Blog post week 10: Big Data, Predictive analytics and the Hash Tag
Every time we sit down at a computer and open an Internet browser, we are sending a torrent of information or “data” out into the world. Everything from social media posts online shopping patters and transaction records can be collected, stored and used to help companies market their products more effectively. This vast well of information is referred to as “Big Data”, and for those who can harness this resource, there are significant competitive advantages to be gained. But just what is “Big Data?”
Big Data refers to the recent and “exponential growth and availability of data, both structured and unstructured” (Davenport & Dyche, 2013). This information is used by businesses to create more effective and accurate marketing techniques, by analyzing and predicting patters of consumer behavior and spending. This is achieved through the process of “machines learning from data” (Siegel, 2013). A variety of companies are using this method of predictive analysis to help improve their products; like Netflix recommendation system for Movies and TV shows, or advertising companies using your data to predict which products you’re most likely to be interested in, and tailoring their ads accordingly. Eric Siegel (2013) refers to this as “Technology that learns from experience (data) to predict the future behavior of individuals in order to drive better decisions”.
Although these predictions are not always 100% accurate, they do help in identifying consumers who are more likely to respond to an ad, or have use for certain products. This helps to increase the amount of relevant advertising a consumer will receive, and reduce the amount of unwanted “junk mail” they receive.
“In this way the business, already playing a sort of numbers game by conducting mass marketing in the first place, tips the balance delicately yet significantly in its favor and does so without highly accurate predictions” (Siegel, 2013)
One of the most valuable sources of data for these companies is social media, and one of the most effective tools in organizing this torrent of information is through use of the “hashtag”. Since their first appearance in 2007, hashtags have been a central part of social media, Twitter in particular. They are used to help connect an individual’s content and thoughts with other people's related content in a simple and quick way. By doing this, it has helped social media to organize and structure content, and “help social media users participate in wider community conversations” (Cazier, 2013).
Recently, other social media sites like Facebook and Google+ have begun to adopt the hashtag. While on one hand this can been seen as an attempt to harness the social advantages of hash tags, companies are likely to use this as another method of “big data” analysis to increase their advertising and marketing potential. This sentiment is reflected by Clay Cazier (2013), who writes “Hashtags are, by their very nature, harnessing the potential of people’s thoughts and interests and turning them into mineable information”.
References:
Davenport, T. H. & Dyche, J. 2013. “Big Data: What it is and why it matters”. Accessed May 8, 2014 http://www.sas.com/en_us/insights/big-data/what-is-big-data.html
Siegel, Eric. 2013. “Introduction – The Prediction Effect.” In Predictive Analytics, 1-16. Hoboken, NJ: John Wiley and Sons Inc.
Crazier, C. 2013. “Hash-tags as Big Data”. PmDigital, July 10. Accessed May 11, 2014 http://www.pmdigital.com/blog/2013/07/hashtags-as-big-data/

















