret.”
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4 more
- At every renewal, rewrite fixed-price and long-notice terms so they stop blocking increases, as Jacobs Moller Korsgaard and Mark Roberge Stiving (Impact Pricing) advise, and set an agreed calendar of increase dates instead of reacting weekly.
3 sources
Price increases cannot reach a high implementation rate while a large share of revenue is locked in fixed-price contracts. Listen
Jacob says contracts with terms such as a four-month notice period or a two-year price period conflict with a pricing calendar. He gives the example that if 50% of revenue is bound in contracts, pushing increases repeatedly makes no sense. Companies should make consistent changes across their contract database to gain flexibility. Mark Stiving adds that renewal time is the moment to change contract terms so you don't get stuck again.
“If we know that 50% of our revenue is bound in contracts, we cannot change them. So we need to get that done before we can have a high implementation rate.”
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Jacob personally favours an agreed pricing calendar with a fixed number of increase slots per year over reacting every time costs move. Listen
He says Danfoss is actively debating cadence internally: some argue for recovering costs immediately when they hit. His personal view is that a calendar, which can differ by industry, gives customers predictability and aligns internal processes instead of keeping them constantly reactive. He presents this as his own opinion, not a settled company policy.
“for me personally, I think the idea of a calendar which can look different from industry to industry makes a lot of sense because then you can ensure that your internal processes are more aligned as opposed to constantly being very reactive to the changes that are bound to happen.”
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When costs change week to week, teams can recalculate endlessly; fixed dates force action. Listen
Jacob notes that with week-to-week cost movements, waiting a week and recalculating can give a different answer, so teams keep recalculating instead of acting. He argues for agreed dates for each step so the organisation and market can follow and a solid process can be installed.
“if you wait one week and do the calculation again, you might come to a different result. So you keep on calculating until but you know, you need to act.”
Listen to the episode Episode Pricing & packaging Link to this Report a problem
- When heavy discounting appears, check rep positioning and add solutions engineers for deeper discovery before blaming competitors, per Usha Iyer (Revenue Leadership Podcast).
1 source
Heavy discounting may reflect positioning or discovery gaps rather than fierce competition or a product gap. Listen
Usha says some revenue leaders assume discounting is caused by competitors or missing product features, which can leave them feeling disempowered. She says the cause may instead be poor positioning, so the team should check rep coaching and bring in solutions engineers for deeper discovery to create value in the deal.
“it could just be that we are not positioning our product well.”
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- Test new models with bundles, offers and discounts before committing, as Usha Iyer recommends.
1 source
Usha recommends running pricing experiments with bundles, offers and discounts before committing to a new pricing model. Listen
Usha says SaaS companies are shifting toward platform, feature-rich and consumption-based models, with experimentation such as credits being sensitive. She says she would start with special bundles, offers or discounts to learn what makes sense, and then revamp pricing and packaging as needed. She cites Salesforce changing its pricing several times a year as an example of the uncertainty.
“experimentation is the best way not to get sucked into one pricing model or another before you know what really makes sense.”
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- Before launching consumption SKUs, confirm your billing and quoting systems can handle them. Joubin Mirzadegan (Grit) says legacy CPQ and billing break, and Chris Degnan (Revenue Builders) recalls Snowflake waiting months to bill signed customers.
2 sources
Complex modern pricing models break the billing and quoting software they were built on. Listen
He lists early renewals, expansions, multi-year deals and more SKUs as making pricing very complex, and says consumption-based SKUs are hard to build on existing software, using Glean's consumption SKU as an example. He says the problem exists on both the billing side and the quoting side. The company he is incubating plans to start with AI configure-price-quote and then build out billing and contract lifecycle management.
“the software that these things were built on is not designed for a world where”
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Snowflake's first contracts were signed by early customers before billing was set up, and billing took about four or five more months. Listen
Accordant Media and White Ops were using the product daily to the point that it was costing Snowflake money. Chris Degnan said that before Bob Muglia became CEO he invented a really awful pricing scheme, which the company later had to unwind, and pitched it to both customers. They agreed to pay around June 2014. He said the company could not bill them until about the fall of 2014.
