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Micro-SaaS Pricing Engine

Micro-saas Pricing Engine: find your price floor, suggested price, and ceiling from per-user costs, competitor benchmarks, and target margin. MRR projections.

Your numbers

Start from an example

Paying users today; fixed costs are spread across them.

$
$
$
$
Target gross margin

Result

Suggested price
$28.80
Price floor
$16.67
Price ceiling
$58.80
Cost per user
$5
Total monthly cost
$250

MRR at each price point

Floor, suggested, and ceiling priced against current user count.

Floor
$833.50
Suggested
$1,440
Ceiling
$2,940

API/infrastructure cost is 60% of your per-user cost. Caching, batching, or a cheaper model tier could meaningfully improve margins.

General business information, not legal, tax or financial advice. The result comes only from your inputs and the published method. How we check our numbers.

How to use it

  1. Enter your current number of paying users, your variable cost per user (AI API costs, hosting, payment fees and other per-user services), and your fixed monthly costs (base hosting, SaaS subscriptions, domain, monitoring). Fixed costs are spread across your users, so cost per user = fixed costs ÷ users + variable cost per user, and it falls as you grow. That cost per user is the basis of your price floor, the lowest price that still hits your target margin.
  2. Set the competitor price range from your market research: the lowest and highest monthly price charged by direct competitors for comparable functionality. The calculator uses these as anchoring points for your suggested price (90% of the midpoint) and ceiling (120% of the high), because customers judge your price against the alternatives they know. If competitors charge $15-$30/month, a $49/month price requires clear differentiation messaging, while a $9/month price signals a budget or less capable alternative. Conduct competitor research across Product Hunt, AlternativeTo, G2, and direct searches to build a realistic range. For micro-SaaS without direct competitors, use the price of the manual alternative (spreadsheet + hours of work) as the value anchor: if your tool saves 5 hours per month and the user's time is worth $50/hour, the tool's value is $250/month, making a $25/month price (10% of value created) highly defensible.
  3. Choose your target margin. It is measured after both per-user and fixed costs, so it is stricter than a pure gross margin. The default is 70%. AI-heavy products often run lower because every request costs inference, and the tool warns when the margin at the suggested price falls below 60%, because operating costs (marketing, support, development) still have to come out of what is left. Prices are per user per month; if you charge per project or per usage unit, convert your cost and competitor prices to that unit first.
  4. Read the three calculated price points: floor price (cost-based minimum that maintains your target margin), suggested price (market-anchored at approximately 90% of the competitor midpoint, ensuring competitiveness while exceeding the floor), and ceiling price (estimated willingness-to-pay at approximately 120% of the competitor high, representing the upper bound for well-differentiated products). Review the MRR projections at each price point using your current user count, and examine the gross margin percentage at each level. If the floor price exceeds the competitor midpoint, your cost structure is the primary problem, and no pricing strategy will compensate. If there is significant headroom between your floor and the suggested price, you have flexibility to test different price points.
  5. Use the key insight to identify your primary constraint: margin (costs too high relative to price), competitive position (priced above market without clear differentiation), or cost structure (fixed costs require more users than you can acquire). If you launched cheap, test a higher price on new signups before assuming the market will not pay it. Re-run this calculator when AI API pricing changes, when competitor pricing shifts, when your user count crosses a new order of magnitude (100, 1,000, 10,000), or when you add features that change the value proposition.

Questions people usually ask

How is the price floor calculated and what does it mean?

The price floor formula is: (fixed costs / number of users + variable cost per user) / (1 - target margin percentage). This is the absolute minimum price needed to cover all costs and achieve your target gross margin at your current user count. For example, with $200/month fixed costs, 100 users, $1/user variable cost, and a 70% target margin, the floor is ($2 + $1) / 0.30 = $10/month. Pricing below the floor means every new customer makes the business less profitable, not more. If your calculated floor exceeds what competitors charge, your cost structure needs optimization before pricing can be competitive.

What pricing research methodology is this based on?

