What Does Your Data Say About You?
Data is collected every second of every day. Every action made generates a piece of data, and big data leverages the advances in computing to make sense of the information and turn it into action to better run a business or provide a better service to customers (The Economist, 2012). The Economist video (2012) expresses the view that we do not necessarily live in an age of information, but one of network intelligence. Existing digital methods include data gathering, processing, analytics and visualisation, with each technique providing evaluation in a range of industries (Woodford, 2014).
When using social media, trends and user involvement can be measured via hashtags. One particular use is gauging engagement with television, as Woodfoord, Prowd and Bruns (in press) explored using telemetrics. Many television programs and networks will engage audiences via hashtags. ABC Family program Pretty Little Liars, as example shown below, uses hashtags relevant to the events of an episode to generate discussion and allow viewers to categorise opinions. Assessing the number, frequency and content of tweets and hashtags helps networks to understand their viewership demographic and continue creating relevant and popular content. Although much of this is location specific. Take Big Brother for example; in the US there is little correlation between viewers and tweets, whereas in the Australian version of the same program, there is a high correlation between viewer count and tweets (Woodford, 2014). As such, US models should not be applied to Australia, and instead location appropriate techniques must be applied.
Pretty Little Liars Screenshot Image Sourced from: http://commercialbreaktv.wordpress.com/2013/02/27/pretty-little-liars-out-of-sight-out-of-mind/.
This use of data analysis demonstrates the scale of information released and the influence it can have. This has become so widespread that companies such as Nielsen SocialGuide and BlueFin Labs, have in fact been bought out by Twitter (Woodford, et al., in press). What commercial organisations must bear in mind though is the variance amongst the Twitter audience. Woodford (et al., in press) found that while the variance in ratings are mirrored in tweets and unique users, actual user variation is more extreme. Supporting Woodford (et al., in press) Harrington (2013) states that further development of analytical processes is required to understand how television is experienced by audiences in their everyday lives.
The data that organisations are collecting could alarm the people from whom they are collecting it. Coles and Woolworths both use their award programs, Fly Buys and Everyday Rewards respectively, to track the buying habits of their customers. Doing this permits them to send personalised, targeted marketing to each of their customers. The supermarket giants rely on this data so heavily that Woolworths has outlaid at least $20 million for a 50% non-controlling stake in data analytics company Quantium (Mitchell and Ramli, 2013). In turn, Quantium will be able to tap Woolworths’ de-identified customer data to improve services to a wide range of clients including eBay, Telstra, Suncorp and Qantas (Mitchell and Ramil, 2013).
Considering the large customer base of Woolworths and other large corporations, this use of data could frighten some customers. Especially when data is passed on to second party organisations. Many people do not feel comfortable with the level of knowledge organisations have on their spending habits. So while big data may be a great asset to organisations, consumers may be opposed to the analytics employed.
Reference List
Commercial Break TV. 2013. “Pretty Little Liars: Out Of Sight Out Of Mind.” Accessed May 8, 2014. http://commercialbreaktv.wordpress.com/2013/02/27/pretty-little-liars-out-of-sight-out-of-mind/.
Harrington, Stephen. 2013. “Chapter 18: Tweeting about the Telly,” In Twitter and society, edited by Katrin Weller, 237-247. New York, NY: Peter Lang. Accessed May 8, 2014. https://qutvirtual3.qut.edu.au/qv/olt_material_search_p?p_unit_code=KCB206.
Mitchell, Sue and David Ramli. 2013. “Quantium leap for Woolworths.” Australian Financial Review, May 2. Accessed May 8, 2014. http://www.afr.com/p/business/companies/quantium_leap_for_woolworths_GVE7EDP9KOkqhdeH5rLw3I.
The Economist. 2012. “What is big data?” YouTube video, posted June 26. Accessed May 8, 2014. https://www.youtube.com/watch?v=ahZGEusG13A.
Woodford, Darryl. 2014. “KCB206 Internet, Self and Beyond: Week 9 lecture notes.” Accessed May 7, 2014. http://blackboard.qut.edu.au/webapps/portal/frameset.jsp?tab_tab_group_id=_4_1&url=%2Fwebapps%2Fblackboard%2Fcontent%2FlistContent.jsp%3Fcourse_id%3D_108110_1%26content_id%3D_5232447_1.
Woodford, Darryl, Katie Prowd and Axel Bruns. (in press). “Telemetrics: Towards Measuring Social Media Engagement with Television.” Accessed May 6, 2014. http://blackboard.qut.edu.au/bbcswebdav/pid-5234702-dt-content-rid-2118244_1/courses/KCB206_14se1/Woodford%2C%20Prowd%20and%20Bruns%20-%20Telemetrics%20Towards%20Measuring%20Social%20Media%20Engagement%20with%20Television.pdf.










