Predictive Analytics and Targeted Marketing
Today’s marketplace continues to develop in the digital realm with an ever-increasing number of companies now interacting with consumers online. This technology also means that the vast majority of consumer behaviours can be easily tracked and stored. For marketing divisions this is a newly discovered gold mine with practically unlimited opportunity if utilised to full potential. “The process of machines learning from data unleashes the power of this exploding resource. It uncovers what drives people and…with the new knowledge gained, prediction is possible” (Siegel 2013, p.4). These consumer behaviour predictions are what marketers require for the optimal alignment of product advertising and promotion with their target audience. This method however, also poses ethical dilemmas. Data tracking could quickly become intrusive, especially given the consumer is often unaware of how they are being targeted or if they are being targeted at all.
Marketers often target consumers with predictive analytics or a “means to drive per-person decisions empirically, as guided by data” (Siegel 2013, p.12). It is scientifically based research and is much more accurate than traditional forecasting as it eliminates the need for opinion and possibly biased outcomes due to cultural expectations about purchase habits. It must be recognised however that subjectivity does still play a role when defining sets of data and interpreting why certain consumers behaved as they did. But possibly of most importance is the question of whether this new technology is really working for corporations?
As an internet user myself, I have witnessed on many occasions a change in advertising after an online purchase. It suddenly becomes much more targeted to products and services that I should theoretically be interested in however this causes a sense of unease. A study in the UK largely identifies with this, stating “69% of consumers say they find it creepy the way brands use the information they hold on them” (Strong 2013). This correlates with the concept of the ‘uncanny valley’, a term which originated in robotics but now is widely used to explain why people feel uncomfortable with businesses knowing too much about personal life choices and behaviours. Strong explains that “initially consumers enjoy the personalisation or marketing communications…however there appears then to be a line which is crossed where there is too much personalisation for consumers’ comfort” (2013). This is happening more frequently than ever before with a recent and famous instance including the big brand name, Target. The retail giant compiles big data about consumer purchases and in this instance advertising material relating to baby products was sent to a teenage girl causing outrage. Turns out Target had recognised the girl was pregnant due to recent purchases, all before her parents had knowledge of the pregnancy (Masnick 2012). This scenario highlights how unwittingly intrusive big businesses can be.
As technology develops, the marketing of products will continue to become more targeted and innovative as consumer data is further researched and understood. Corporations will have to consider however, the most ethical and unobtrusive methods of disseminating advertising material as this will affect how the business is seen amongst the public sphere and ultimately the bottom line.
References
Masnick, M., 2012. Getting Past the Uncanny Valley in Targeted Advertising. [Online] Available at: http://www.techdirt.com/blog/innovation/articles/20120217/03044617792/getting-past-uncanny-valley-targeted-advertising.shtml [Accessed 11 May 2014].
Siegel, E., 2013. Introduction: The Prediction Effect. In: Predictive Analytics: The Power to Predict who will Click, Buy, Lie or Die. Hoboken: Wiley, pp. 1-16.
Strong, C., 2013. The Big Data Arms Race Part Two: Consumer Perceptions. [Online] Available at: http://www.theguardian.com/media-network/media-network-blog/2013/oct/04/consumer-marketing-big-data-perceptions [Accessed 11 May 2014].
YouTube, 2012. Target Knows When Your Pregnant. [Online] Available at: https://www.youtube.com/watch?v=XH1wQEgROg4 [Accessed 11 May 2014].














