What is ‘Big data’?
It is considered to be the application and usage of data gained from the growing volume, velocity and variety that is now available given the multiple channels and platforms availableTracking and analysing these data means marketers can dig deeper into the minds of the consumer and understand finer details about their preferences and behaviours.
Data is growth at the rate of approximately 40% per year -McKinsey Chief Marketing & Sales Officer Forum, 2014
What are the 3 V’s?
Volume is the growth in data coming from online platforms including social media
Online shops can analyse heatmaps to track consumer behaviour, they know their most sought after item based on trackpad or mouse behaviour.
They may not have a high conversion rate, but the heatmap allows businesses to narrow down what the barrier to conversion could be. Previously, the only data available to physical shop-owners is their own interpretation of what seems popular.
Velocity is the speed in which markets can access data, real-time results are considered to be essential in current analysis.
Restaurants can monitor social data and detect certain ‘buzzwords’ during a service period and remedy the issue. A consumer could tweet
‘hate when the service isn’t friendly #disappointed’
and the marketer can receive this in real-time and tell their waiter to be more friendly.
Variety covers the new types of more ‘unstructured data’ (Chaffey and Ellis-Chadwick, 2016) that now exist.
An event manager could post an event on Facebook and monitor the responses through comments and shares to determine who the consumers want to share the event with. Trends could be something as simple as special dinners resulting in primarily women tagging men on the platform.
Is Big Data actually a new idea?
Some researchers argue that the ‘Big Data’ concept isn’t new, it’s simply a term used to push businesses to outsource data-mining and analysis.
This theory is unlikely though, any internet user knows the depth of information available and how specifically targeted some areas can be. This massive amount of information directly relates to the consumer data gathered.
The concern of privacy arises regularly when Big Data is concerned. Although websites and platforms have privacy policies to cover them from a legal perspective, there remains ethical issues. Data storage, management and relativity are important from an operational side. Other issues include the level of targeting, purpose of targeting and tracking of personal details.
Big Data is more than an analytical tool for marketers, it also means consumers receive better content that is personally interesting. The mutual benefits align with the growth of a semantic web and mass personalisation.
Chaffey, D, Ellis-Chadwick, F. 2016, Digital Marketing, 6th Edition. Pearson (Intl), VitalBook file, P. 651
Chen, H., Chiang, R.H. and Storey, V.C., 2012. Business Intelligence and Analytics: From Big Data to Big Impact. MIS quarterly, 36(4), pp.1165-1188.
McKinsey Chief Marketing & Sales Officer Forum, (2014). Big Data, Analytics, and the Future of Marketing & Sales. USA: Createspace Independent.
Soubra, D. (2012). The 3Vs that define Big Data. [online] Datasciencecentral.com. Available at: http://www.datasciencecentral.com/forum/topics/the-3vs-that-define-big-data [Accessed 10 Sep. 2016].
Steve, L. (2012). The Age of Big Data. 1st ed. [ebook] New York: The New York Times. Available at: http://s3.amazonaws.com/academia.edu.documents/34393761/2_The_New_York_Times_on_The_Age_of_Big_Data.pdf?AWSAccessKeyId=AKIAJ56TQJRTWSMTNPEA&Expires=1473636025&Signature=gSGK1i1w6tIlZwxUAXgW6aIWh3U%3D&response-content-disposition=inline%3B%20filename%3D2_The_New_York_Times_on_The_Age_of_Big_D.pdf [Accessed 10 Sep. 2016].
Wu, X., Zhu, X., Wu, G.Q. and Ding, W., 2014. Data mining with big data.IEEE transactions on knowledge and data engineering, 26(1), pp.97-107.