Although the conditions that motivate individuals to buy, sell, search, and post on the Internet are diverse, the information generated as a byproduct of these activities has the potential to help marketers develop a better understanding of consumer and firm behavior. In this paper, we utilize online product search data to build a model that links sales to marketing mix activity. The objectives of this research are threefold: first, to incorporate secondary data collected from online sources into a model of demand, thus improving our ability to forecast sales; second, to develop a better understanding of the role of marketing mix activity in the sales generation process; and third, generation of “nowcast” or contemporaneous prediction of sales. We illustrate the benefits of our approach using data for a luxury automobile brand where we use advertising as an example of marketing mix activity. We show that our proposed model produces improved sales forecast relative to standard time series approaches. Further, the specification of our model is ideal for the generation of a nowcast. We discuss why nowcasting has the potential to improve operations in the automotive industry.
Bayesian estimation, Online search, Nowcasting, Marketing mix modeling
Advertising and Promotion Management | E-Commerce | Marketing
Customer Needs and Solutions
Springer Verlag (Germany)
CHANDUKALA, Sandeep R.; DOTSON, Jeffrey P.; LIU, Qing; and CONRADY, Stephan.
Exploring the Relationship Between Online Search and Offline Sales for Better "Nowcasting". (2014). Customer Needs and Solutions. 1, (3), 176-187. Research Collection Lee Kong Chian School Of Business.
Available at: http://ink.library.smu.edu.sg/lkcsb_research/4800
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.