Analysis of Sales Promotion Effects on Household Purchase Behavior

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Table 8.7, and Table 8.8. But what is lacking is a decomposition <strong>of</strong> the promotional bump that provides detailed insights in the relative strengths <strong>of</strong> brand switching, purchase timing, and purchase quantity. Following the line <strong>of</strong> reasoning applied in the major prior studies on promotional bump decomposition (e.g., Gupta 1988, Bell et al. 1999, Van Heerde et al. 2001, 2002), three different response patterns can occur when a promotion takes place. Current purchases can be borrowed from future purchases (changes in purchase time; purchase time acceleration or purchase time deceleration), current purchases can be drawn from planned current other brand purchases (unchanged purchase timing combined with brand switching), or regular customers purchase a different quantity (unchanged purchase timing, no brand switching). Two different approaches have been applied in prior studies to decompose the promotional sales, the elasticity based decomposition (e.g., Gupta 1988, Bucklin et al. 1998, Bell et al. 1999), and the unit sales based decomposition (Van Heerde et al. 2001, 2002). The elasticity based approach decomposes the total elasticity <strong>of</strong> a brand into brand choice elasticity, purchase time elasticity, and purchase quantity elasticity. Overall, the elasticity based decomposition studies found that the brand switching component is by far the largest (74 percent), followed by purchase quantity (15 percent), and purchase timing (11 percent). It was also found that this decomposition differs across product categories. Van Heerde et al. (2001) demonstrated that decomposing the promotional sales bump using an elasticity approach differs from a unit sales approach. They argue that a temporary price cut for a brand may increase the purchase incidence probability. A large part <strong>of</strong> this typically goes to the promoted brand. However, the authors argue that the nonpromoted brands can also benefit. That is, even though their conditional choice probabilities tend to decrease, other brands may gain in part from the increased purchase incidence probability. As stated by Van Heerde et al. (2001), the elasticity based decomposition does not take this into account whereas the unit sales decomposition does take this into account. In addition, a mathematical explanation for the difference between the elasticity based and the unit sales based approach is derived by Van Heerde et al. (2001). The authors argued that the unit sales decomposition should be preferred. Although differences are found across product categories, there is a clear tendency that brand switch effects derived using the unit sales 181
approach (about one third) are much smaller than what the elasticity based decomposition suggests (about thee fourth). In our study, we are dealing with household data. Applying the unit sales decomposition <strong>of</strong>fers the opportunity to derive an insightful decomposition <strong>of</strong> the promotional bump into the relative influence <strong>of</strong> the three response patterns, change in purchase timing, brand switching, and change in purchase quantity. Figure 8.1 depicts the decomposition <strong>of</strong> promotional unit sales into the three response patterns, corresponding to the decomposition used by Van Heerde et al. (2001). The focal point <strong>of</strong> this decomposition is distinguishing between purchases that would have taken place anyway during the current shopping trip, versus purchases that are changed in time. A retailer is interested in the degree to which sales promotions draw consumers to the store, consumers that would not have bought currently from that product category when the promotion would not have been there. Therefore resulting in an increase <strong>of</strong> the current unit sales. <strong>Promotion</strong>al unit sales Figure 8.1:Decomposition <strong>of</strong> promotional unit sales First <strong>of</strong> all, promotional unit sales can come from purchases that are either accelerated or decelerated in time (TA- and TA+). When purchases are not borrowed in time from other shopping trips, promotional unit sales either come from regular consumers (consumers that also purchase the brand when it is not on promotion, QP) or from non-regular consumers (consumers that normally do not purchase the brand when it is not on promotion, BS). The results <strong>of</strong> this decomposition can be found in Table 8.9. The first rows contain the results for each product category separately. The last row contains the decomposition across all product categories. This overall decomposition is derived by decomposing the total 182 Change in time (TA) No change in time Accelerated purchases (TA - ) Decelerated purchases (TA +) Brand switch (BS) No brand switch (QP)
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LINDA H. TEUNTER Analysis</
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Analysis o
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Voorwoord Soms valt de appel echt n
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Contents 1 INTRODUCTION AND OVERVIE
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5.4.2.3.1 Inter Purchase Time .....
