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Erschienen in: Quantitative Marketing and Economics 3/2017

05.08.2017

The impact of advertising along the conversion funnel

verfasst von: Stephan Seiler, Song Yao

Erschienen in: Quantitative Marketing and Economics | Ausgabe 3/2017

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Abstract

We assemble a unique data set that combines information on supermarket feature advertising with path-tracking data on consumers’ movement within the store as well as purchase information. Using these novel data, we trace out how advertising affects consumer behavior along the path-to-purchase. We find advertising has no significant effect on the number of consumers visiting the category being advertised. The null effect is precisely estimated. At the upper bound of the confidence interval, a one-standard-deviation shift in advertising increases category traffic by only 1.3%. We do find a significant effect at the lower end of the conversion funnel. A one-standard-deviation change in advertising (evaluated at the point estimate) increases category-level sales by 10%. We further decompose the impact on sales and find the increase is driven by the same number of consumers buying a larger number of products of the same brand. We find no evidence of spillover effects of advertising between categories that are stocked in proximity of each other, nor between different products in the same category. Two mechanisms are consistent with these patterns: consumers retrieve memory of the ad only when interacting with the category or only consumers wanting to purchase the brand choose to consume the ad.

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Fußnoten
1
“The Food Industry Speaks 2015,” Food Marketing Institute.
 
2
If a consumer moves farther than to an adjacent traffic point between signals, the movement over traffic points between the signals is interpolated. Because the signal is emitted at a high frequency, little interpolation is necessary for most trips.
 
3
The data provide the linkage between traffic points and product locations. Most product locations are associated with two or three traffic points.
 
4
We find that for 88% of all brand/week combinations in our data, feature advertising status is identical across all products within the specific brand/week (i.e., products within the same brand are all featured or not featured).
 
5
The average pairwise correlation of displays (across all categories and weeks) between stores of the same chain in the same market is equal to 0.50.
 
6
The categories in IRI not included in our analysis are razors, razor blades, cigarettes, deodorant, diapers, household cleaner, photo, shampoo, sugar substitutes, and tooth brushes.
 
7
We also implement the wild bootstrap method that Cameron et al. (2008) propose for settings with a small number of clusters. For our baseline regressions (for the impact on traffic as well as sales), we find the level of precision is slightly higher when applying the bootstrap procedure.
 
8
The price information is obtained from the purchase data. A promotion is defined as a reduction of at least 15% relative to the base price. The average price level is computed as the average (unweighted) price of all products in the category, and captures promotional price fluctuation over time in a more continuous fashion (relative to the number-of-promotions variable).
 
9
The inclusion of marketing controls does not play a role in driving the null effect (see Table 6 in the Appendix).
 
10
We emphasize that the null effect is precisely estimated and not due to a lack of statistical power, which is often documented in studies of online advertising (see Lewis and Rao 2015; Lewis and Reiley 2014).
 
11
We compute the standard deviation of features within categories by regressing the feature variable onto category fixed effects and then calculating the standard deviation of the residuals from this regression.
 
12
One could also use the share of purchases divided by the number of consumers visiting the category as the dependent variable. Due to the null effect on traffic, conditioning on category visits will not materially affect the results. For simplicity, we therefore focus on the unconditional number of purchases.
 
13
Because the across-store regression is estimated at the weekly level, we divide the estimated demand shocks by 7.
 
14
We emphasize that the display variable in the academic IRI data set is recorded for each store individually. Although industry practice is to sometimes impute display information from other stores, we did confirm with IRI directly that the display information is not imputed for the data used here.
 
15
The standard deviation of the pickup/purchase ratio (based on all locations) is 0.306, and hence a one-standard-deviation shift in the number of features (eight additional products) leads to an increase of 4% of a standard deviation (0.0017*8/0.306).
 
