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Effectiveness of Online Marketing Campaigns: An Investigation into Online Multichannel and Search Engine Advertising
Internet advertising has come off age; yet little is known in research and practice about how digital channel advertising really works. The empirical research in this thesis intends to fill this gap and shed light on the effectiveness of online advertising. Two studies are conducted that focus on multichannel online advertising and search engine advertising, the single-most important online ad channel. In an interdisciplinary approach, both studies first develop comprehensive theoretical models based on existing work in related research fields―for example, marketing and information retrieval. This approach pays off and leads to new and insightful - There are synergies in multichannel online purchase propensity increases when consumers receive advertising messages through multiple channels. - The channel order can influence the conversion probability. - Click-through rates in search engine advertising are influenced through various keyword criteria on semantic and syntactic level The results of this thesis constitute an important starting point for future research in online advertising. Furthermore, the results enable practitioners to improve the effectiveness of online advertising through a more differentiated campaign management approach. Based on its findings, the thesis outlines how a future integrated approach to online advertising could look like.
156 pages, Paperback
First published March 31, 2013
2 people want to read
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December 27, 2020
✯✯✯✯ = really liked it.
Estos conceptos no me quedaron claros, tengo que leer más al respecto:
#4.1.1.3 Interaction of Previous Purchase with Exposure Intensity As introduced in Section 3.2.1.1, Deighton et al. (1994) examine two interaction effects: diagnostic framing and usage dominance. These effects move in opposite directions—that is, diagnostic framing enhances the effect of advertising, and usage dominance diminishes it— and the product category determines which one dominates (Hoch & Ha, 1986). Both effects should emerge in an online context. The product category of the focal advertiser (fashion and apparel) is ambiguous and complex, however, so framing should outweigh usage dominance, resulting in a positive overall interaction. This prediction is in line with Hoch and Ha (1986), who use polo shirts as products from an ambiguous category in their experiments. Pp.53
#That is, framing should increase the effect of channel-related
features on conversion rates, but usage dominance diminishes it. The resulting net effect depends on actual product characteristics, so framing dominates when products are complex and
ambiguous, whereas usage dominance occurs when products are more simple and consumers
can easily evaluate product quality.
#Both the Nagelkerke(?) and
McFadden R-square(?) values are well above 50%, indicating a good overall fit of the model.
Furthermore, the estimation produces stable coefficients with low p-values and good t-statistics for all six main variables.
# The author therefore does not expect any unstable coefficient estimates due to multicollinearity.
Estos conceptos no me quedaron claros, tengo que leer más al respecto:
#4.1.1.3 Interaction of Previous Purchase with Exposure Intensity As introduced in Section 3.2.1.1, Deighton et al. (1994) examine two interaction effects: diagnostic framing and usage dominance. These effects move in opposite directions—that is, diagnostic framing enhances the effect of advertising, and usage dominance diminishes it— and the product category determines which one dominates (Hoch & Ha, 1986). Both effects should emerge in an online context. The product category of the focal advertiser (fashion and apparel) is ambiguous and complex, however, so framing should outweigh usage dominance, resulting in a positive overall interaction. This prediction is in line with Hoch and Ha (1986), who use polo shirts as products from an ambiguous category in their experiments. Pp.53
#That is, framing should increase the effect of channel-related
features on conversion rates, but usage dominance diminishes it. The resulting net effect depends on actual product characteristics, so framing dominates when products are complex and
ambiguous, whereas usage dominance occurs when products are more simple and consumers
can easily evaluate product quality.
#Both the Nagelkerke(?) and
McFadden R-square(?) values are well above 50%, indicating a good overall fit of the model.
Furthermore, the estimation produces stable coefficients with low p-values and good t-statistics for all six main variables.
# The author therefore does not expect any unstable coefficient estimates due to multicollinearity.
Displaying 1 of 1 review