Price Elasticity of Demand: Formula and Examples

Price elasticity of demand (PED) measures how much the quantity demanded changes in response to a price change. 

It is calculated as:

PED = (% Change in Quantity Demanded) ÷ (% Change in Price)

When demand is elastic (PED > 1), even small price changes cause significant shifts in sales. When demand is inelastic (PED < 1), price changes have little effect on demand. PED is categorised into elastic, inelastic, unitary, perfectly elastic, and perfectly inelastic demand.

For businesses, understanding PED is essential for optimising pricing, maximising revenue, and planning promotions. It sets the foundation for strategic decisions across competitive markets. In this blog, you will delve deeper into the price elasticity of demand formula, types, examples, and how to estimate elasticity.

Price Elasticity of Demand Formula

The price elasticity of demand formula measures how demand responds to price changes:

Price Elasticity of Demand (PED) = (% Change in Quantity Demanded) ÷ (% Change in Price)

% change in quantity demanded = (Q₂ – Q₁) ÷ Q₁ × 100

% change in price = (P₂ – P₁) ÷ P₁ × 100

For larger price changes, the midpoint (arc) method is more accurate:

(ΔQ ÷ average Q) ÷ (ΔP ÷ average P)

Price elasticity is usually negative because price and demand move inversely, but economists express it as an absolute value. Applying the correct price elasticity of demand formula enables precise revenue forecasting and pricing strategies.

Types of Price Elasticity of Demand

There are 5 types of elasticity of demand, each showing how quantity demanded responds to price changes:

Elastic Demand (PED > 1)

A small price cut causes a significant rise in demand. For example, for fashion apparel, a 10% discount may increase sales by 30%.

Inelastic Demand (PED < 1)

Price changes have little effect on demand. For example, salt – even a 20% price hike barely reduces purchases.

Unitary Elasticity (PED = 1)

Price and demand change proportionally, keeping total spending constant. Example: mid-range dining.

Perfectly Elastic (PED → ∞) 

Any price increase drops demand to zero. Example: highly competitive online marketplaces.

Perfectly Inelastic (PED = 0)

Demand remains unchanged despite price shifts. Example: life-saving medicines like insulin.

Factors Influencing Price Elasticity

The value of price elasticity of demand varies from product to product due to several key factors:

• Availability of substitutes: Products with many alternatives (e.g., multiple smartphone brands) show more elastic demand.
• Necessity vs luxury: Essentials like basic rice are inelastic, while luxury watches are more elastic.
• Proportion of income spent: High-ticket items, such as premium laptops, tend to have more elastic demand than low-cost goods, like pens.
• Time horizon: Over time, consumers find cheaper substitutes, making demand more elastic in the long run.
• Definition of the market: Broad markets (e.g., food) are inelastic, while narrow ones (e.g., vegan protein bars) are elastic.
• Brand loyalty/habits: Strong loyalty reduces elasticity, though economic downturns can weaken this effect.

If WareIQ helps businesses diversify SKUs and substitute options, they can indirectly influence elasticity and optimise pricing strategies. Learn more about how SKU rationalization supports effective inventory planning and smarter pricing decisions.

How to Estimate or Calculate Elasticity

To calculate the price elasticity of demand, start by collecting data on previous prices and quantities sold. Next, calculate the percentage changes in both using the price elasticity of demand formula:

PED = (% Change in Quantity Demanded) ÷ (% Change in Price)

For greater accuracy, apply the midpoint method:

(ΔQ ÷ average Q) ÷ (ΔP ÷ average P)

You can also utilise regression analysis or advanced tools for analysing large datasets and assessing segment-level elasticity by category, region, or customer type.

Walk-through (simple method):

Here, PED = 20% ÷ –10% = –2 (elastic), meaning demand is highly responsive to price changes.

Walk-through (midpoint method, preferred):

ΔQ/avg Q = 40/220 = 18.18%; ΔP/avg P = –10/95 = –10.53%.

PED = 18.18% / –10.53% = –1.73 (elastic).

Real-World Examples

Here are elasticity examples with proper calculation using the price elasticity of demand formula:

Example 1 (Elastic):

A flash sale reduces the price of headphones from ₹2,000 to ₹1,600 (–20%). Orders rise from 1,000 to 1,500 (+50%).

PED = (%ΔQ) ÷ (%ΔP) = 50% ÷ –20% = –2.5 → highly elastic demand.

Example 2 (Inelastic):

The price of rice increases from ₹40/kg to ₹46/kg (+15%). Sales fall from 10,000 kg to 9,700 kg (–3%).

PED = –3% ÷ 15% = –0.2 → inelastic demand.

WareIQ Use-Case: Managing 10× Order Surge for Leemboodi Fashion

During a festive sales season, WareIQ helped Leemboodi Fashion, an apparel brand, handle a 10× surge in orders across channels, ensuring that 100% of orders were dispatched on time and with 0 seller cancellations.

This case demonstrates how WareIQ supports businesses in capitalising on elastic demand moments. This mirrors an elasticity scenario where rapid sales growth (akin to elastic demand) required robust fulfilment scaling. 

Significance of Price Elasticity of Demand for Businesses

The price elasticity of demand helps businesses craft precise pricing and marketing strategies. By understanding how demand reacts to price changes, companies can decide when to raise or lower prices to maximise profit.

For example, an online retailer selling smart home devices (elastic product) may reduce prices by 10% during a festive sale and see a significant increase in sales volume. In contrast, a seller of essential medicines (inelastic) can implement a slight price increase with minimal impact on demand.

Accurately estimating elasticity using historical price and quantity data allows businesses to forecast revenue shifts, optimise production, and align inventory planning with market behaviour.

How WareIQ Helps Businesses Leverage Price Elasticity of Demand

WareIQ enables businesses to leverage price elasticity of demand insights for better pricing decisions. By integrating real-time sales, inventory, and demand data, WareIQ helps brands test price changes and measure their impact on sales volumes.

For example, a D2C brand using WareIQ can experiment with discounts on seasonal products while monitoring fulfilment speed and stock levels. This allows them to avoid overstocking low-demand items and scale inventory for high-elasticity SKUs.

With WareIQ’s analytics-driven omnichannel fulfilment, businesses can adapt pricing strategies dynamically. This boosts revenue when demand is elastic and protects margins when it is inelastic.

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