Attribution modelling in digital advertising for e-commerce Online publication date: Mon, 21-Feb-2022
by Sergey Alexandrovskiy; Olga Trundova
International Journal of Internet Marketing and Advertising (IJIMA), Vol. 16, No. 1/2, 2022
Abstract: The authors aim to offer a probability approach for measuring media contribution to online conversions in e-commerce. The authors reviewed literature on attribution modelling with application of heuristics (Google Analytics) and probability (Markov chains) models. The survey used the data of customer journeys from 134,132 users to build up the attribution model. As a result, Markov chains model minimises the value of direct online channel, and redistributes the value in favour of other traffic channels and gives a significant weight to the paid traffic. Markov chains model increases the importance of display and paid search channels, which is not so noticeable in heuristic models. Findings of this study help marketers to apply Markov chains modelling in online advertising evaluation and budgeting. The authors proposed application of Markov chains attribution modelling in the e-commerce website. Other e-commerce companies might apply Markov chains attribution modelling in a similar way.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Internet Marketing and Advertising (IJIMA):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook