FRINK Linked Data Fragments server

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• W2598556338 abstract "INTRODUCTION Propelled by the growth in commercial usage of the internet by companies and customers, Big Data has emerged as a scientific and marketing discipline which gathers, analyzes, and extracts informational value from massive amounts of business and customer online interactions. The growth of publicly available unstructured data is immense and pervasive --and it is growing at an accelerated pace according to Jonathan Shaw (2014). Shaw makes the case for Big Data: Data now stream from daily life: from phones and credit cards and televisions and computers; from the infrastructure of cities; from sensor-equipped buildings, trains, buses, planes, bridges, and factories. The data flow so fast that the total accumulation of the past two years--a zettabyte--dwarfs the prior record of human civilization (Shaw, 2014, p. 30). Many companies and institutions have quickly recognized the value of harnessing Big Data. Allouche (2014) suggests that applying the science and discipline of Big Data to the massive amounts of unstructured marketing data can leverage that data to innovate their advertising programs. He also suggests that it is important to help companies advertise to customers for the things they want and use--without being annoying. Forbes Magazine (Whitler, 2015) supports the virtues of Big Data and the analysis of that data using Advertising Analytics. Advertising Analytics, a term popularized in the academic literature by Nichols (2013), refers to the set of capabilities that allows marketing firms to make sense of Big Data, ultimately enabling the measurement of an advertising campaign's impact on their business. Jobs, Aukers, and Gilfoil (2015) studied this emerging Big Data/Advertising Analytics discipline and developed a consolidated framework and typology of the firms operating in the ecosystem. It is evident from this work that, even though the ecosystem is thriving and rapidly evolving, the discipline is complex and sometimes difficult to understand. While there are some clear lines of distinction in the types of Big Data and Advertising Analytic firms in the ecosystem, there are some blurry lines, overlap, and interdependence between the constituent firms. Furthermore, some marketing clients are still not convinced about the overall value of Big Data (Ross, Beath, & Quaadgras, 2013), while others are questioning the affordability of Big Data and Advertising Analytic firms, the steepness of their learning curves, how to use them to drive their marketing strategies, or how they can be used to improve marketing efficiency and effectiveness (Purohit, 2014; IBM, 2013; Duke CMO Survey, 2013; Moorman, 2013). Purohit (2014), in particular, suggests that there is a strong enough incentive to overcome the barriers to using Big Data, provided that companies understand the power of this data and analytics to deliver higher throughput, better value for customers, and the immaculate growth in the global economy. While the potential power of Big Data and Marketing Analytics can readily be detailed, a key challenge lies is integrating Big Data into a client company's overall strategy. It requires a significant commitment of resources in terms of money, staff, and time--and the organization needs a plan on how to execute. A recent McKinsey report (Biesdorf, Court, & Willmott, 2013) underscores this point while noting that CIO's must also stress the need to completely remake company data architectures and applications. The report concludes that the missing step for most companies is spending the time to understand how data, analytics, frontline tools, and people can come together to create business value. The problem being addressed in this research endeavor is that the Big Data and Advertising Analytics ecosystem is complex and still evolving. While there is much hype about the industry and its promises to enhance marketing (advertising) program efficiencies and effectiveness, many potential marketing clients (i. …" @default.
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• W2598556338 date "2016-01-01" @default.
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• W2598556338 title "How Marketing Organizations Can Benefit from Big Data Advertising Analytics" @default.
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