A major concern for retailers is knowing the effect on sales of marketing activities, such as price discounts or special promotions. Since the advent of optical scanner data, retailers have used 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 often assessed by estimating sales response functions (eg Moriarity 1985). Price elasticity explains the change in the quantity of goods purchased by a retailer due to the change in unit price. But a crucial decision for a retailer is knowing how elastic their products really are in quantitative terms, as that helps them to change prices accordingly to increase profits.
The next section gives a retailer a fair idea of how elastic their products are.
o Needs tend to have inelastic demand
o Luxury items tend to have elastic demand
o Demand is elastic when there are close substitutes
o Elasticity is higher when the market is more narrowly defined: food vs. ice cream
o The elasticity is greater in the long run, since people are freer to adjust their behavior
o How is price elasticity relevant to a retailer from a revenue perspective?
Some of the empirical research has shown that the elasticity is clearly related to the income generated. The next section gives us an idea of the relationship between elasticity and income.
o Revenues increase if demand is inelastic,
o Revenues decrease if demand is elastic, and
o Revenue stays the same if demand is unit elastic
Price elasticity provides grocers with the ability to define and optimize consumer-focused pricing strategies based on consumer, demand, and market information:
o Define strategies and optimize prices throughout the entire life cycle of the product: initial, daily, promoted and discounted prices, given the demand and competition of the local market.
o Determine the correct balance of EDLP and Hi-Lo prices
o Validate and refine price levels, image elements, and category roles
o Leverage superior insights into price elasticity, consumer demand, and competitor actions.
References:
1. Food Marketing Institute (1985), Retailer Applications of Scanning Data, Washington, DC: 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), “Effects of Retail Promotion on Sales Performance Within and Between Brands,” Journal of Retailing, 61(3), 27-47.