Abstract
With the advent of digital era the business landscape has evolved drastically thereby impacting all the marketing and advertising activities. Advertisers employ multiple channels to reach the customers on digital platform. Now the challenge has come up to design methodology to attribute conversions to these multiple channels in order to measure ROI (return on investment) and optimise the allocation of media budget. The problem gets compounded on digital platform where people tend to visit multiple times through multiple channels before each conversion. Conventional models of first touch, last touch and linear attribution do not give statistically complete picture, but at the same time, there are not enough resources outside which helps to implement a model like Markov attribution model to get statistically sound attribution and analysis of conversions. This paper aims to provide a high-level overview of different attribution models provided within some of the most prominent tools like Adobe Analytics and Google Analytics. At the same time the paper builds the case for more statistically sound model like 'Markov analysis' to showcase how and why it is better than traditional models.
Published Version
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