Price elasticity of demand calculator

The formula this uses

This calculator uses the midpoint (arc) method, which divides each change by the average of the two values rather than by the starting value. That matters: with the simple method, moving from $100 to $92 and back from $92 to $100 give different elasticities for the same pair of points. The midpoint method is symmetric, so it does not depend on which price you call the starting one.

elasticity = ((Q1 − Q0) / ((Q1 + Q0) / 2))
            ÷ ((P1 − P0) / ((P1 + P0) / 2))

Example: P0 = $100, Q0 = 420, P1 = $92, Q1 = 505
  ΔQ / avgQ = 85 / 462.5  =  0.1838
  ΔP / avgP = −8 / 96     = −0.0833
  elasticity = 0.1838 / −0.0833 = −2.21

Elasticity is not the decision — break-even volume is

An elastic product can still be a bad one to discount. What decides it is contribution per unit. If a $100 product carries a 35% margin, contribution is $35. Cut the price to $92 and contribution drops to $27, a 23% fall. To hold gross profit flat you now need 420 × 35 ÷ 27 = 545 units, which is a 29.8% volume increase. That is the number the calculator shows as break-even volume, and it is the number worth arguing about in a pricing meeting.

Estimating elasticity without a formal experiment

Most teams never run a clean price test. The practical alternative is to use price changes that already happened: find a SKU whose price moved and whose volume you can measure before and after, and compute the arc elasticity. Do it across many SKUs and the noise partly averages out.

Be honest about how fragile that estimate is. Every one of these will corrupt it:

• A competitor moved at the same time. This is the big one, and it is why competitor price history matters as much as your own. Without it you are attributing their move to your price.
• Seasonality. A December price cut looks brilliant and a January one looks disastrous, for reasons that have nothing to do with price.
• Stock-outs. Volume that did not happen because there was nothing to ship reads as inelasticity.
• Marketing activity. A price cut that ran alongside a paid push measures the campaign, not the price.
• Category drift. Compare against a control group of similar SKUs that did not change price, or you are measuring the whole category's trend.