“We got them to agree to pay us money, but then we couldn't bill them until probably the fall of 2014.”
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All 12 positions best supported first
- AI vendors have to translate usage and credit bills into concrete value or ROI, or buyers will focus on minimising spend.
4 independent voices · 2 shows4 new this month
said Manny Medina (Topline), Kellie Woodin ([Un]Churned), Jaleh Rezaei (Topline), Sam Slevin (Topline)
6 sources
- Outcome-based pricing is the right model for AI products because it ties what the vendor earns to the value the customer gets.
5 independent voices · 4 shows2 new this month
said Manny Medina (Topline), Grant Clarke ([Un]Churned), Bret Taylor (Grit), Michelle Donnelly (The Revenue Leadership Podcast), Diego Ballona ([Un]Churned)
5 sources
- Per-seat pricing is going away and is being replaced by platform fees plus usage or outcome charges.
3 independent voices · 2 shows1 new this month
said Ann Davis (Revenue Builders), Jake Saper ([Un]Churned), Ghazi Masood ([Un]Churned)
3 sources
- A cheap entry plan should be used to acquire users, with the real money made by upgrading them to much larger plans.
3 independent voices · 2 shows2 new this month
said Alex Mashrabov (The Twenty Minute VC), Keith Peiris (Topline), Tomasz Tunguz (Topline)
6 sources
- True outcome-based pricing is hard to put into practice, so most companies end up pricing on effort or output instead.
3 independent voices · 2 shows1 new this month
said Manny Medina (Topline), Katie Bullard (Topline), Seong Park (Revenue Builders)
3 sources
- Keeping price low early removes barriers to adoption and matters more than maximising revenue per deal.
3 independent voices · 3 shows1 new this month
said John Gilbo (Impact Pricing), Aman Narang (Grit), Ed Calnan (The Science of Scaling)
6 sources
- Charging for agent work or usage instead of seats removes or offsets the seat contraction that hits SaaS renewals.
2 independent voices · 2 shows2 new this month
said Manny Medina (Topline), Kellie Woodin ([Un]Churned)
2 sources
- Locking revenue into fixed-price contracts stops a vendor from capturing more value or pushing through price increases.
2 independent voices · 2 shows2 new this month
said Manny Medina (Topline), Jacob Moller Korsgaard (Impact Pricing)
2 sources
- Incumbents with high prices struggle to cut them to match cheaper AI-driven challengers.
2 independent voices · 1 show
said Mark Roberge (Topline), Sam Jacobs (Topline)
3 sources
- Pure consumption pricing creates budget anxiety for buyers, so it needs caps, limits or a predictable fixed base.
2 independent voices · 1 show2 new this month
said Manny Medina (Topline), Keith Peiris (Topline)
3 sources
- Companies leak margin by acting too slowly on cost changes, and automation can close that gap.
2 independent voices · 1 show2 new this month
said John Gilbo (Impact Pricing), Roberto Rivera (Impact Pricing)
2 sources
- Post-sale success and support services can be packaged and sold as paid offerings on top of the software subscription.
2 independent voices · 1 show
said Jean de Villiers ([Un]Churned), Abbas Haider Ali ([Un]Churned)
3 sources
Actions written 10 Oct 2026 from the most useful of 111 recent insights and checked against them.
What was said 144 insights
Mashrabov expects OpenAI and Google to demolish the $20/month prosumer subscription market, so Higgsfield focuses on upgrading users to over $1,000 a year. Listen
He calls this a contrarian bet and says horizontal products will absorb many verticalized $20-30/month tools; he agrees that much low-end consumer design work Canva served can now be done in OpenAI. He says Higgsfield will never win at $20 a month. Its priority is showing value fast enough to move a $20 subscriber to spending more than $1,000 a year.
“How can we make them to upgrade to over, to spend over $1 ,000 a year with us?”
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Jake Saper suggests technology vendors may come to look more like insurance carriers that financially guarantee an outcome, though he calls this a wild future rather than a settled one. Listen
He describes a vendor guaranteeing a renewal percentage and being paid accordingly as the rate flexes up or down. He ties this to the value of a human being accountable for warranting the outcome and fixing things when they break, which he says is why he does not see human involvement as a passing fad.
