पाठशाला Pathshala · हिसाब Hisāb, Unit economics · Lesson 19 · Build
Usage-based, seat-based and hybrid pricing
The unit you charge for decides how revenue grows inside an account, how well you can forecast it and whether heavy users make you money. Choose it before you choose the price.
Pathshala, The Founder Library · 11 October 2026 · 7 min read
Founders spend weeks on the price and minutes on what the price is per. Yet the unit decides more: whether an account’s bill grows as it gets more from the product, whether next quarter’s revenue can be forecast, and whether the customers who use the product most are the most profitable or the least.
This lesson sets out the three families of pricing metric, shows each on real price lists, works one product through all three, and gives four tests for choosing. The figure in the middle bills one customer three ways and shows what each does to margin and to the spread between a slow month and a busy one.
Seats: a bill everyone can predict
Seat pricing charges for each person who can use the product. Its virtue is predictability. The buyer knows the bill before the year starts, finance can budget it, and the seller can forecast revenue from headcount. It suits products whose value genuinely rises with the number of people using them: collaboration, communication, design, anything where the twentieth user makes the first nineteen more productive.
Its defect is that it charges for access, not use. Customers buy seats for people who never log in and then feel overcharged at renewal. Slack’s answer is its Fair Billing Policy: a paid member who has not used Slack in over 28 days stops being billable, and the account receives a prorated credit for the unused part of the period. That is a seat model that has quietly borrowed one feature of usage pricing, and it removes the most common objection at renewal.
Seat pricing has two newer problems. When a product automates work, the customer needs fewer seats as the product gets better, so success shrinks the bill. And when each seat carries a real variable cost, such as AI inference, messaging or storage, the heaviest seat and the lightest pay the same while one costs many times the other.
Usage: the bill follows the value
Usage pricing charges for each unit of work the product does. Most Indian founders already pay it. Razorpay’s standard rate is 2 per cent of each successful domestic transaction, with GST charged only on the fee and no setup or annual maintenance charge (checked October 2026). The merchant pays nothing in a month with no sales and more in a festive month, and the gateway’s revenue grows exactly as its customers’ businesses do. Meta moved the WhatsApp Business Platform to per-message pricing from 1 July 2025, charging for marketing templates and for utility templates outside an open customer-service window. Google’s BigQuery charges on demand at $6.25 for each tebibyte a query processes, with the first tebibyte each month free.
The strengths are large. Entry is cheap, so small customers start without a procurement process. Revenue in an account expands on its own as the customer grows, which is the cleanest route to [net revenue retention](/library/net-revenue-retention-saas-engine) above a hundred per cent. And revenue tracks cost, so gross margin holds on the heaviest users.
The weaknesses are the mirror image. Revenue falls when the customer’s business does, so a slow quarter across your customer base arrives as a slow quarter for you. The buyer cannot predict the bill, and finance teams dislike a line they cannot budget. And forecasting becomes a forecast of other people’s businesses.
Hybrid: a floor and a meter
A hybrid takes the floor from one model and the meter from the other. The common form is a platform fee that includes a block of usage, with a unit price for usage above it. The fee gives the seller a predictable base and the buyer a known minimum; the overage keeps the bill growing with value and cost. A second form trades price for commitment. BigQuery offers capacity priced by the slot-hour as an alternative to on-demand queries, and its Enterprise edition lists $0.06 an hour on pay-as-you-go against $0.054 with a one-year commitment and $0.048 with three. The buyer accepts a minimum in exchange for a lower unit price; the seller gets revenue it can forecast.
Bill Gurley put the investor’s view in All Revenue is Not Created Equal: investors favour pricing models that provide a high level of predictability and consistency in the future. A hybrid is usually the cheapest way to buy that predictability without giving up the growth that usage brings.
One product, billed three ways
A Pune company sells software that reads purchase invoices for chartered-accountant firms and posts them to the ledger. A typical firm has ten staff using it and sends 4,000 invoices a month. Each invoice costs the company about ₹1.50 in AI processing. It can charge ₹2,000 a seat, which is ₹20,000 a month; ₹5 an invoice, which is also ₹20,000; or ₹8,000 a month including 1,500 invoices and ₹5 for each one after that, which is ₹20,500. In an ordinary month the three bills are the same. They stop being the same in the months that matter.
