Demand appears elastic: quantity changed more than price. Customers are relatively price-sensitive, so a price increase can cut units sharply and a discount can lift them meaningfully — check profit before discounting.
Download the pricing workbook — from your current inputs
A 10-sheet Excel workbook with live formulas. Projections are estimates based on your inputs — not guaranteed outcomes.
What this tool shows
Then test whether a price increase or discount is likely to raise revenue, protect profit, and suit your costs.
Midpoint (arc) and simple PED, with elasticity classification and interpretation
Revenue before/after and the directional result of a price change
A business pricing simulator: estimated quantity, profit, margin, and break-even
A −30%…+30% scenario table with best-revenue, best-profit, and lowest-risk markers
Ecommerce/Retail, SaaS, and Local-service models with fees, churn, and capacity
A demand-point chart, revenue/profit bars, and an elasticity gauge
A formula-driven 10-sheet Excel pricing workbook
Formula-backed Revenue & profit impact Scenario simulator Midpoint + simple PED 10-sheet XLSX Works on any device
Your elasticity value falls into one of three bands, and each band points the price a different way. |PED| above 1 means demand is elastic — quantity changes more than price, so customers are relatively price-sensitive: a price increase can cut revenue and a discount can raise it, though profit needs checking separately, because more units at a lower margin can still shrink profit. |PED| below 1 means demand is inelastic — quantity moves less than price, so raising price usually increases revenue, though long-term churn or customer satisfaction is worth watching. |PED| near 1 is unit elastic — revenue stays broadly the same either way, so the decision should turn on profit and customer mix rather than revenue. The sign is usually negative, since price and quantity normally move in opposite directions, and business interpretation typically uses the absolute value.
So the band, not intuition, sets the direction: at −1.7 the discount is the revenue-raising move, at −0.7 the increase is, and at −1.0 revenue lands in much the same place either way. Revenue is only half the picture — a discount that lifts revenue can still cut profit once costs are counted, which is what the pricing simulator and scenario modes are for.
The midpoint formula answers −1.70 whichever way the price moved
Elasticity is the percentage change in quantity demanded divided by the percentage change in price. The midpoint (arc) method takes the average of the two prices and the average of the two quantities as its base, which is why it returns the same result whether price rose or fell between the two points; the simple method uses the initial values instead, so the two directions disagree. The simulator then projects quantity as current × (1 + elasticity × % price change), capped at zero, and computes revenue and gross profit from it.
Midpoint (arc) PED
[(Q2−Q1)/((Q1+Q2)/2)] ÷ [(P2−P1)/((P1+P2)/2)]
Recommended — same result whether price rises or falls.
Simple PED
(% change in quantity) ÷ (% change in price)
Uses the initial values as the base.
Revenue
Revenue = Price × Quantity
Compare revenue before and after the price change.
Estimated quantity
Q = Current × (1 + elasticity × %ΔP)
Elasticity is usually negative, so a price rise lowers quantity.
Run those four lines once on the defaults: price rises from $100 to $110 and units sold fall from 1,000 to 850. Midpoint PED = (−150 ÷ 925) ÷ (10 ÷ 105) ≈ −1.70, elastic since |PED| is above 1. Revenue before = $100 × 1,000 = $100,000; revenue after = $110 × 850 = $93,500, so the $10 rise gave up 150 units and $6,500 of revenue — exactly what elastic demand predicts. Whether profit also fell depends on the margin gained on each remaining unit; the pricing simulator answers that from your costs.
Revenue peaks at −20%, profit peaks at +10%
Every row uses the calculator's defaults: price $100, 1,000 units, elasticity −1.5, variable cost $45, fixed cost $10,000.
Revenue and gross profit at seven price changes on the default inputs
Price change
Price
Units
Revenue
Gross profit
−30%
70
1,450
101,500
26,250
−20% best revenue
80
1,300
104,000
35,500
−10%
90
1,150
103,500
41,750
0% current
100
1,000
100,000
45,000
+10% best profit
110
850
93,500
45,250
+20%
120
700
84,000
42,500
+30%
130
550
71,500
36,750
The revenue peak sits at a discount and the profit peak at an increase, so a price set on revenue alone moves the wrong way. That profit column exists only because a variable and a fixed cost were entered: a pricing decision needs cost data, not just revenue.
A +10% rise can lose 15.4% of units and still break even
At the default 55% contribution margin this needs no elasticity estimate at all.
Break-even unit loss at four price rises on a 55 percent contribution margin
Price rise
Units you can lose and still break even
Implied elasticity at that point
+5%
−8.3%
−1.67
+10%
−15.4%
−1.54
+15%
−21.4%
−1.43
+20%
−26.7%
−1.33
Two clean periods, one SKU, nothing else moving
Two periods are enough; keeping them clean is the whole job.
Use two periods where the price genuinely changed and nothing else did.
Measure in units, not revenue — revenue already contains the price.
Run one SKU at a time; a mix shift masquerades as elasticity.
Discard any window containing a promotion, a stockout or a competitor's price move.
Past demand does not guarantee future demand — competitors and seasonality matter, so re-measure rather than reuse an old figure.
A price test that moves anything else measures nothing
Hold everything but price still, or the lift you measure belongs to something you did not record.
Hold a control group or a control region at the old price.
Run it for at least one full purchase cycle.
Freeze promotions, ad spend and assortment for the duration.
Fix the sample size before starting — a small lift needs many orders to separate from noise.
An elasticity measured between $100 and $110 says nothing about $150
A value measured between two nearby prices describes that stretch of the demand curve and nothing else. The same product is usually inelastic near its current price and elastic well above it, so one estimate stretched across a wide move is the most common misuse — it is the sharpest limitation on this page, and moves beyond about 30% are where the projection stops being reliable. Demand response also differs by business model: SaaS churn does not behave like one-time-purchase elasticity, which is why the SaaS mode asks for a churn sensitivity rather than reusing a retail figure.
What you get here is own-price elasticity of demand only — how the quantity of a good responds to its own price. Cross-price elasticity (the response to a substitute or complement’s price), income elasticity (the response to income), and price elasticity of supply are related but distinct concepts with their own formulas, and this calculator does not compute them. It cannot tell you why demand moved either: this is an educational and planning tool, not financial, tax, or business advice.
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Everything on this page is arithmetic on the two price and quantity pairs, or the elasticity estimate, that you enter. Nothing is fetched: no demand data, no competitor prices, no category elasticities.
Price elasticity of demand is an economic model taught in the textbooks cited below, not a rate or a threshold set by any authority. There is no government body, regulator or standards organisation that publishes the elasticity of your product, and the classification bands at 1.0 come from the definition of the ratio itself rather than from any rule. What statistical agencies do publish is estimates for specific markets, measured from real data - the last two sources are exactly that, and they are worth reading mainly to see how narrowly each estimate is scoped.
This calculator is for educational and planning purposes only. It does not guarantee customer behaviour, revenue, profit, or business outcomes. Real pricing decisions should consider competitors, costs, taxes, customer segments, brand strength, inventory, seasonality, and legal/compliance requirements.
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Authorship & verification
Created and maintained by Jay Sudha, finance educator.