Analysis of Sales Promotion Effects on Household Purchase Behavior

elasticities can be attributed to three sets <strong>of</strong> exogenous variables: category factors, brand
factors, and consumer factors. As Gupta (1988), they concluded that switching (i.e., secondary
demand) is the most important effect <strong>of</strong> a promotion. However, that effect is not as dominant
as reported by previously reported. <strong>Promotion</strong>s can also have a significant effect on primary
demand for a product (i.e., purchase time and quantity choice). Furthermore, the magnitude <strong>of</strong>
primary and secondary demand effects were found to vary substantially across brands and
categories. The choice elasticity varied from 49% for butter to 94% for margarine. The time
elasticity varied from 1% for liquid detergents to 42% for butter. The quantity elasticity varied
from almost 0% for margarine to 45% for c<strong>of</strong>fee. The overall average decomposes elasticities
into 75/11/14 percent for respectively brand/time/quantity. Up to 70% <strong>of</strong> this variance was
explained by the category-, brand-, and consumer-specific factors, in this order <strong>of</strong> importance.
All refrigerated products had much higher timing effects than quantity effects. All storable
products showed the opposite patterns. Recall that Gupta (1988) obtained different results for
the storable product category c<strong>of</strong>fee. Bell et al. (1999) attributed this to two factors. First, they
use newer and different data. Second, while Gupta’s model addresses the ‘when’ question <strong>of</strong>
purchase timing, Bell et al. focus on the ‘whether’ question. No differences were found in
brand choice elasticities related to storability. The overall elasticity decomposition
distinguishing between storable and nonstorable products resulted in 75/3/22 for storable
products versus 75/17/8 for nonstorable products.
But, as noted and researched by Van Heerde et al. (2001, 2002), there is a big
difference between the promotional bump decomposition depending on whether this is
derived using elasticities or unit-sales effects. Researchers decomposing the sales promotion
elasticity into brand switching, purchase quantity, and purchase timing (e.g., Gupta 1988,
Chiang 1991, Chinatagunta 1993, Bucklin et al. 1998, Bell et al. 1999) concluded on average
that 74% is due to brand switching (secondary demand effects) and the remainder is due to
timing acceleration and quantity increases (primary demand effects). Van Heerde et al. (2001,
2002) argued that the decomposition <strong>of</strong> unit sales effects is theoretically and managerially
more relevant than the decomposition <strong>of</strong> elasticities. The former decomposition considers
promotional sales effects in terms <strong>of</strong> comparable units (unit sales), whereas the latter is
constructed in terms <strong>of</strong> percentage changes <strong>of</strong> non-comparable units (probabilities and
purchase quantities). Van Heerde et al. (2001, 2002) transformed the elasticity-based results
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