SaaS pricing models: per seat, usage-based, tiered and hybrid, with the evidence on each

The main SaaS (software as a service) pricing models are flat-rate, per-seat, tiered, usage-based, freemium and hybrid. Most sit on a subscription, which Benchmarkit reports is the primary model for over 80% of business-to-business SaaS companies. The real choice is the value metric the subscription charges on. Usage adoption figures range from 85% to 15%, depending on whether a survey counts any usage component or only the primary model.

What are the main SaaS pricing models?

Subscription is still the default. Benchmarkit reports that subscription pricing is still the primary pricing model for over 80% of B2B SaaS companies, meaning business-to-business software as a service. The real choice is what the subscription charges on.

That unit is the value metric. Each model below is defined by the one it uses.

Model versus strategy

Paddle draws a clear line: pricing models are different from pricing strategies. The model is the framework, such as per-user, tiered or usage-based. The strategy is the reasoning behind your price points and target segments. As Paddle puts it, you can see a company's model on its pricing page. This section covers models. Our pricing page teardowns show how real companies put them on the page.

The six models

• Flat-rate charges every customer the same amount regardless of how much they use your product. Basecamp charges $299/month for unlimited users and projects.
• Per-seat charges based on the number of people using your software. Slack uses a variant that bills only active users.
• Tiered offers multiple packages at different price points, typically separated by features, usage limits, or user counts.
• Usage-based charges customers based on consumption, for example per application programming interface (API) request, as Twilio does.
• Freemium pairs a free version with limited features alongside paid tiers with expanded functionality. See our guide on freemium versus free trial.
• Hybrid mixes these. HubSpot combines tiered pricing (Starter, Professional, Enterprise) with per-seat charges and usage-based fees for contacts above set thresholds.

Model	Value metric	Revenue predictability (our reading)	Typical buyer (our reading)
Flat-rate	Access to the product	High	Small teams wanting one simple price
Per-seat	Named or active users	High, grows with headcount	Teams where each person uses the tool
Tiered	Feature or limit bundle	Medium to high	Mixed segments, from startup to enterprise
Usage-based	Units consumed	Low, varies month to month	Developer and infrastructure buyers with variable volume
Freemium	Upgrade from a free plan	Low until conversion settles	Self-serve users trying before buying
Hybrid	Base fee plus a usage or seat metric	Medium to high	Accounts that need a fixed budget and room to scale

The lines between models blur in practice. Metronome reports that 77% of the largest software companies incorporating consumption-based pricing into their revenue models. Benchmarkit found that just under 50% of a top 125 high-growth PLG company cohort were using a more basic subscription model (seat based). PLG stands for product-led growth. In those companies, usage acted as a limiting function by pricing package tier and was not billed directly. In our reading, many companies described as usage-based are really tiered subscriptions with usage caps.

How many SaaS companies use each pricing model?

The adoption figures for usage pricing look contradictory until you read what each survey asked. Put them side by side with the sample and the date, and most of the gap goes away.

Survey	Sample	Date	Figure	What it counts (our reading)
Metronome and Greyhound Capital	100 SaaS companies	January 2025	85% have adopted usage-based pricing (UBP)	Any usage component
Forbes list of next billion-dollar startups, via Metronome	Startups on the list	Not stated	64% offer UBP	Any usage component
Survey cited by Stripe	Not stated	2025	15% usage-based, 11% value-based	Primary pricing approach

The top line comes from a January 2025 survey of 100 SaaS companies run by Metronome and its investor, Greyhound Capital, in which 85% said they had adopted UBP. The same report put usage adoption among the largest software companies in a similar range, as covered above, and found that 64% of Forbes' Next Billion-Dollar Startups use the model.

A separate 2025 survey cited by Stripe found that only 15% of software as a service (SaaS) companies reported taking a usage-based approach and 11% a value-based one.

Why the numbers diverge

We think the two sets of figures measure different things. "Taking a usage-based approach" reads as the main way a company prices. Most hybrid pricing passes the first test and fails the second.

For a wider view, the High Alpha 2025 benchmarks drew on more than 800 respondents, mostly in the US and Europe. It reported that the leaders are experimenting with hybrid, consumption, and outcome-based models, not settling on one. Our summary is in the High Alpha digest.

