What it means
The model starts from a simple observation: customers buy less when the price goes up. A business can sketch this relationship as a demand curve, a line showing how many units it would sell at each price.
It then compares the revenue from selling more units with the cost of producing them. Two ideas are central: marginal revenue is the extra revenue from selling one more unit, and marginal cost is the extra cost of making one more unit.
As long as marginal revenue exceeds marginal cost, selling more adds profit. The best point is where the two are equal.
The model also explains why a firm cannot simply choose the highest possible price. Raising the price increases the margin on each sale but reduces the number of sales, so profit rises and then falls.
The peak is the profit-maximising price. In real businesses the picture is messier.
Demand is hard to measure, competitors respond, and costs change with scale. Even so, the logic helps managers ask the right questions, such as how sensitive customers are to price and how much each extra unit really costs to produce.
Different market structures change the answer. A business in a highly competitive market has little power over price and takes the market price as given, while a business with a unique product has more freedom.
Fixed costs, such as rent, do not affect the best price in the short run, though they determine whether the business makes money overall. For managers outside finance, the practical value is in the questions the model prompts, such as how many customers would be lost if the price rose by 5% and what the next unit really costs once unchanging costs are stripped out.
Answering these with real data usually leads to better pricing decisions than a rule of thumb.
In practice
Real-world examples.
Example
A software company runs price tests on a subscription plan and finds that raising the monthly price from $40 to $50 loses only 5% of customers. Because the extra revenue outweighs the lost customers and costs barely change, profit rises. The company adopts the higher price, and it keeps testing in case customers become more sensitive over time.
Example
A craft brewery has a fixed batch cost and a small cost per bottle. It notices that selling at a lower price boosts volume but that the last few thousand bottles barely cover their cost. It sets its price at the level where the extra bottle just pays for itself.
Example
An airline sells seats at different prices depending on how early customers book. The model explains why: price-sensitive travellers buy early at lower fares, while business travellers pay more for flexibility. The airline earns more than it would with one price, provided it can stop low-fare buyers from using the cheaper seats late.
Formula
Calculation
Profit is maximised where Marginal revenue (MR) = Marginal cost (MC)
Suppose demand is Price = 100 - 0.02 x Quantity, and the marginal cost of each unit is a constant $20. Total revenue is 100 x Quantity - 0.02 x Quantity squared, so marginal revenue is 100 - 0.04 x Quantity. Setting MR equal to MC gives 100 - 0.04 x Quantity = 20, so 0.04 x Quantity = 80 and Quantity = 2,000 units. The price is 100 - 0.02 x 2,000 = 100 - 40 = $60. Profit before fixed costs is 2,000 x (60 - 20) = $80,000, and after fixed costs of $30,000 it is 80,000 - 30,000 = $50,000.Case study
Seen in the real world.
Meridian Home Fitness is an illustrative, fictional company that sells a home rowing machine for $900. Its unit cost is $400, and it sells 5,000 machines a year. The finance manager suspects the price is too low and builds a simple demand estimate from past discounts.
Her analysis suggests that each $50 price rise reduces sales by about 300 units. At $1,000 the company would sell 4,400 units, earning (1,000 - 400) x 4,400 = $2,640,000, compared with the current (900 - 400) x 5,000 = $2,500,000. The higher price adds $140,000.
In this illustrative case, management tests a price of $1,000 in one region first, because the demand estimate is uncertain. Results come close to the forecast, and the price is rolled out more widely. The finance manager records the assumptions behind the decision, including the demand estimate and the unit cost of $400. If component costs rise, she knows exactly which numbers to update, and the model gives her a quick way to see whether the price should change again.
Watch out
Common mistakes.
- Setting price by adding a fixed percentage to cost without considering how customers will respond.
- Letting fixed costs drive the optimal price, when in the short run only marginal cost and demand matter.
- Treating the model as exact, when demand estimates are uncertain and need testing.
Questions
People also ask.
What is marginal cost?
It is the extra cost of producing one more unit, which can differ from the average cost per unit.
Why does profit fall if I raise prices too far?
Because the number of customers drops faster than the gain on each sale, so total profit declines.
Do businesses really use this model?
Most use simplified versions through price testing and margin analysis, even if they do not draw the curves.
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