Digital advertising has a distinct advantage over traditional forms of advertising in that it can monitor the ads to which customers respond, as well as draw direct connections between specific ads and actual purchases. Digital marketing seduces the advertiser who believes in data driven decision making. While digital inherently has a data advantage over other forms of advertising, one of the major problems faced by advertisers today “is the inability to measure data and media across channels to effectively measure ROI and optimize their media mix.”[i] The proliferation of mobile devices and the movement away from the desktop has only made it harder for marketers to accurately attribute purchases (or downloads) to certain ads across multiple screens. Marketers have to now deal with eyeballs shifting from countless devices/mediums (mobile phones, tablets, desktop, TV, radio, print, billboards, etc.) as well as channels (display, email campaigns, paid search, social media, etc.).
Last click attribution, once the norm in digital advertising, appears to be a dying attribution model fraught with weaknesses. In the words of Aggregate Knowledge’s Pascal Bensoussan, “it’s like having a sales guy at the Macy’s store entrance with a big sales display in front of him and attributing every sale in the store to that guy, so that everything you have done up to that point is completely ignored.” Forrester Research shares Bensoussan’s concern: “Traditional one-to-one, last-touch methods of allocating demand to marketing efforts are outdated and lead to a suboptimal marketing mix. Customer Intelligence professionals must adopt a cross-channel attribution model in order to optimize marketing budgets, accurately calculate customer value and acquisition costs, and develop a holistic view of the marketing ecosystem. Failure to embrace this new standard is expensive — firms will be plagued with continued channel conflict and an inefficient marketing budget.”[ii]
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