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Per-user pricing still makes sense when each person’s access is a meaningful unit of value. It becomes a poor fit when customer value or product consumption grows independently of headcount—for example, when a few people account for most activity or software completes work through automated workflows. That is why some SaaS companies consider usage-based, platform-fee, outcome-linked, or hybrid pricing. It is not evidence that seats are obsolete: survey respondents still use seat metrics widely, and no pricing model is shown to outperform all others.
Why can per-user pricing stop matching value?
A seat is easy to count, explain, and forecast. It can be a sensible price unit when each additional person receives useful access and the customer sees that access as part of the value being purchased. The mismatch arises when adding users does not add much consumption or value—or when substantial value is delivered without adding users.
- Use is concentrated: a handful of power users may generate most of the activity, while a seat count treats all licensed users alike. McKinsey illustrates this with an analytics product in which three of 100 enterprise users account for 95% of use. That is an example, not a general usage statistic. (McKinsey & Company)
- Seats are difficult to audit: shared credentials can make it hard to determine how many people actually use a product.
- Work is automated: AI or software workflows can produce actions or outputs without a corresponding increase in human users.
- Consumption drives value: when the customer’s perceived value changes with a measurable volume of work, a seat count may be a weak proxy for what the customer receives.
Those are reasons to examine the meter, not proof that seat pricing is wrong for every product. Access itself can be valuable even when usage is uneven, and a new metric can create costs in predictability, explanation, and billing.
Have SaaS companies abandoned seat pricing?
No. Price Intelligently by SBI’s 2025 State of SaaS Pricing reports show that seats remain common, though they are rarely the only value metric. Part 1 reports that more than 80% of respondents use some kind of seat-based metric, while only 8% said seats were their only value metric. These are survey responses, not a census of SaaS products. (Price Intelligently by SBI, Part 1)
The same report describes respondents’ pricing models as approximately 21% pure usage-based, 23% flat fees with no usage included, and 37% platform fees that include usage. Those categories and percentages belong to the report’s survey; they should not be read as shares of every company or market. The report’s Part 2 also finds that seats appear across pricing structures but are less often the primary or sole value metric outside flat-fee pricing: 60% of flat-fee companies use seats as the primary or only value metric, compared with 34–38% for other pricing models. (Price Intelligently by SBI, Part 2)
What can replace a seat-only price?
There is no single replacement. The useful question is which unit best reflects what customers value while remaining understandable and operationally practical.
Rank #2
| Model | How it connects to value | Buyer predictability | Operational considerations |
|---|---|---|---|
| Per-user or seat-based | Strong when each person’s access is itself valuable; weaker when activity or value is concentrated or automated. | Generally straightforward to forecast because the number of seats is visible. | Familiar and comparatively simple, though shared credentials can complicate auditing. |
| Usage-based | Charges for a defined consumption unit, which can track variable use more closely. | Can be less predictable if use fluctuates or the bill is hard to estimate. | Requires a clear meter and accurate measurement and invoicing. (Stripe) |
| Platform fee with included usage | A recurring base fee buys access and an allowance of use; additional usage may be limited or charged separately. | The base and included allowance can make routine costs more predictable, but customers need to understand caps and what happens beyond them. | Balances access revenue with expansion, provided allowances and overages are communicated clearly. |
| Base fee plus variable usage | Combines recurring access with a charge tied to a selected usage unit. | The base is predictable; the variable portion depends on consumption. | Choose a unit customers can connect to value, not merely one that is easiest to count. (Microsoft’s SaaS pricing guidance) |
| Outcome-based | Links payment to an agreed result. | Depends on how reliably the result can be identified and attributed. | Defining what counts as the outcome and establishing attribution can make the model difficult to scale. (Price Intelligently by SBI, Part 1) |
| Hybrid | Combines seats, tiers, platform access, or usage to reflect more than one source of value. | Varies with the mix of fixed and variable charges. | Can fit a complex product, but too many meters make pricing harder to explain and run. (Microsoft’s SaaS pricing guidance; Price Intelligently by SBI, Part 1) |
Is usage-based pricing better than per-seat pricing?
Not automatically. Usage-based pricing can align charges with consumption and variable delivery costs, but it can leave customers uncertain about their bill. Seat pricing offers a familiar, comparatively forecastable unit, but may not track concentrated usage or automated work. The better fit depends on which trade-off customers will accept and whether the chosen meter represents value they recognize.
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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchSurvey growth figures do not establish that switching models causes better performance. In Price Intelligently by SBI’s Part 2 survey, among respondents in the growth-structure chart (N=271), 34% of platform-fee respondents and 32% of usage-based respondents said they were at or above growth targets, compared with 40% of flat-fee and 45% of base-fee respondents. These are descriptive, self-reported results; the report explicitly concludes that no model always outperforms the others. (Price Intelligently by SBI, Part 2)
What changes when AI performs the work?
AI-enabled products make seat counts less dependable when a system can complete actions or workflows without one human user per unit of work. But an AI price should not simply mirror a vendor’s compute bill: the cost of delivery matters to margins, while the customer-facing meter should still make sense in terms of value.
McKinsey’s examples show that AI monetization does not have one settled pattern. Its analysis names ServiceNow Now Assist credits and describes Salesforce Agentforce options that include pay-per-action, Flex Credits, or per-user licensing. These are examples of approaches discussed in the analysis, not a guarantee of current vendor packaging. McKinsey also notes that setting appropriate price levels is challenging and uncertain in the AI-and-SaaS model. (McKinsey & Company)
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How should a company choose a new meter?
Start with the mismatch between the current charge and the value customers receive—not with a preference for whichever model is fashionable.
- Identify the mismatch. Check whether unused seats, highly concentrated usage, automation, or another documented pattern makes headcount a poor proxy. Do not assume that any one pattern applies without product and customer evidence.
- Name the customer-valued unit. State plainly what will be counted—such as a meaningful action, volume, or outcome—and why customers can connect it to value. A metric that is easy for the vendor to measure is not automatically a good value metric.
- Decide how much predictability to preserve. If bills can vary, define any included allowance, caps, upgrade behavior, or overage handling so a buyer can understand likely costs. Do not promise a transition arrangement unless the company has established one.
- Keep the architecture legible. Prefer a small number of meaningful meters over a web of charges. Price Intelligently by SBI cautions against over-rotating away from seats into complicated metric structures. (Price Intelligently by SBI, Part 1)
- Plan for the operating change. Metering and variable billing affect product, pricing, sales, customer success, finance, and billing. McKinsey describes a usage-pricing transformation as a multi-month, cross-functional effort rather than a simple pricing toggle. (McKinsey & Company)
Why “we killed it” needs a company-specific explanation
A company can credibly say it ended its per-user subscription only by explaining its own decision: what the seat metric failed to capture, which customer-valued unit replaced it, and what buyers gain or give up. Industry survey data supplies context, not that company’s motive or results. Without company-specific evidence, it would be misleading to claim that a particular product abandoned seats because of unused licenses, AI, customer feedback, or improved growth.
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