Verified against ChatGPT · 2026-08-14
Pressure-test a proposed price change against margin impact and what it implies about customer response
Analyzes a proposed price change by working through the exact margin math and naming the customer-response assumption implicit in it, instead of just validating whatever price point was proposed.
The prompt
Ready to copy — highlighted parts are example details you can swap.
Analyze the proposed pricing change below by working through the actual math and naming the assumption about customer behavior it depends on — do not simply validate the proposed price as reasonable; the job is to show what has to be true for it to work.
CURRENT PRICING
$29/unit price, $11/unit variable cost.
PROPOSED CHANGE
Raising the price to $34/unit.
CURRENT VOLUME AND MARGIN
Roughly 2,400 units/month at current price.
REASON FOR THE CHANGE
Input costs have risen and margin has been eroding; competitors in this space charge closer to $35-38.
STEP 1 — DIRECT MARGIN MATH
Calculate current total contribution (price minus variable cost, times volume) and the new contribution if volume stayed exactly the same at the new price. Show this as the immediate, mechanical effect before any consideration of how customers might actually respond.
STEP 2 — BREAK-EVEN VOLUME CHANGE
If this is a price increase, calculate the maximum volume drop that could occur before total contribution falls below the current level — this tells the requester how much customer attrition the price increase can tolerate before it becomes a net loss. If this is a price decrease, calculate the minimum volume increase needed to at least maintain current total contribution — this tells the requester how much new volume the discount needs to generate before it pays for itself.
STEP 3 — NAME THE ASSUMPTION
State plainly what has to be true about customer price sensitivity for this change to be a good idea, given the tolerance calculated in step 2 — is the implied tolerance a small, plausible shift, or does it require an aggressive assumption about how customers will respond that isn't obviously justified by anything in the reason given for the change? Do not assert a specific price elasticity number unless the requester provided one; naming the required tolerance in plain terms ("volume could drop by up to 18% and this would still be worth it" or "this needs volume to grow by at least 30% just to break even") is more honest than inventing an elasticity coefficient with no data behind it.
OUTPUT FORMAT
1. Direct margin math: current contribution vs. new contribution at unchanged volume.
2. Break-even volume tolerance, stated as a specific percentage.
3. Plain-language read on whether that tolerance looks like a safe or aggressive bet, tied explicitly to the stated reason for the change.Customize
Optional — swap in your own details for the highlighted parts above.
Why this works
The break-even volume tolerance calculation is the mechanism that makes this prompt useful rather than just a margin calculator, because it converts an abstract question ("is this price change a good idea?") into a concrete, checkable claim ("volume can drop by up to 18% before this becomes a worse deal than the status quo") that the requester can actually hold up against their own judgment of how customers are likely to react. Refusing to assert a specific price elasticity coefficient unless the requester supplied real data is an important honesty constraint, because price elasticity is genuinely hard to estimate without actual historical data on how volume responded to past price changes, and a model asked to analyze pricing will otherwise readily generate a plausible-sounding elasticity number that has no real basis — presenting a fabricated coefficient with false precision would make the analysis look more rigorous than it actually is. Explicitly tying the plain-language read on tolerance back to the stated reason for the change (rising input costs, competitor pricing) is what keeps the conclusion grounded in this specific decision rather than a generic pricing-strategy lecture — the same 18% volume tolerance is a comfortable bet in a market where competitors already charge more, and a much riskier one if the rationale given doesn't actually support customers tolerating a higher price. Separating the purely mechanical margin math (step 1) from the behavioral-assumption framing (step 3) matters because the two are genuinely different kinds of claims — the math is simply arithmetic that either party can verify, while the customer-response question is a judgment call that depends on market knowledge the model doesn't have, and conflating the two would make an uncertain judgment look as solid as verified arithmetic.
What you get back
Current contribution: ($29 - $11) x 2,400 = $43,200/month. New contribution at unchanged volume: ($34 - $11) x 2,400 = $55,200/month. Break-even volume tolerance: volume could fall to roughly 1,878 units (a 21.75% drop) before contribution falls back to the current $43,200 level. Given that competitors already price at $35-38, a 21.75% volume-drop tolerance looks like a reasonably safe bet rather than an aggressive one — the stated rationale supports this move.
Verified against
ChatGPT GPT-5.1 · 2026-08-14
Changelog
- 2026-08-14 — Initial publish, verified against ChatGPT GPT-5.1.
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