The Role of Geo-Demographic Big Data for Assessing the Effectiveness of Crowd-Funded Software Projects: A Case Example of “QPress”

The Role of Geo-Demographic Big Data for Assessing the Effectiveness of Crowd-Funded Software Projects: A Case Example of “QPress”

Jonathan Bishop
Copyright: © 2016 |Pages: 21
DOI: 10.4018/978-1-4666-9840-6.ch066
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Abstract

The current phenomenon of Big Data – the use of datasets that are too big for traditional business analysis tools used in industry – is driving a shift in how social and economic problems are understood and analysed. This chapter explores the role Big Data can play in analysing the effectiveness of crowd-funding projects, using the data from such a project, which aimed to fund the development of a software plug-in called ‘QPress'. Data analysed included the website metrics of impressions, clicks and average position, which were found to be significantly connected with geographical factors using an ANOVA. These were combined with other country data to perform t-tests in order to form a geo-demographic understanding of those who are displayed advertisements inviting participation in crowd-funding. The chapter concludes that there are a number of interacting variables and that for Big Data studies to be effective, their amalgamation with other data sources, including linked data, is essential to providing an overall picture of the social phenomenon being studied.
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Background

This chapter is in essence looking at effective means for assessing the impact of a crowd-funded campaign supported by advertising. It is argued that geo-demographic factors play a significant role in the effectiveness of crowd-funding projects, particularly those supported by advertising. It is further argued that Big Data can be used to identify trends that go beyond the usual metrics for advertising campaigns – such as impressions, clicks and average position – while at the same time supporting the use of such measures.

Big Data

According to the New York Times, many think Big Data is synonymous with “Big Brother,” in the form of mega-corporations collecting masses of surveillance information on their customers or potential customers. However, as this chapter advocates, it can also be of use to smaller entities, such as crowd-funded projects. It has been estimated that Google alone contributed 54 billion dollars to the US economy in 2009 as a result of Big Data, but there is still no clear consensus on what it is (Labrinidis & Jagadish, 2012). Even so, Big Data is something that each business will have to adopt as a normal way to develop business strategy (Woerner & Wixom, 2015).

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