pricing · pricing-models

Pricing Models

The eight core ways to structure how you charge. This is distinct from the value metric (what unit you charge on) and the tier structure (how you package). Most real products combine two or more of these.

The 8 Pricing Models
Combining Models
The Value/Price Ratio
The Low-Price Retention Counterpoint

The 8 Pricing Models

Model	How it works	Best when	Reference
Flat-rate	One price, one product, everyone pays the same	Simple product, one persona, you want zero pricing friction	Basecamp
Usage-based	Pay for what you consume (metered)	Value scales directly with volume; consumption is variable and easy to meter	Stripe
Tier-based	Good-better-best packages at set prices	Distinct segments with different needs and budgets	Kinsta
User-based	Price per seat/user	Value grows as more people in the org use it (collaboration)	Notion
Feature-based	Price gated by which capabilities are unlocked	Clear feature tiers map to willingness to pay	Intercom
Credit-based	Buy a bucket of credits, spend them on actions	Usage is lumpy or bursty; you want prepaid commitment and simple mental accounting	Audible
Outcome-based	Pay per result delivered (resolution, task completed)	You can measure and attribute the outcome, and the outcome is what the buyer actually wants	Intercom Fin, Zapier
Hybrid	Deliberate mix (e.g. platform fee + usage, or seats + credits)	A single model under- or over-charges different customers	Drift

When to reach for each

Flat-rate — reach for it first if you can. It's the easiest to sell, easiest to understand, easiest to forecast. The tradeoff: you leave money on the table with your biggest customers.
Usage-based — the fairest model when consumption tracks value, but revenue is less predictable and buyers fear a surprise bill. Pair with spend caps or alerts.
Tier-based — the default for self-serve SaaS. Lets one page serve SMB through mid-market.
User-based — only if value genuinely rises with headcount. If it doesn't, seats punish adoption (teams share logins to avoid paying).
Feature-based — powerful for segmentation, but don't gate the feature that delivers your core value; gate the ones that separate casual from serious users.
Credit-based — good for AI/actions-based products where each action has a cost. Credits decouple price from a single unit and make prepayment feel natural.
Outcome-based — the emerging model for AI agents (charge per resolved ticket, per automation run). Highest trust because the buyer only pays when they win — but only viable when the outcome is measurable and clearly attributable to you.
Hybrid — where most mature products end up. A base platform fee for predictability plus a usage/outcome component for upside.

Combining Models

These aren't mutually exclusive. Common combinations:

Tiers + per-user — seats within each package (most B2B SaaS)
Platform fee + usage — predictable base, variable upside (Twilio-style)
Seats + credits — pay per person, then top up credits for heavy actions
Feature tiers + outcome — unlock capabilities by tier, charge per result on top

Pick the primary model from the value metric, then layer a second only if a single model clearly mis-prices a real segment.

The Value/Price Ratio

Aim for roughly a 10:1 value-to-price ratio (Ryan Kulp): the customer should perceive about 10x more value than they pay. This is the buffer that makes the purchase feel obvious rather than negotiated, and it leaves headroom to raise prices later as you add value.

If you can't articulate 10x value, the problem is usually the offer or the positioning, not the price point.

The Low-Price Retention Counterpoint

Charging too little is not the safe choice. Low prices hurt retention (Patrick Campbell / ProfitWell data, echoed by operators like Josh Pigford of SpyFu and Tyler Tringas): under-priced customers churn more, not less, because a low price signals low value and attracts the least-committed, most price-sensitive buyers.

Related: the discount-asker signal — customers who negotiate for a discount tend to churn at roughly 2x the rate of full-price customers. Discounting to close a deal often buys a customer who leaves anyway.

Implication: when in doubt, price higher. It's easier to grandfather a price down than to claw one up, and a higher price selects for better-fit, longer-retained customers.