Check any adoption stat before you quote it

Run every figure through four questions before it goes into a board deck or a pricing memo:

1. Sample: how many companies, and who picked them?
2. Date: when was the survey run (not when it was published)?
3. Definition: "any usage component" or "primary model"?
4. Sponsor: does the publisher sell the model being measured?

Is usage-based pricing better than per-seat?

Neither model wins on every count. The choice comes down to four trade-offs: how easy it is to start, how revenue grows inside an account, how well you can forecast it, and what happens when your product does work that people used to do.

On entry, usage has the edge. In his review of the market, Kyle Poyar wrote that usage-based pricing let customers start using a product for a comparatively low cost. Snowflake makes the same case from the vendor side: customers can try out the product with a single use case or workload before they expand. Expansion is built in, because usage pricing removed limits to the number of people who had access.

Forecasting is where seats hold up. Switching also means rethinking everything from billing to forecasting to org structures to sales comp.

Automation tips the balance. Poyar put it plainly: the more successful a product is, the fewer user seats a customer needs. Your workflow automation lets them run the same volume with 12 people. Price per automated task instead, and the bill follows the work.

Per seat (our reading)	Usage-based (our reading)
Entry: higher upfront commitment	Entry: low starting cost, one use case first
Expansion: only when headcount grows	Expansion: grows with consumption
Forecast: fixed, known in advance	Forecast: moves with the customer's activity
Automation: revenue shrinks as the product works	Automation: revenue tracks work done

When seats still fit

Seats fit when value tracks the number of people using the product, such as collaboration, design or sales tools where each user gets their own workspace. They also fit when the buyer needs a fixed annual budget line. Smaller customers lean this way: Poyar found hybrid models common among businesses selling to smaller customers who might be more sensitive to unplanned expenses.

When usage fits

Usage fits API, automation and data products. For API-first software, there doesn’t need to be a user to see value. Some AI products go a step further: Intercom priced its Fin chatbot at $0.99 per successful resolution.

This week, pull your ten largest accounts. For each, compare the change in seats over the past year with the change in your core usage metric. Where usage grew and seats stayed flat or fell, your seat price is leaving money behind. Watch retention on those accounts too.

What public companies on usage pricing report in their filings

Survey data shows what companies say they charge. Annual reports show what usage revenue does once it is booked. Snowflake and Twilio both bill on consumption, and their filings for fiscal 2025 and 2026 give a founder a reference point for the metrics investors read first.

Snowflake: expansion shows up in retention

Snowflake's fiscal 2026 ended January 31, 2026. It reported product revenue of $1.23 billion in the fourth quarter, up 30% year over year. The 10-K ties growth to usage: customers typically expand their usage significantly, as evidenced by a net revenue retention rate of 125% as of that date.

Net revenue retention (NRR) is the metric to copy. Under consumption pricing, that figure moves with how much customers run, not with how many contracts they sign.

Metric Snowflake reported	Figure	What it tells a startup (our reading)
Customers above $1 million in trailing 12-month product revenue	576 to 733, January 2025 to January 2026	Large accounts grow into their spend over time
Forbes Global 2000 customers	790, about 43% of revenue	Usage revenue can concentrate in a few heavy users
Remaining performance obligations (RPO)	$9.77 billion, up 42%	Committed contracts give a floor under variable billing

In our reading, the RPO line matters most for a startup copying the model. Committed spend contracts let a usage business show forward revenue even though monthly bills vary.

Twilio: the filing warns against reading one period

Twilio's 10-K for the year ended December 31, 2025 reported net income of $33.8 million,. The same filing cautions that revenue and revenue growth for any quarterly or annual period should not be relied upon as a guide to the future. We think that warning reads differently for a usage business, where a quarter can swing when a few customers cut their consumption.

Track it the same way this week

Set up three numbers in your own reporting, using the same definitions the filings use. Put them in your growth model.

Monthly usage revenue report

1. NRR (trailing 12 months)
   = revenue this month from customers active 12 months ago
     / revenue from the same customers 12 months ago

2. Accounts above threshold
   = count of customers whose trailing 12-month spend
     exceeds your chosen line (set it at roughly 10x median spend)

3. Committed vs variable
   = committed contract value remaining / last 12 months of revenue

Flag any month where the top 10 accounts' usage drops more than
15% from their 3-month average, and call them before the invoice goes out.

