The measurement and utility of brand price elasticities

Abstract

The price elasticities of brands have been measured by analysis of store-level data, field experiments and regression analysis. These methods are reviewed and the main findings are reported. Price elasticities vary in response to a variety of market conditions but there are also product-specific factors that are related to elasticity. The price elasticities of the leading five brands in 100 categories were established by regression. Elasticities were found to be widely spread and 19% were positive. Stronger regression estimates tended to produce higher elasticities. The study also revealed: greater price elasticity magnitudes for new brands; no difference between growing and declining brands; brand leaders were slightly less sensitive to price changes than other brands; higher adspend was associated with lower price sensitivity.

Market Share is Correlated with Word-of-Mouth Volume

“…In the field of advertising, a positive relationship between advertising expenditure and market share has been reported (Balasubramanian and Kumal, 1990; Farris and Reibstein, 1979), giving rise to the managerial rule to match share of voice with market share. Another study found that the advertising expenditure for leading brands in 100 categories was, on average, approximately twice as much as that for the mean of the next four brands in market share order (Hamilton et al, 1997). Bigger brands also have wider distribution and, it seems, increments in distribution work with increasing effect as brands become bigger (Reibstein and Farris, 1995).…”

Assessing the impact of a very successful price promotion on brand, category and competitor sales

“…Danaher and Brodie (2000) analysed 22 grocery categories and calculated an average elasticity of −2.3. Hamilton et al (1997) examined data on 500 brands to find an average elasticity of −1.3, or −1.9 if only the negative price elasticities were included. The overall average appears to be approximately −2.5.…”

“…Woodside and Waddle (1975) reported that non‐advertised price cuts could generate a 66 per cent volume increase, but this figure rose to 400 per cent when the price cut was accompanied by in‐store advertising (p. 33). Hamilton et al (1997) reported that price cuts coupled with additional promotional support could increase sales by between 173 per cent and 545 per cent (p. 286). Totten and Block (1994) reported that a deep price cut of 45 per cent supported by feature or display advertising could increase volume by approximately 280 per cent, and possibly as much as 400 per cent (p. 70, Figure 4.5).…”

Demand Forecasting: Evidence-Based Methods

“…For example, a meta-analysis by Tellis (1988) of price elasticities of demand for 367 branded products, estimated using econometric models, reported a mean value of -2.5. Hamilton et al's (1997) analysis of 406 brand price elasticities also reported a value of -2.5. Estimates can also be made about other measures of market activity, such as advertising elasticity.…”