Retail Price Elasticity

An important concern of retailers is to know the effect of sales of marketing activities such as price discounts or special promotions. Since the advent of optical scanner data, retailers have utilized estimates of the effects of marketing mix variations to better manage inventory, shelf-space allocation, and promotional activities (Food Marketing Institute 1985; Petrison 1987). The effects of marketing activities on retail sales are frequently assessed by estimating sales-response functions (e.g., Moriarity 1985). Price elasticity explains the amount change in goods shopped by a retailer because of change in unit price. But a crucial decision would be for a retailer is to know about his goods how elastic they are really in quantitative terms because which helps him to change prices accordingly to increase profits.

The following section gives a fair idea for a retailer about how elastic are his products.

o Necessities tend to have inelastic demand

o Luxuries tend to have elastic demand

o Demand is elastic when there are close substitutes

o Elasticity is greater when the market is defined more narrowly: food vs. ice cream

o Elasticity is greater in the long run, as people are more free to adjust their behaviour

o How the price elasticity does is relevant to a retailer from revenue prospect?

Some of the empirical researches have show that elasticity is clearly related to revenue generated. The following section gives us idea of elasticity relation to revenue.

o Revenue increases if demand is inelastic,

o Revenue decreases if demand is elastic, and

o Revenue stays the same if demand is unit elastic

Price elasticity provide grocers with the ability to define and optimize consumer-centric pricing strategies based on consumer, demand, and market insights:

o Define strategies and optimize prices across the complete product lifecycle – initial, everyday, promoted, and markdown pricing-given local market demand and competition

o Determine the right balance of EDLP and Hi-Lo pricing

o Validate and refine price tiers, image items, and category roles

o Leverage superior insights into price elasticity, consumer demand and competitor actions


1. Food Marketing Institute (1985), Retailer Applications of Scanning Data, Washington,D.C.:Research division, Food Marketing Institute.

2. Petrison, Lisa (1987),”Retailers Scan Data Horizon,” Adweek’s Marketing Week 28, 53(November), 16-17.

3. Moriarity, Mark M.(1985),”Retail Promotion Effects on Intra- and Interbrand SalesPerformance,” Journal of Retailing, 61 (3),27-47.

Source by Jethendra B K