(4 and a half minute read)

AN OVERVIEW AND SETTING THE SCENE

The topic of Big Data relates to macro-level consumer behaviour where insights are gleaned from trends and patterns arising from micro-level consumer actions.

While organisational buying deals with the direct marketing implications for business arising from consumer trends, Big Data looks at the technology behind the gathering and analysis of data. The term ‘Big’ is prefixed simply to illustrate and emphasise the scale and scope of data complexity and issues surrounding its analysis.

BIG DATA AND BUSINESS INTELLIGENCE

Big Data is often confused with Business Intelligence. BI relates to use and analysis of data that directly informs business decision making. BI often relates to manageable data sets where clear, concise questions are asked, neat analysis is carried out, and clear, concise answers are obtained to business problems. Big Data however relates more to the technology itself, the prevalence of technology in everyday lives, the potential it provides to access unimaginable amounts of human data, and generating ideas about questions that can be asked of that data that will help businesses.

BIG DATA SCOPE

The challenges in dealing with Big Data arise from the scale and scope of data that is accumulated everyday, the challenges of storing and analysing data, and the lack of technology in developing appropriate solutions.

The growth of Internet of Things (IoT) is only expected to intensify these challenges. Developments in cloud computing, mega servers, Artificial Intelligence, and other developments provide some solutions. Large tech companies are investing heavily in Big Data solutions.

IMPLICATIONS FOR BUSINESS

The impact of Big Data is already being felt in several industries. The shape and nature of marketplaces, industries, sectors, and exchange systems are being radically changed as companies gather insights from data and use them to shape their business practices.

This means that traditional understandings of marketing such as 4Ps and conventional methods of market segmentation are fast becoming obsolete as accurate information about consumer behaviours is being gathered through everyday devices and user-generated content.

ETHICAL CHALLENGES

The ethical challenges lies between balancing the growing commercial pressures of monetising user-generated data, harmonising the power that tech companies hold over our everyday lives, enabling governments to uphold citizen rights, and protecting individual consumer’s ability to control their own data and maintain ethics and privacy. Consumers find that they have very little control over their own data and privacy but may be able to sacrifice some of their concerns if it benefits them in some way. However governments and businesses have a moral and legal responsibility to ensure that data is being used for common good and not just for profits.