Price Test Calculator
Turn a two-price test into price elasticity, profit per visitor and an estimate of the profit-maximizing price.
Your numbers
Your result · updates as you type
Profit-maximizing price (estimate)
$33.50
About $555 profit per 1,000 visitors, against $540 at $30.00 and $552 at $35.00.
- Price elasticity (arc)
- -1.44
- Profit per 1,000 visitors
- A $540 · B $552
- Conversion difference
- Not significant (p = 0.064)
The gap in conversion could still be chance (p = 0.064). Keep the test running until each price has more orders before you commit, and treat the price above as a direction, not an answer.
Breakdown
- Conversion at $30.00
- 3%
- Conversion at $35.00
- 2.4%
- Arc elasticity (% change in demand ÷ % change in price)
- -1.44
- Constant-elasticity exponent
- -1.45
- Demand is
- Elastic: buyers react strongly to price
From two prices to a best price
A price test shows each price to a similar group of visitors. The calculator turns units per visitor into a demand curve, then finds the price where profit per visitor peaks.
Example: the default numbers
- $30 to 5,000 visitors
- 150 sales (3.0%)
- $35 to 5,000 visitors
- 120 sales (2.4%)
- Unit cost
- $12
Elasticity is −1.44. Profit per 1,000 visitors is $540 at $30 and $552 at $35. The straight-line model peaks at $33.50 ($555 per 1,000 visitors). But p = 0.064, so the conversion gap could still be chance.
Straight line or constant elasticity?
Two points can't show the true shape of demand. The straight line is cautious and keeps the best price close to what you tested. Constant elasticity assumes buyers react the same to every 1% change, which suggests bolder prices and only has a peak when elasticity is below −1.
If the models disagree a lot, test a third price between them.
Running a fair price test
- Split traffic, not time. Showing one price this week and another next week mixes the price with seasonality.
- Count units per visitor, not conversion rate alone, if people buy several at once.
- Wait for significance. The calculator runs a two-proportion z-test on conversion. Aim for p below 0.05 before acting.
- Tell the truth at checkout. Every visitor must pay the price they saw. Test on new products or new traffic if showing different prices would upset returning customers.
Questions people ask
What does a price elasticity of −1.44 mean?
A 1% price rise cuts units sold by about 1.44%. Below −1, demand is elastic: buyers react strongly. Between 0 and −1 it's inelastic, and a price rise usually increases revenue.
How many visitors do I need for a price test?
Enough that each price gets dozens of orders or more. The p-value tells you when the difference in conversion is unlikely to be chance.
Why maximize profit instead of revenue?
A lower price can raise revenue while earning less, because each sale carries your costs. Profit per visitor is the number that pays the bills.
How do I run a price test on Shopify or WooCommerce?
Use a price testing app, or split traffic between two landing pages that sell the product at different prices. Enter each group's visitors and sales here.
Related tools
Want this builtinto your store?
I'm Emmanuel, a Shopify and WooCommerce developer. If this tool pointed at something you'd rather have fixed for you (a faster store, cleaner product data, a migration, a custom feature), send me a note.
Emmanuel Asika
Shopify & WooCommerce developer, Dublin
I build and fix online stores: new builds, migrations, speed, SEO and the custom bits apps can't do.
Last reviewed 30 September 2026.