Promotional Elasticities and Category Characteristics

(Research Paper)

Author Chakravarthi Narasimhan, Scott A.

Neslin and Subrata K. Sen

Objective

• To study the relationships between the product category characteristics and average brand promotional elasticity within the category and present a framework for understanding these relationship and use it to generate hypotheses by studying 108 product categories.

Introduction

• Attempt to understand how the average increase in brand sales resulting from these promotions can be explained by category characteristics like-

o Category penetrationo Average inter purchase timeo Price, Market share of private label brandso Number of brands in the categoryo Susceptibility to impulse buyingo Susceptibility to consumer stockpiling.

Gap

• We consider variables such as impulse buying and ability to stockpile that is not considered in Fader and Lodish study.

Gap

Promotional elasticity vary significantly from category to category so-

o What accounts for these differences?o Are they related to how widely used the

category is?o How frequently it is purchased?o How easy the category is to stockpile?

Literature Review

Three Important studies in the promotions literature- Fader and Lodish (1990): Relate category characteristics to category volume purchased on

deal. They investigate 331 categories and report that categories with -o Higher category penetrationo Shorter inter purchase timeso Higher private label shareo And lower price levels

Have high volume sold on deal

Cont’d Raju (1992): Relate category characteristics to temporal variation in

category sales by studying variables such as -o Expensiveness or priceo Bulkiness,o Level of competition and promotional efforts. He covers 63 categories and finds that category with high

variability are promoted steeply, but not frequently, and are less expensive, but not bulky and highly competitive.

Cont’d

Bolton(1989): Investigates the relationship between brand-price

promotion elasticity and category characteristics like –o Price levelo Variation in priceo Brand market shareo Manufacturer advertisingo Brand use of couponso Displays and features

Cont’d

She investigates four product categories and uses data from 12 stores and finds that highly elastic brands have lower market share, less category and brand display activity.

Hypothesis

• HI: Promotional response is positively related to the level of category penetration.

• H2:The positive relationship between promotional response and category penetration is especially strong for featured price cuts.

• H3:Promotional response is negatively related to the category's average inter purchase time.

Cont’d• H4:Promotional response is positively related

to the degree of impulse buying in the product category.

• H5:The positive relationship between impulse buying and promotional response is especially strong for display promotions.

• H6:Promotional response is positively related to the ability of a product category to be stockpiled.

Methodology

Under this we are measuring data according to these hypothesis.

o Promotional response. • Category characteristics from panel data. • Category characteristics from survey data.

Methodology

• The IRI study covers 164 categories and incorporates data from 2400 grocery stores collected during 1988. Information on weekly sales was collected with in-store checkout scanners.

• Feature and display data were collected by IRI staff visiting each store each week and monitoring major daily newspapers and store fliers.

• The percentage sales increase for each promotion in each category over the one-year time period was measured using IRI's Promotion Scan' methodology.

Cont’d

• A multiplicative regression model was formulated for each category, in which the percentage sales increase due to promotion was the dependent variable, and descriptors of the promotion (e.g., feature, display, amount of price cut) served as independent variables.

• Depending on the type of promotion, the coefficients from this regression were used to estimate the average response to a brand promotion in the category.

Cont’d

• Average percentage sales increases were calculated for a pure 15% price cut, a 15% price cut accompanied by feature advertising, and a 15% price cut accompanied by a special in-store display.

• Category characteristics from survey data-o Impulse buyingo stock-pile

Analysis

• We used regression analysis to test six hypotheses.

Dependent variables are –o Featured price cut elasticityo Displayed price cut elasticityo Pure price cut elasticity

Independent Variables

• Each regression took the following form –

Independent Variables

Results (3 points)

1) Display price cut elasticities are the highest on average, whereas pure price cut elasticities are the lowest.

2) Good variation in the three elasticity measures, as is indicated by the standard deviations. How-ever, the pure price cut elasticities exhibit somewhat lower variation than do the displayed price cut and featured price cut elasticities.

Cont’d

3) Fairly strong correlations exist among numbers of brands, category penetration and inter purchase times.

Limitations

• The limitations has been in the research is that it is difficult to find categories that meet all these criteria because the promotion for each product category has different response.

• The research has been the mixture of old research which is secondary data and new which is primary data.

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