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Published by: Allied Business Academies
Originally published in: "Academy of Marketing Studies Journal", 2016
Length: 18 pages

Abstract

Propelled by the growth in commercial usage of the internet by companies and customers, Big Data and Advertising Analytics have emerged as a scientific and marketing discipline which gathers, analyzes, and extracts informational value from business-to-customer online interaction. Jobs, Aukers, & Gilfoil (2015) studied this emerging discipline and developed a consolidated typology of the firms operating in the ecosystem. It is evident from this work that customer-facing companies (digital advertisers) could be confused about Big Data service offerings and affordability of firms, how to use them to drive their marketing strategies, or how they can be used to improve marketing efficiency and effectiveness. Key findings from the present research indicate which digital advertisers can most benefit from Big Data, and by how much. More specifically, findings indicate minimum advertising spend levels required to benefit from each type of Big Data firm, the expected return on advertising spend for each, as well as critical factors for successful engagement. Insights relating to costs and performance expectations are also distilled from in-depth, semi-structured interviews with key executives from 24 Big Data and Advertising Analytics firms. This research concludes that Big Data firms can potentially add value if properly matched with the right digital client. Depending on the type of Big Data firm used, cost of entry can range from USD5,000 to USD100,000 a month, while mean advertising efficiency savings range from a low of 20% to a high of 35%.

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Abstract

Propelled by the growth in commercial usage of the internet by companies and customers, Big Data and Advertising Analytics have emerged as a scientific and marketing discipline which gathers, analyzes, and extracts informational value from business-to-customer online interaction. Jobs, Aukers, & Gilfoil (2015) studied this emerging discipline and developed a consolidated typology of the firms operating in the ecosystem. It is evident from this work that customer-facing companies (digital advertisers) could be confused about Big Data service offerings and affordability of firms, how to use them to drive their marketing strategies, or how they can be used to improve marketing efficiency and effectiveness. Key findings from the present research indicate which digital advertisers can most benefit from Big Data, and by how much. More specifically, findings indicate minimum advertising spend levels required to benefit from each type of Big Data firm, the expected return on advertising spend for each, as well as critical factors for successful engagement. Insights relating to costs and performance expectations are also distilled from in-depth, semi-structured interviews with key executives from 24 Big Data and Advertising Analytics firms. This research concludes that Big Data firms can potentially add value if properly matched with the right digital client. Depending on the type of Big Data firm used, cost of entry can range from USD5,000 to USD100,000 a month, while mean advertising efficiency savings range from a low of 20% to a high of 35%.

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