Social networking theory and the rise of digital marketing in the light of big data

The topic of this thesis is the use of ‘Big Data’ as a catalyst for true precision target marketing, where online advertisements across all communication channels are so timely and relevant that they are welcomed by the consumer because they improve the customer experience. In particular, the research has been directed to demonstrate the link between investment in digital branding and sales revenue at the company level. This thesis includes a review of the accumulation of ‘Big Data’ from a plethora of social networks, and an assessment of its current use and application by marketing and sales departments and emerging others. The hypothesis tested was that companies most advanced in processing ‘Big Data’ by rules-based, algorithmic, digital analysis are the companies realizing the greatest return on investment in the use of ‘Big Data’. The research was conducted using a questionnaire and interviews with the top people working in large consultancy and related firms who are actively engaged in the utilization of social media and large datasets. As there is a lack of understanding within companies in terms of using social media, and many obstacles have to be overcome, the research was meant to unearth some insights into the effective use of data. The research indicated that companies that had certain organizational and operational characteristics actively use social media, although the utilization is often limited in scope. However companies that do use them effectively gain measurable ROI and tend to track users across many venues. The companies using advanced ‘Big Data’ analytical tools to describe and predict user characteristics, applying the intelligence to target, time, tailor and trigger the release of cogent content to the ‘dynamic throng of individual audiences’ are experiencing the highest return on social media investment. This thesis makes a contribution to the wider understanding of social media use by the large business entities, and to the current and future problems that this explosion of data is creating and is likely to create