Imagine a visitor came to your site, two times a day. At the first instance, he found your media brand selling premium content through a Facebook advertisement in his newsfeed. He clicked on the advertisement and visited the media site. In the second instance, a few hours later during the day, after having gathered some more information he Googled the media brand name, he clicked the paid search results and landed on your site.
In the second visit, imagine he subscribed to your premium content and made the necessary payment. While measuring the effectiveness of the campaigns, the campaign manager would find zero conversions against Facebook ads, while one conversion against Google paid ads.
The conversion in the second instance would not have happened had he not seen the Facebook banner ad campaign. This would mislead the campaign manager who would now give less weightage to the first click that came through the Facebook campaign.
Depending on the type of products or services for which you’re running campaigns, the time taken to decide would also vary. For e.g.: Long sales cycles are particularly common when the value of the service you have advertised is considerably high. Shorter sales cycles and impulsive purchases are common when the price is lower, and the risk associated with the purchase is lower.
Highlighting the last click that resulted in the sale in the same session would not give the due weightage for the clicks that introduced the brand. All web analytics tools do not completely reveal the entire customer journey and hence advertised budgets are being wasted.
An agency in their individual brand study collected feedback from buyers and realized that the high-value buyers had seen on an average at least seven campaigns of the brand. All buyers recall having seen at least three campaigns. While the last campaign results according to the campaign manager, showed only 50% of the audience reached resulted in a sale and rest is wasted.
The metrics according to the agency would guide you to think that the rest of the ad exposure was wasted since they did not convert in the same session. This is the biggest trap of last click attribution that is widely practiced in free web analytics tools.
Himanshu Sharma, Attribution Modelling in Google Analytics and Beyond, pp. 49-235.
Tahir M. Nisar and Man Yeung, Attribution Modelling In Digital Advertising, Journal of Advertising Research
Patrick Jordan, Mohammad Mahdian, Sergei Vassilvitskii and Erik Vee, The Multiple Attribution Problem in Pay-Per-Conversion Advertising, Stanford University - http://theory.stanford.edu/~sergei/papers/sagt11-multattr.pdf
Attribution Whitepaper 2015, Internet Advertising Bureau - https://www.iabuk.com/sites/default/files/public_files/Attribution_White_Paper_0.pdf
Last Click Attribution: A Simple Way to Misallocate Your Budget, Dataxu - https://www.dataxu.com/wp-content/uploads/MarketPulse-3.pdf