In the weeks before a tax deadline the firm sends three times as many invoices. On seats it still pays ₹20,000, but processing now costs ₹18,000, and the company’s margin on its busiest customer in its busiest month falls to 10 per cent. On usage the bill is ₹60,000 and the margin holds at 70 per cent. In a quiet month at 40 per cent below normal the usage bill drops to ₹12,000, while the hybrid floor keeps it at ₹12,500 and a firm with almost no invoices still pays ₹8,000.
Set the usage to 12,000 and switch between the three models to see the margin on the seat plan collapse. Then set the swing to 60 per cent and read the slow-month and busy-month bills: that spread is the forecasting problem in one pair of numbers. Finally raise the platform fee and the included units until the hybrid floor covers your fixed cost to serve one account, which is usually the right place for it.
Charge for the unit that grows when the customer gets more from you, and put a floor under it that pays for the account even in a quiet month.
Four tests for any metric
Does it grow with value? Ask customers what they would measure to decide whether the product was worth it, and charge for that or for its nearest countable proxy. Transactions processed, invoices posted, orders shipped, patients booked. If the customer would not recognise the unit as a measure of what they got, it is the wrong unit.
Can the customer predict the bill? If the buyer cannot estimate next month’s bill within a reasonable band, add a floor, a cap, a committed tier or alerts as usage approaches a threshold. A bill the customer did not see coming is the quickest way to lose an account that was otherwise happy.
Can you forecast it? Model next year’s revenue under the metric using last year’s actual usage by account. If the forecast range is too wide to plan hiring against, the metric needs a committed component.
Does it track your cost to serve? If one customer can cost ten times another under the same price, the metric is wrong for a product with real variable cost. This test matters most for AI products, where inference is a cost of every unit, and is the one founders most often skip. Two practical tests sit under all four: the unit must be easy to count from your own logs, and hard for the customer to game by batching, sharing logins or moving work outside the product.
Changing the metric later
A metric change is a price change for every existing customer, even when the average bill stays the same, because some bills rise and some fall. Start with new customers only. For existing accounts, run shadow billing for two cycles first: send each customer, alongside the real invoice, what they would have paid under the new metric, so nobody is surprised. Move the accounts whose bill falls first, cap the rise for those whose bill climbs, and give the largest accounts a conversation before an email. The disciplines in [pricing experiments](/library/pricing-experiments-without-burning-customers) apply in full.
The quarterly metric review
Once a quarter, pull every active account and plot its bill against its usage for each of the last three months. Mark three groups. Accounts whose gross margin is below your target, usually the heaviest users on a flat plan. Accounts whose bill moved by more than a third from one month to the next, the ones most likely to call finance. And accounts whose usage grew while their bill did not, which is expansion revenue the metric is failing to capture.
Compare churn and expansion in each group with the rest of the base. If heavy users are unprofitable, the metric needs a meter. If volatile bills churn faster, it needs a floor or a commitment. If growing accounts are not paying more, the unit is not the one that tracks value. Change one thing a quarter, for new customers first, and read the same chart again ninety days later.
Nothing here is legal, tax or investment advice. The Pune company is illustrative; the price lists cited were checked in October 2026 and change often.
Sources
- Slack, Slack’s Fair Billing Policy, Slack Help Center — Members inactive for more than 28 days are not billable; prorated credits. Checked October 2026.
- Razorpay, Payment Gateway Pricing and Fees Explained, February 2026 — 2 per cent of successful domestic transaction value; GST on the fee only; no setup fee or AMC. Checked October 2026.
- Meta for Developers, WhatsApp Business Platform pricing — Per-message pricing from 1 July 2025. Checked October 2026.
- Google Cloud, BigQuery pricing — On-demand at $6.25 per TiB with the first TiB a month free; capacity pricing by slot-hour with one- and three-year commitments. Checked October 2026.
- Bill Gurley, All Revenue is Not Created Equal: The Keys to the 10X Revenue Club, Above the Crowd, May 2011 — Investors favour pricing models with predictability and consistency.