“Instead, it could look more like I am an insurance carrier and I am guaranteeing financially some outcome you're hiring me to perform.”
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The ACV companies can close remotely over Zoom is coming down, so he expects an in-person outside sales process and outsized demand gen to matter more. Listen
He attributes this to the noise in the market and to the trust and relationships needed when a company buys a system like this for the first time. He says the company does not need to start with a $100 million enterprise revenue target.
“we're seeing the ACVs come down. So, I think there's going to be an outside sales process and furthermore an outsized demand gen process.”
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Daniel expects AI pricing to move from seats to consumption, and says Glean has only recently added a consumption model. Listen
Daniel said Glean had sold by seat and has only recently introduced consumption pricing. He argued the model benefits both sides, since customers use the product more as they get more value. He said sellers and post-sale teams must then make customers successful to drive that usage.
“I see a big movement to this whole model is consumption. based moving forward”
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Outcome-based pricing sounds attractive but is hard to execute because outcomes vary widely across customers Listen
Seong says customers like the idea of paying for outcomes rather than tokens, but outcomes differ by industry, maturity, people, process and tools. He says consumption pricing will likely stay for a while because it exposes whether value is being delivered. He calls his view early and says it is only his current view.
“Unfortunately, I think outcomes for customers are going to be wildly different, right?”
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He has seen other organisations moving to a customer outcomes structure, driven by the shift toward outcome-based pricing where customers pay for a discrete piece of value. Listen
Rob described a future where people pay for a concrete or discrete piece of value from their software. He said that under that model the goal is to make sure customers are solutioned the right way and then able to attain the value. He said he has seen other organisations moving to this kind of structure too.
“if you think about a future where people are just paying for a, a concrete or discrete piece of value that you get out of your software.”
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Alex suggests AI companies with flat subscriptions could add premium speed tiers, as some providers already have. Listen
Alex describes a customer with a flat, one-size-fits-all subscription and asks whether it could open a premium tier for speed. He notes this is happening elsewhere, citing Anthropic's fast option and OpenAI's Codex Spark, which runs on Cerebras. The customer said it had never considered premium tiers but agreed it was possible, and Alex said he imagined such a tier would more than pay for the speed.
“And I imagine it would pay for what you and I are talking about in droves.”
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Peter's bull case for OpenAI is that the rivalry between leading AI labs will eventually come down to price, and that product advantages are not long-lasting. Listen
Peter describes this as one interesting bullish take on OpenAI. He says that at some point the competition between the top firms has to come down to who can offer what customers need at the best price. He suggests that compute deals made now could enable pricing power later, and that a competitor catching up on product could then gain that pricing power.
“that at some point this war between these firms, especially number one and number two, has to come down to price.”
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AJ Meyer predicts robotics business models will follow the arc of enterprise software, moving from long payback periods to near-immediate time to value. Listen
He says the current capex model sounds like enterprise software in the 1970s and 80s, with three-year paybacks. Over the following decades software became cheap enough that payback periods stopped being discussed, and free trials became common. He expects robotics to follow the same path over the next 20 years, starting with capex.
“sounds an awful lot like enterprise software in the 1970s and the 80s.”
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SaaS pricing is being completely restructured and that the direction is unclear, with outcome-driven models a possibility in the agentic world. Listen
Josh said he does not know exactly where pricing will go in the agentic world and mentioned outcome-driven approaches as one possibility. He made the remark while discussing Conga's acquisition of PROS, a CPQ and pricing optimization company.
“right now we're in a time in SAS where you know what pricing is being completely restructured and we don't know exactly where it's going to go in the agentic world, outcome driven, so on and so forth.”
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AJ Bruno predicted that up to 50 percent of pricing models for AI products will be based on outcomes next year. Listen
He said 2026 will be the year SaaS success is defined by measurable business outcomes delivered by AI workflows, not by features or automation alone. Others on the show reacted with surprise, and one offered to take the other side.
“Up to 50 % of pricing models next year in non, in AI products will be based on outcomes.”
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