16
All of our discussion in this section focuses on classical, that is, additively separable, measurement error.
 
17
As discussed above, one could imagine that displays divert traffic away from main category locations, and hence the impact on traffic might be negative. However, our analysis in the previous section provides evidence against such an effect.
 
18
We note that we have sales data for all products and categories in the store, but the advertising data (from IRI) is limited to only 21 categories. See Section 2.3 for more details.
 
19
We manually code whether categories are substitutes, complements, or unrelated to each other. For instance, in the vicinity of beer, one substitute category (wine) is stocked as well as several complementary categories (chips, popcorn, etc.). We also note the majority of nearby products belongs to unrelated categories (88%) and only a small subset of products are either substitutes or complements of the focal category.
 
20
We note, however, that our estimates from this regression are noisy, and only the coefficient on the feature dummy variable is precisely estimated. The confidence interval for the brand-level effect of advertising (α 1 + α 2) ranges from -0.45 to 1.17 and therefore includes a null effect of advertising at the brand level as well as a modest positive spillover effect.
 
21
The path-data time stamp that records the arrival at the checkout can be noisy because the consumer will be stationary when standing in line at the cashier. Therefore, checkout baskets within a certain time window after the consumer became stationary in the checkout area qualify as possible matches.
 
22
The data provider did not disclose the precise algorithm to us.
 
23
We have path data for only 26 days, but we have data on feature advertising and other marketing variables for a longer time period. As a result, our lagged regressions have the same number of observations as the main regressions.
 
24
We can only define visit timing for consumers who actually pass the category at all during their trip. The day/category average therefore represents the average visit time for the subset of consumers who visit the specific category.
 
25
We also ran the same set of regressions based on distance walked before reaching a specific category (rather than time elapsed), and found similarly small and insignificant results.
 
26
The confidence interval for columns (5) and (6), respectively, are equal to [-0.050,0.021] minutes and [-0.089,0.149] percentage points.
 
