How does this pricing simulator avoid hallucination?

It uses deterministic arithmetic only: current and simulated MRR/ARR are calculated from your prices, customer volume, and expected customer change percentage. It does not invent elasticity or market behavior.

What is break-even customer change?

Break-even customer change is the customer volume increase or decrease needed so simulated MRR equals current MRR at the new price point. It helps you quantify how much customer loss a price increase can tolerate, or how much gain a price decrease requires.

Can I trust this as a forecast?

Treat it as a scenario model, not a prediction engine. Accuracy depends entirely on the customer change assumption you input.

Free tools

Free Pricing Scenario Simulator

Compare current vs simulated price points and see deterministic MRR/ARR deltas.

Copy-paste outputs

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Tool 01

Pricing Scenario Simulator

Model MRR and ARR impact from pricing changes with explicit customer response assumptions.

Scenario Inputs

Deterministic MRR/ARR impact simulation from your own assumptions.

Current Price ($) *

Simulated Price ($) *

Current New Customers per Month *

Expected Customer Change (%)

Negative means fewer customers, positive means more.

Scenario Output

Compare baseline vs simulated revenue impact.

Enter current price, simulated price, and customers to run a scenario.

How it works

Pricing Scenario Simulator: methodology and worked example

How this tool computes its result

calculatePricingScenario is a deterministic, single-formula model: simulatedCustomersPerMonth = currentCustomers * (1 + expectedChangePercent/100), floored at 0. Current and simulated MRR are price × customers, ARR is MRR × 12, and deltas are simple subtraction. A separate breakEvenCustomerChangePercent = (currentPrice / simulatedPrice - 1) * 100 answers a different question than the customer-change input: it is the customer-count change (as a percent) that would be needed at the new price to hold MRR exactly flat, independent of whatever expectedCustomerChangePercent you entered.

Worked example

Current price $99, simulated price $119, 120 new customers/month, expected customer change -10%: simulatedCustomersPerMonth = 120 * 0.9 = 108. currentMRR = $11,880, simulatedMRR = $12,852, mrrDelta = $972 (8.18%). currentARR = $142,560, simulatedARR = $154,224, arrDelta = $11,664. breakEvenCustomerChangePercent = (99/119 - 1) * 100 = -16.81%, meaning customer count could fall by up to 16.81% at $119 before MRR would drop below the $99 baseline.

When not to use this tool

The model applies one flat multiplier to volume with no cohort or time dimension — it does not model churn ramping in over months, existing-customer price grandfathering, or elasticity that varies by segment. It also only simulates "new customers per month," not your full existing customer base, so it understates the revenue impact of a price change if you intended it to apply to the whole book.

Common mistakes

- Leaving "Expected Customer Change" blank, which defaults to 0 — this silently assumes a price increase has zero effect on new signups, which is rarely realistic.
- Entering 0 or a negative value for current price, simulated price, or current customers causes the entire scenario to return null (no output panel) rather than a partial or zero-value result.
- Reading breakEvenCustomerChangePercent as "the customer change you should expect" — it is actually the maximum tolerable customer loss at the new price before MRR falls below today's baseline, a distinct question from the scenario's own delta output.

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