Location
260-055, Owen G. Glenn Building
Start Date
12-15-2014
Description
This study scrutinizes the predictive relationship between three referral channels, search engine, social medial, and third-party advertising, and online consumer search and purchase. The results derived from vector autoregressive models suggest that the three channels have differential predictive relationship with sale measures. Search engine plays a more important role in driving online sales, social media the next, and third-party ads the lowest. Referrals from social media, however, have the strongest relationship with conversion, search engine the next and third-party the lowest The predictive power of the three channels is also considerably different in referring customers among competing online shopping websites. This study offers new insights for IT and marketing practitioners in respect to better and deeper understanding on marketing attribution and how different channels perform in order to optimize the media mix and overall performance.
Recommended Citation
Zhang, Jennifer and Duan, Wenjing, "THE IMPACT OF REFERRAL CHANNELS IN ONLINE CUSTOMER JOURNEY" (2014). ICIS 2014 Proceedings. 47.
https://aisel.aisnet.org/icis2014/proceedings/EBusiness/47
THE IMPACT OF REFERRAL CHANNELS IN ONLINE CUSTOMER JOURNEY
260-055, Owen G. Glenn Building
This study scrutinizes the predictive relationship between three referral channels, search engine, social medial, and third-party advertising, and online consumer search and purchase. The results derived from vector autoregressive models suggest that the three channels have differential predictive relationship with sale measures. Search engine plays a more important role in driving online sales, social media the next, and third-party ads the lowest. Referrals from social media, however, have the strongest relationship with conversion, search engine the next and third-party the lowest The predictive power of the three channels is also considerably different in referring customers among competing online shopping websites. This study offers new insights for IT and marketing practitioners in respect to better and deeper understanding on marketing attribution and how different channels perform in order to optimize the media mix and overall performance.