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1 INTRODUCTION AND OVERVIEW 1.1 Int
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generally generated from a smaller
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switching, purchase acceleration, c
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strategy change (decrease in promot
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of promotions, or
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characteristics are important in ex
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Chapter 5 are applied to study the
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2 THEORIES OF CONSUMER BUYING BEHAV
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systematically explored the decisio
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the part of the co
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As mentioned before, Figure 2.3 is
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product use coupled with the import
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2.3.2 Stimulus-Response Model Appli
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2.3.2.2 Operant Conditioning In ope
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X is very popular that it will brin
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But, in contrast, economic theory c
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compared to a perceived benchmark -
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High need-for-cognition (NFC) indiv
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2.3.4.2 Literature Overview Our rev
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The previously described research h
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has its deficiencies. Any purchase
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Chandon et al. 2000). But deal pron
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2.4 Concluding Remarks Regarding th
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stimulus-organism-response model) c
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Shoemaker 1987). Several factors ha
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such as display promotions. Althoug
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3.2.3 Type of resi
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3.2.5 Education Education links to
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these advantages therefore could be
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less likely to seek variety. More e
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3.3.1 Store Loyalty Store loyalty s
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more often (probab
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Table 3.12 continued Hypothesis H9a
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4.2.1 Brand Switching Brand switchi
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involvement purchases for most cons
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Neslin (1998), there is a great nee
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are called “attributions.” Attr
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and less than 2 percent by stockpil
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into a unit sales decomposition and
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4.3.4 Storability/Perishability Sto
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Economic theory ignores mental deci
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seeking (cf. Assael 1987, Desphande
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there another factor that is relate
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Pr(event) 90 = 1+ 1 z e − Here Z
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5.4.2 Sales <stron
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It represents the fraction
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96 We measure possible time acceler
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promotional post-promotional purcha
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( 12) CategoryExpansion effect : 10
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PART II EMPIRICAL ANALYSIS 103
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more persons living together and di
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6.4 Linking Household and Store Dat
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Table 6.1 contains the results <str
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The age of the sho
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Table 6.4: Frequency distribution <
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7 EMPIRICAL ANALYSIS ONE: DRIVERS O
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Table 7.1: Operationalization <stro
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during 435 shopping trips more than
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The variables size, age, and cycle
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7.5 Results Drivers of</str
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esponsive the households within tha
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Table 7.3: Relationship promotion r
Page 142 and 143: indication that decreasing marginal
Page 144 and 145: Table 7.6: Relationship promotion r
Page 146 and 147: Table 7.8: Relationship promotion r
Page 148 and 149: Table 7.10: Relationship promotion
Page 154 and 155: 7.5.2.8 Variety Seeking Two intrins
Page 156 and 157: anymore. Therefore it is concluded
Page 158 and 159: Thus, store loyalty and promotion r
Page 160 and 161: dummies add up to one. This implies
Page 162 and 163: Table 7.22: Overview empirical test
Page 164 and 165: enacting-on-impulse hypothesis and
Page 166 and 167: Table 7.23: Summary of</str
Page 168: Table 7.24: Correlation error coeff
Page 171 and 172: another category? Or do households
Page 173 and 174: and unweighted. With respect to the
Page 175 and 176: 164 In general, the average quantit
Page 177 and 178: Purchase frequency is defined as th
Page 179 and 180: Table 8.3: Product category rating
Page 181 and 182: Table 8.4: Pearson correlation betw
Page 183 and 184: We hypothesized that within impulse
Page 185 and 186: measure (PU). Referring to Figure A
Page 187 and 188: Table 8.6: Significant within categ
Page 189 and 190: looked at this promotional bump dec
Page 191: Table 8.8: Differences in promotion
Page 195 and 196: promotions lead to large purchase t
Page 197 and 198: studies. Promotion
Page 199 and 200: Promotional extra
Page 201 and 202: categories revealed that the strong
Page 203 and 204: degree. When households switch bran
Page 205 and 206: specific sales promotion reaction m
Page 207 and 208: increasing (Inman and Winer 1998),
Page 209 and 210: indirectly from promotional purchas
Page 211 and 212: quantity downward for potato chips.
Page 213 and 214: 9.2.2.3 Deal Proneness With respect
Page 215 and 216: 204 related to promotion response.
Page 217 and 218: influenced by out-of</stron
Page 219 and 220: Andrews, K.Z. (1997), “Do Marketi
Page 221 and 222: Blattberg, R.C., Eppen, G.D. and J.
Page 223 and 224: Chintagunta, P. (1993), “Investig
Page 225 and 226: East, R. and K. Hammond (1996), “
Page 227 and 228: Gupta, Sachin and P.K. Chintagunta
Page 229 and 230: Kahn, B.E., Morrison, D.G.and G.P.
Page 231 and 232: Lattin, J.M. and R.E. Bucklin (1989
Page 233 and 234: McAlister, L. and E. Pessemier (198
Page 235 and 236: Petty, R.E. and J.T. Cacioppo (1981
Page 237 and 238: Shimp, T.A. (1990). Promoti
Page 239 and 240: Van Trijp, H.C.M. and J.B.E.M. Stee
Page 241 and 242: Winer, R.S., Bucklin, R.E., Deighto
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APPENDIX A4: Research Overview Tabl
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Table A4.1 continued Article Promot
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� Size of munici
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Table A7.1 continued Symbol Descrip
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Table A7.2: Data legitimacy check (
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Table A7.3: Results binary logistic
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Table A7.4: Results interacting wit
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Table A7.5: Results age and size no
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Table A7.5 continued Variable B S.E
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Table A8.1 continued Impulse BS TA
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Table A8.2 continued Number <strong
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Table A8.3: Relative occurrence and
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Figure A8.2: Decomposing total prom
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interessante aanbieding is. Combina
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aantalmerken in een categorie en im
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ERASMUS RESEARCH INSTITUTE OF MANAG
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Title: Beyond Generics;A closer loo
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Title: Planning and Control Concept
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