Literatur
Zurück zum Zitat Anderson, E., Malin, B.A., Nakamura, E., Simester, D., & Steinsson, J. (2016). Informational rigidities and the stickiness of temporary sales. Journal of Monetary Economics, forthcoming. Anderson, E., Malin, B.A., Nakamura, E., Simester, D., & Steinsson, J. (2016). Informational rigidities and the stickiness of temporary sales. Journal of Monetary Economics, forthcoming.
Zurück zum Zitat Anderson, E.T., & Simester, D. (2013). Advertising in a competitive market: the role of product standards, customer learning, and switching costs. Journal of Marketing Research, 50, 489–504. CrossRef Anderson, E.T., & Simester, D. (2013). Advertising in a competitive market: the role of product standards, customer learning, and switching costs. Journal of Marketing Research, 50, 489–504. CrossRef
Zurück zum Zitat Bagwell, K. (2007). The economic analysis of advertising. In M. Armstrong, & R. Porter (Eds.), Handbook of industrial organization. Elsevier Science, (Vol. 3 pp. 1701–1844). Bagwell, K. (2007). The economic analysis of advertising. In M. Armstrong, & R. Porter (Eds.), Handbook of industrial organization. Elsevier Science, (Vol. 3 pp. 1701–1844).
Zurück zum Zitat Blattberg, R.C., & Neslin, S.A. (1990). Sales promotion: concepts, methods and strategies, 2nd edn. Prentice Hall. Blattberg, R.C., & Neslin, S.A. (1990). Sales promotion: concepts, methods and strategies, 2nd edn. Prentice Hall.
Zurück zum Zitat Bodapati, A.V., & Srinivasan, V. (2006). The impact of feature advertising on customer store choice. Working Paper. Bodapati, A.V., & Srinivasan, V. (2006). The impact of feature advertising on customer store choice. Working Paper.
Zurück zum Zitat Bronnenberg, B.J., Kim, J.B., & Mela, C.F. (2016). Zooming in on choice: how do consumers search for cameras online? Marketing Science, 35, 693–712. CrossRef Bronnenberg, B.J., Kim, J.B., & Mela, C.F. (2016). Zooming in on choice: how do consumers search for cameras online? Marketing Science, 35, 693–712. CrossRef
Zurück zum Zitat Bronnenberg, B.J., Kruger, M.W., & Mela, C.F. (2008). The IRI marketing data set. Marketing Science, 27, 745–748. CrossRef Bronnenberg, B.J., Kruger, M.W., & Mela, C.F. (2008). The IRI marketing data set. Marketing Science, 27, 745–748. CrossRef
Zurück zum Zitat Cameron, A.C., Gelbach, J.B., & Miller, D.L. (2008). Bootstrap-based improvements for inference with clustered errors. The Review of Economics and Statistics, 3, 414–427. CrossRef Cameron, A.C., Gelbach, J.B., & Miller, D.L. (2008). Bootstrap-based improvements for inference with clustered errors. The Review of Economics and Statistics, 3, 414–427. CrossRef
Zurück zum Zitat Chan, T., Ma, Y., Narasimhan, C., & Singh, V. (2006). An empirical analysis of store competition. Working Paper. Chan, T., Ma, Y., Narasimhan, C., & Singh, V. (2006). An empirical analysis of store competition. Working Paper.
Zurück zum Zitat Chen, Y., & Yao, S. (2016). Sequential search with refinement: model and application with click-stream data. Management Science, forthcoming. Chen, Y., & Yao, S. (2016). Sequential search with refinement: model and application with click-stream data. Management Science, forthcoming.
Zurück zum Zitat De Los Santos, B.I., Hortacsu, A., & Wildenbeest, M. (2012). Testing models of consumer search using data on web browsing and purchasing behavior. American Economic Review, 102, 2955–2980. CrossRef De Los Santos, B.I., Hortacsu, A., & Wildenbeest, M. (2012). Testing models of consumer search using data on web browsing and purchasing behavior. American Economic Review, 102, 2955–2980. CrossRef
Zurück zum Zitat Erdem, T., Imai, S., & Keane, M.P. (2003). Brand and quantity choice dynamics under price uncertainty. Quantitative Marketing and Economics, 1, 5–64. CrossRef Erdem, T., Imai, S., & Keane, M.P. (2003). Brand and quantity choice dynamics under price uncertainty. Quantitative Marketing and Economics, 1, 5–64. CrossRef
Zurück zum Zitat Hendel, I., & Nevo, A. (2006). Measuring the implications of sales and consumer inventory behavior. Econometrica, 74, 1637–1673. CrossRef Hendel, I., & Nevo, A. (2006). Measuring the implications of sales and consumer inventory behavior. Econometrica, 74, 1637–1673. CrossRef
