Abstract
With the development of multimedia information technology, all walks of life use multimedia technology to publish business information and advertising information to enhance users’ awareness and satisfaction with the industry. Among the applications of using multimedia to enhance management, keyword advertising is undoubtedly one of the successful models. Keyword advertising, a typical kind of multimedia advertising, is an important way for advertiser to match customer needs precisely. Evaluating the effectiveness of this novel advertising approach comes to be the focus of attentions in this field. In addition, user experiences in advertisers’ page are hardly taken into account in existing researches. Using a unique dataset of keywords on a commercial search engine provider in China, we model click, cost per click and conversion simultaneously. We introduce factors of three categories: bidding factor, keyword semantics factors and user cognition factors. Page view and bounce rate, which have not been reported in existing researches as far as we know, are employed to discover user cognition on website. We find that cost per click has a significant relationship with clicks and conversions. Brand information can increase both clicks and conversions while decrease cost per click. Although long tail keyword advertisement may bring website more traffic, it does not increase conversions. Specifically, we find that page view is positive relate to clicks and conversions while bounce rate is negative to conversions. Our research results can be easily applied in practice by advertiser to improve multimedia advertising performance.
Similar content being viewed by others
References
Agarwal A, Hosanagar K, Smith MD (2011) Location, location, location: An analysis of profitability of position in online advertisement markets. J Mark Res 48(6):1057–1073
Agarwal A, Mukhopadhyay T (2016) The Impact of Competing Ads on Click Performance in Sponsored Search. Inf Syst Res 27(3):538–557
Bucklin RE, Sismeiro C (2009) Click here for Internet insight: Advances in clickstream data analysis in marketing. J Interact Mark 23(1):35–48
Dandan Q, Jin Z, Qiang W et al (2017) Finding competitive keywords from query logs to enhance search engine advertising. Inf Manag 54(4):531–543
Edelman B, Ostrovsky M, Schwarz M (2007) Internet advertising and the generalized 2nd-price auction: Selling billions of dollars worth of keywords. Am Econ Rev 97(1):242–259
Ghose A, Yang S (2009) An empirical analysis of search engine advertising: Sponsored search in electronic markets. Manag Sci 55(10):1605–1622
Gupta G, Saha B, Sarkar UK (2017) Emergent Heterogeneity in keyword valuation in sponsored search markets: a closer-to-practice perspective. Comput Econ 50(4):687–710
Haans H, Raassens N, Hout RV (2013) Search engine advertisements: The impact of advertising statements on click-through and conversion rates. Mark Lett 24(2):151–163
Jansen BJ, Liu Z, Simon Z (2013) The effect of ad rank on the performance of keyword advertising campaigns. J Am Soc Inf Sci Technol 64(10):2115–2132
Kim S, Qin T, Liu TY et al (2014) Advertiser-centric approach to understand user click behavior in sponsored search. Inf Sci 276(c):242–254
Rutz OJ, Trusov M (2011a) Zooming in on paid search ads—a consumer-level model calibrated on aggregated data. Mark Sci 30(5):789–800
Rutz OJ, Bucklin RE, Sonnier GP (2012) A latent instrumental variables approach to modeling keyword conversion in paid search advertising. J Mark Res 49(3):306–319
Rutz OJ, Trusov M (2011b) Zooming in on paid search ads—a consumer-level model calibrated on aggregated data. Mark Sci 30(5):789–800
Yang S, Ghose A (2010) Analyzing the relationship between organic and sponsored search advertising: positive, negative, or zero interdependence. Mark Sci 29(4):602–623
Acknowledgements
The authors acknowledge the National Natural Science Foundation of China (Grant: 71462002).
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Qin, C., Li, C. & Wei, J. Study on the evaluation of multimedia advertising performance. Multimed Tools Appl 79, 9921–9934 (2020). https://doi.org/10.1007/s11042-019-07780-1
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-019-07780-1