How do I choose a value metric?

In our reading, picking the unit you charge for is where most usage pricing projects stall. A 2021 survey from Coatue Partners found that finding the right metric was the hardest part of deploying usage-based pricing. Treat it as a scoring exercise with three to six candidates.

The three tests

Billing provider m3ter sets out the first test: attach pricing to a usage metric that matches how customers get value and what success looks like to them. When that holds, spend rises when the customer is doing well, and they treat it as a good cost.

The second and third tests come from the same guide: fees should be simple to understand and not impossible to predict. If a buyer cannot explain the bill to their finance lead, or cannot guess next quarter's spend, adoption slows.

The guide's own example is a backend service for mobile games. Pricing on the number of players a studio attracts tracks the studio's own measure of success, is easy to explain and is easy to forecast. If your product has a north star metric, start your list there.

Metrics in use

Company	What the price moves with	What the buyer forecasts (our reading)
Slack	Active users on a subscription	Headcount that logs in
Clay	Credits, features, integrations, support	Credit burn per month
Zapier	Tier chosen by product needs and automated tasks	Task volume

Add a fourth test: can you meter it

A metric you cannot count accurately turns into disputed invoices. In a 2026 PwC and m3ter survey of over 350 software leaders, 63% lacked full confidence in their billing operations. Score metering before you commit.

Scoring template

Copy this, list every candidate, and score each from 1 (weak) to 5 (strong). Weight value alignment double, because a metric customers resent hurts expansion even if the other scores are high.

VALUE METRIC SCORECARD
Product: ____________   Date: ________   Scored by: ________

Candidate metric | Value alignment (x2) | Ease of explanation | Forecastability | Ease of metering | Total (max 25)
-----------------|----------------------|---------------------|-----------------|------------------|---------------
Monthly players  | 5 (=10)              | 5                   | 4               | 4                | 23
API calls        | 3 (=6)               | 3                   | 2               | 5                | 16
Seats            | 2 (=4)               | 5                   | 5               | 5                | 19
________________ |                      |                     |                 |                  |

Questions per column:
- Value alignment: does this number rise when the customer is succeeding?
- Ease of explanation: can a buyer state the bill in one sentence?
- Forecastability: can the buyer predict next quarter within a range they accept?
- Ease of metering: can we count it per account today, with an audit trail?

Rule: any score of 1 disqualifies the metric. Shortlist the top two and test them with five customers.

The figures in the template are our own illustrative scores for the game backend, not data. Run the scorecard with product, finance and sales in one session this week, then take the top two candidates into customer calls.

How many pricing tiers should I have, and when does a hybrid make sense?

Our default is three paid tiers plus an enterprise option. Three tiers give a buyer a low entry point, a middle tier sized for the typical customer and a top tier that frames the middle one as reasonable. Enterprise sits outside the grid as a conversation, not a price. Adding more rarely helps: Paddle lists the risk plainly, that "too many tiers create decision paralysis, poorly designed tiers confuse buyers". If you want buyers drawn to the top paid tier, see how to emphasise the premium tier.

Match the packaging to the buyer

Paddle's guidance was that "B2C pricing requires simplicity and self-serve flows, B2B needs value-based tiers, and enterprise payment demands custom pricing with dedicated support." In practice that changes what each tier is built around.

Buyer type	What the packaging needs	First move this week (our reading)
Business-to-consumer (B2C)	Simplicity, self-serve signup	Cut to the fewest tiers you can, with checkout on the pricing page
Business-to-business (B2B)	Tiers built around value	Separate tiers by the outcome each buyer segment pays for
Enterprise	Custom pricing, dedicated support	Replace the price with a contact form and a named owner

When a hybrid makes sense

A hybrid pairs a base subscription with a usage charge. Paddle described the aim as models that "combine base subscriptions with usage-based components for predictable revenue plus upside". HubSpot is the worked case: it "combines tiered pricing (Starter, Professional, Enterprise) with per-seat charges and usage-based fees for marketing contacts above certain thresholds."