Zurück zum Zitat Honka, E., Hortacsu, A., & Vitorino, M.A. (2016). Advertising, consumer awareness and choice: Evidence from the U.S. Banking Industry. RAND Journal of Economics, forthcoming. Honka, E., Hortacsu, A., & Vitorino, M.A. (2016). Advertising, consumer awareness and choice: Evidence from the U.S. Banking Industry. RAND Journal of Economics, forthcoming.
Zurück zum Zitat Hui, S.K., Bradlow, E.T., & Fader, P.S. (2009a). The traveling salesman goes shopping: the systematic deviations of grocery paths from TSP optimality. Marketing Science, 28, 566–572. Hui, S.K., Bradlow, E.T., & Fader, P.S. (2009a). The traveling salesman goes shopping: the systematic deviations of grocery paths from TSP optimality. Marketing Science, 28, 566–572.
Zurück zum Zitat Hui, S.K., Fader, P.S., & Bradlow, E.T. (2009b). Path data in marketing: an integrative framework and prospectus for model building. Marketing Science, 28, 320–335. Hui, S.K., Fader, P.S., & Bradlow, E.T. (2009b). Path data in marketing: an integrative framework and prospectus for model building. Marketing Science, 28, 320–335.
Zurück zum Zitat Hui, S.K., Huang, Y., Suher, J., & Inman, J. (2013a). Deconstructing the first moment of truth: understanding unplanned consideration and purchase conversion using In-Store video tracking. Journal of Marketing Research, 50, 445–462. Hui, S.K., Huang, Y., Suher, J., & Inman, J. (2013a). Deconstructing the first moment of truth: understanding unplanned consideration and purchase conversion using In-Store video tracking. Journal of Marketing Research, 50, 445–462.
Zurück zum Zitat Hui, S.K., Inman, J., Huang, Y., & Suher, J. (2013b). Estimating the effect of travel distance on unplanned spending: applications to mobile promotion strategies. Journal of Marketing, 77, 1–16. Hui, S.K., Inman, J., Huang, Y., & Suher, J. (2013b). Estimating the effect of travel distance on unplanned spending: applications to mobile promotion strategies. Journal of Marketing, 77, 1–16.
Zurück zum Zitat Jedidi, K., Mela, C.F., & Gupta, S. (1999). Managing advertising and promotion for long-run profitability. Marketing Science, 18, 1–22. CrossRef Jedidi, K., Mela, C.F., & Gupta, S. (1999). Managing advertising and promotion for long-run profitability. Marketing Science, 18, 1–22. CrossRef
Zurück zum Zitat Johnson, G.A., Lewis, R., & Nubbemeyer, E. (2016). The online display ad effectiveness funnel & carry-over: a meta-study of ghost ad experiments. Working Paper. Johnson, G.A., Lewis, R., & Nubbemeyer, E. (2016). The online display ad effectiveness funnel & carry-over: a meta-study of ghost ad experiments. Working Paper.
Zurück zum Zitat Keller, K.L. (1987). Memory factors in advertising: the effect of advertising retrieval cues on brand evaluations. Journal of Consumer Research, 14, 316–333. CrossRef Keller, K.L. (1987). Memory factors in advertising: the effect of advertising retrieval cues on brand evaluations. Journal of Consumer Research, 14, 316–333. CrossRef
Zurück zum Zitat Kim, J.B., Albuquerque, P., & Bronnenberg, B.J. (2010). Online demand under limited consumer search. Marketing Science, 29, 1001–1023. CrossRef Kim, J.B., Albuquerque, P., & Bronnenberg, B.J. (2010). Online demand under limited consumer search. Marketing Science, 29, 1001–1023. CrossRef
Zurück zum Zitat Lee, A.Y. (2002). Effects of implicit memory on memory-based versus stimulus-based brand choice. Journal of Marketing Research, 39, 440–454. CrossRef Lee, A.Y. (2002). Effects of implicit memory on memory-based versus stimulus-based brand choice. Journal of Marketing Research, 39, 440–454. CrossRef
Zurück zum Zitat Lee, A.Y., & Labroo, A.A. (2004). The effect of conceptual and perceptual fluency on brand evaluation. Journal of Marketing Research, 41, 151–165. CrossRef Lee, A.Y., & Labroo, A.A. (2004). The effect of conceptual and perceptual fluency on brand evaluation. Journal of Marketing Research, 41, 151–165. CrossRef