Three simple rules, not a survey method. The floor is cost-plus: cost per user ÷ (1 − target margin). The suggested price anchors to the market at 90% of the competitor midpoint, but never below the floor. The ceiling is 120% of the highest competitor price, a rough upper bound for a well-differentiated product. Survey methods such as Van Westendorp or Gabor-Granger measure what your own customers would pay; use them to test the range this calculator gives you.

What value metric should I use for my micro-SaaS?

The value metric is how you measure and charge for usage: per seat, per project, per API call, usage-based, or flat monthly fee. This calculator works per user per month, so convert costs and competitor prices to that unit, or to your own unit, before entering them. Per-seat works when each user adds roughly equal value (team collaboration tools). Usage-based pricing aligns cost with value delivered (API products, AI tools). Flat pricing works when usage patterns are similar across customers (simple utilities, single-user tools). For micro-SaaS in the $5-$50/month range, flat pricing with 2-3 tiers (personal, team, business) is the most common and simplest to implement.

What gross margin should a micro-SaaS product target?

As a reference, Damodaran's January 2026 data puts gross margin for listed US system and application software companies at 71.7%. Per-user AI API costs pull a micro-SaaS below that; what matters is whether what is left covers marketing, development, support and your own pay, because no amount of growth fixes a margin eaten by per-user costs. Buyers of small SaaS businesses also look closely at gross margin when they set a multiple. Note that this calculator's margin includes your fixed costs, so it is stricter than a pure gross margin.

How do I validate my pricing before committing?

Three practical validation methods: First, the 'Mom Test' approach (from Rob Fitzpatrick's book) — ask potential customers about their current spending on the problem, not whether they would pay your price. Second, offer a limited-time launch price at your floor price and gradually increase toward the suggested price for new customers, measuring conversion rate changes at each level. Third, A/B test your pricing page with different price points using tools like PostHog or simple page variants, tracking trial-to-paid conversion rates. A common micro-SaaS pricing mistake is starting too low and never testing a higher price on new customers.

When should I raise prices?

Raise prices when any of these conditions are true: your gross margin is below 60%, your price is significantly below the competitor midpoint without a strategic low-cost positioning reason, you have added substantial features or value since the last price change, customer acquisition is strong but revenue per customer is too low to fund growth, or you have not changed pricing in 12+ months. Grandfather existing customers at their current rate (builds loyalty and reduces churn risk) while increasing prices for new customers.

How does pricing differ for AI-powered micro-SaaS?

AI-powered products have fundamentally different cost structures: the marginal cost of serving each user is higher due to AI API token costs, which means the traditional SaaS advice of 'price for value, not cost' must be tempered by real per-user economics. A product priced at $10/month with $4/user in AI API costs has only $6/user gross margin, compared to a traditional SaaS product at the same price with $0.50/user costs and $9.50 margin. This means AI product pricing must be more carefully calibrated to unit economics. Strategies to improve AI product margins include using cheaper models for routine queries, implementing caching, and tiering plans by usage volume so heavy users pay proportionally more.

Is this tool free and private?

Yes. All calculations run entirely in your browser. No data is sent anywhere. No signup or account required.

Is this professional pricing or business advice?

No. This tool provides pricing estimates based on cost-plus methodology and competitive anchoring. Optimal pricing depends on positioning strategy, customer segments, willingness-to-pay research, competitive dynamics, and other factors not fully captured by any calculator. Use the outputs as a starting framework and validate with actual customer data.

  • 16 min read The AI Micro-SaaS Unit Economics Report 2026

    AI micro-SaaS unit economics 2026: engine-computed margins by model tier (77% premium, 91% mid, 98% budget), full-stack cost, break-even price.

  • 13 min read Pricing AI Features: Cost-Plus vs Value-Based

    Pricing AI features: cost-plus breaks because token cost per customer can vary 100-fold; a per-seat base plus a usage cap holds margin and room for value.

  • 7 min read How to Set Up Pricing Tiers

    How to set up SaaS pricing tiers: three tiers mapped to three segments, a value metric that scales with customer success, and the middle tier as anchor.

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The same calculation as a JavaScript module you can import. It runs where you import it, with no request, key or rate limit.

import { compute } from "https://aibizhub.io/engines/micro-saas-pricing-engine.js";

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