Price Elasticity Calculator
Enter two price points and how many units you sold at each to calculate your price elasticity of demand and estimated revenue impact. Free, no signup required.
Elasticity coefficient
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Revenue impact
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How to use this calculator
Find a product where you changed the price at some point and know roughly how many units sold before and after. Enter the original price and units sold as “Price A” and the new price and units sold as “Price B.” The calculator uses the midpoint (arc elasticity) method, which gives a consistent result regardless of whether the price went up or down.
Worked example
Say a product sold 100 units per month at $20 (Price A), and after raising the price to $24 (Price B), it sold 88 units per month. Percentage change in quantity, using the midpoint method: (88 − 100) / ((88 + 100) / 2) = −12.8%. Percentage change in price: (24 − 20) / ((24 + 20) / 2) = 18.2%. Elasticity = −12.8% / 18.2% = −0.70. Since |−0.70| is below 1, demand is inelastic: the price increase grew revenue even though unit sales dropped a little.
What the elasticity coefficient means
- Elastic (|E| > 1): your customers are price-sensitive. A price increase reduces units sold by more than the percentage increase - revenue may fall.
- Inelastic (|E| < 1): your customers are relatively price-insensitive. There may be room to raise prices without losing many sales.
- Unit elastic (|E| ≈ 1): demand moves proportionally with price - revenue stays roughly flat as price changes.
This two-point calculation is a useful sanity check, but it only reflects one price change. Zorin fits a full demand curve from your complete order history, automatically excludes promotional sales spikes that would skew the result, and tells you the exact price that maximizes profit for every product in your catalog.
Frequently asked questions
What formula does this calculator use?
The midpoint (arc elasticity) method: percentage change in quantity divided by percentage change in price, where both percentage changes are calculated against the average of the two values rather than the starting value. This gives the same result whether the price went up or down, unlike a simple before/after percentage calculation.
What counts as a good number of units sold to compare?
There's no strict minimum, but a few weeks to a couple of months of sales at each price gives a steadier read than a day or two, which can be skewed by normal day-to-day variance. If either period included a sale, promotion, or stockout, the result will reflect that distortion, not price sensitivity alone.
Why does my elasticity number come out positive instead of negative?
Demand curves slope downward for almost all products, so a properly calculated elasticity is negative: price up, quantity down. If your result comes out positive, double check that Price A and Price B (and their matching unit counts) weren't swapped when entering the data.
Can I use this for a product that's never had a price change?
No. Elasticity measures how quantity responds to a price change, so you need at least one instance of an actual price change in your sales history. Without that, a Van Westendorp survey is a better starting point for a launch price than a calculator that needs price variation to work.
Is a two-point calculation as reliable as a full regression?
No, and this calculator is meant as a quick sanity check, not a final answer. A two-point calculation can't separate the effect of the price change from other things happening at the same time (seasonality, promotions, competitor moves), and it has no way to tell you how much to trust the result. A regression fit across many price points, run automatically per SKU, does both.