Zurück zum Zitat Lewis, R.A., & Nguyen, D. (2014). A Samsung Ad for the iPad? Display advertising’s competitive spillovers to search. Working Paper. Lewis, R.A., & Nguyen, D. (2014). A Samsung Ad for the iPad? Display advertising’s competitive spillovers to search. Working Paper.
Zurück zum Zitat Lewis, R.A., & Rao, J.M. (2015). The unfavorable economics of measuring the returns to advertising*. The Quarterly Journal of Economics, 130, 1941. CrossRef Lewis, R.A., & Rao, J.M. (2015). The unfavorable economics of measuring the returns to advertising*. The Quarterly Journal of Economics, 130, 1941. CrossRef
Zurück zum Zitat Lewis, R.A., & Reiley, D.H. (2014). Online ads and offline sales: measuring the effect of retail advertising via a controlled experiment on Yahoo! Quantitative Marketing and Economics, 12, 235–266. CrossRef Lewis, R.A., & Reiley, D.H. (2014). Online ads and offline sales: measuring the effect of retail advertising via a controlled experiment on Yahoo! Quantitative Marketing and Economics, 12, 235–266. CrossRef
Zurück zum Zitat Mela, C.F., Gupta, S., & Lehmann, D.R. (1997). The long-term impact of promotion and advertising on consumer brand choice. Journal of Marketing Research, 34, 248–261. CrossRef Mela, C.F., Gupta, S., & Lehmann, D.R. (1997). The long-term impact of promotion and advertising on consumer brand choice. Journal of Marketing Research, 34, 248–261. CrossRef
Zurück zum Zitat Osborne, M. (2011). Consumer learning, switching costs and heterogeneity: a structural examination. Quantitative Marketing and Economics, 9, 25–70. CrossRef Osborne, M. (2011). Consumer learning, switching costs and heterogeneity: a structural examination. Quantitative Marketing and Economics, 9, 25–70. CrossRef
Zurück zum Zitat Quelch, J.A., & Court, A.M. (1983). PROCTER & GAMBLE CO. (B). HBS Case, 584048. Quelch, J.A., & Court, A.M. (1983). PROCTER & GAMBLE CO. (B). HBS Case, 584048.
Zurück zum Zitat Rossi, P.E. (2014). Invited paper – even the rich can make themselves poor: a critical examination of IV methods in marketing applications. Marketing Science, 33, 655–672. CrossRef Rossi, P.E. (2014). Invited paper – even the rich can make themselves poor: a critical examination of IV methods in marketing applications. Marketing Science, 33, 655–672. CrossRef
Zurück zum Zitat Sahni, N.S. (2016). Advertising spillovers: evidence from online field experiments and implications for returns on advertising. Journal of Marketing Research, 53, 459–478. CrossRef Sahni, N.S. (2016). Advertising spillovers: evidence from online field experiments and implications for returns on advertising. Journal of Marketing Research, 53, 459–478. CrossRef
Zurück zum Zitat Sahni, N.S., Zou, D., & Chintagunta, P.K. (2016). Do targeted discount offers serve as advertising? Evidence from 70 field experiments. Management Science, forthcoming. Sahni, N.S., Zou, D., & Chintagunta, P.K. (2016). Do targeted discount offers serve as advertising? Evidence from 70 field experiments. Management Science, forthcoming.
Zurück zum Zitat Seiler, S., & Pinna, F. (2016). Estimating search benefits from path-tracking data: measurement and determinants. Marketing Science, forthcoming. Seiler, S., & Pinna, F. (2016). Estimating search benefits from path-tracking data: measurement and determinants. Marketing Science, forthcoming.
Zurück zum Zitat Shapiro, B.T. (2016). Positive spillovers and free riding in advertising of prescription pharmaceuticals: The case of antidepressants. Journal of Political Economy, forthcoming. Shapiro, B.T. (2016). Positive spillovers and free riding in advertising of prescription pharmaceuticals: The case of antidepressants. Journal of Political Economy, forthcoming.
Zurück zum Zitat Sorensen, H. (2003). The science of shopping. Marketing Research, 15, 31–35. Sorensen, H. (2003). The science of shopping. Marketing Research, 15, 31–35.
Metadaten
Titel
The impact of advertising along the conversion funnel
verfasst von
Stephan Seiler
Song Yao
Publikationsdatum
05.08.2017
Verlag
Springer US
Erschienen in
Quantitative Marketing and Economics / Ausgabe 3/2017
Print ISSN: 1570-7156
Elektronische ISSN: 1573-711X
DOI
https://doi.org/10.1007/s11129-017-9184-y