We think a hybrid earns its complexity when your own costs move with usage. Artificial intelligence (AI) features are the clear case, since "each prompt, automation, or inference can carry a marginal cost, which makes flat-rate pricing harder to sustain." The trade is that hybrids are "more complex to implement but offer the flexibility to serve diverse customer needs."

A simple structure to start from:

Monthly bill = tier base fee + max(0, units used - units included) x overage rate

Worked example (illustrative numbers):
Base fee        $200, includes 1,000 units
Overage rate    $0.15 per unit
Usage           1,400 units
Bill            $200 + (400 x $0.15) = $260

Set the included allowance so most customers on a tier never pay overage. The overage should catch the heavy users, not surprise the typical ones.

Price by region

Willingness to pay is not uniform. Paddle reported that Nordic customers paid 28% more than US prices on average, while Brazilian customers paid 12% less. Run these as experiments on one tier first, and keep the tier structure identical across regions so only the price moves.

What does AI do to SaaS pricing?

AI arrived in most SaaS products through the existing subscription. In High Alpha's 2024 benchmarks, 56% of companies reported that they have launched or tested AI features in the prior year. Of that group, 41% are monetizing AI features, a number up 9% from 2023. Among those charging for it, 68% do so with a subscription component.

That default is under pressure. In the 2025 report, AI is core to 100% of products for companies founded in 2025. For companies founded in 2016, none indicated that AI was core to their product. Companies with AI deeply built in were growing twice as fast as those with AI as a supporting product feature. We read that as a correlation, not proof that pricing or AI alone drives the gap.

Why seats break when AI does the work

Earlier sections showed how automation shrinks seat counts. AI goes further. Kyle Poyar describes it as eventually eliminating the need for whole teams of people for ongoing routine work. When the product does the job, the buyer needs fewer logins, and a per-seat bill falls as the value rises.

Here is a worked example with our own numbers. A customer pays $100 per seat per month for 20 support agents, so $2,000. The customer cuts to 12 seats and now pays $1,200.

Pricing approach	Monthly bill in the example	What it tracks (our reading)
Seats only	$1,200	Human logins, which AI reduces
Seats plus per-outcome fee	$2,200	Humans plus work the AI completes

Outcome-based pricing charges customers based on the value it provides. It suits AI because a resolved ticket or a drafted contract is easy to count.

Costs matter too. High Alpha noted that OpenAI had shared it was losing money on their $200-per-month Pro subscriptions. A flat fee with heavy users can eat margin.

What to do this week

1. List each AI feature and the human task it replaces.
2. Pick the unit of finished work for each one: a resolution, a document, a record enriched.
3. Check compute cost per unit against your planned price before you publish it.

AI feature: ________
Human task replaced: ________
Unit of finished work: ________
Units per account per month (90-day median): ________
Compute cost per unit: $____
Proposed price per unit: $____
Seats-only revenue: $____  |  Hybrid revenue: $____

How to test a new price before you commit

The bar for pricing work is low. Benchmarkit reports that the typical B2B SaaS company only invests 1 to 2 days a year on analyzing or testing pricing models, and that pricing is still more ad-hoc and not informed by statistically valid research. A focused week of work puts you ahead of that baseline.

Four steps, in order

1. Test on new signups only. Show the new price to new accounts and leave existing customers where they are. Nobody's invoice changes mid-contract, and you get a clean comparison.
2. Run a pricing page A/B test sized in advance. Pick the conversion lift you need to detect, then use the sample size calculator to set the visitor count before launch. Stop the test at that count, not when one variant pulls ahead. The growth experiment guide covers the setup.
3. Move existing customers later. Once the new price holds up for new signups, migrate the base in groups, with notice and a grandfathering window.

Worked example: seats to base plus usage

A team plan costs $49 per seat. There are 200 accounts averaging 6 seats, so each account pays $294 a month and the plan brings in $58,800 a month. The proposal is $99 base plus $0.02 per task. Replace them with your own percentiles from product data.

Run this model before step 2, not after.

Metrics to watch

• Trial-to-paid conversion for the new-price cohort against the old. Our free-to-paid conversion benchmarks give a reference range.
• Share of customers who reduce spend after migration. If light users downgrade faster than heavy users expand, the base price is too low.

What this page does not cover

This page covers pricing models, not the strategy behind specific price points or segments, and it does not compare billing systems. Nothing here is financial or legal advice.