Every day, 2.5 quintillion bytes of data are created. Consider then that 90% of the data in the world today has been created in the last two years alone.
That data comes from myriad sources, including climate information gathering sources, unstructured data posts to social media sites and blogs, digital pictures, videos and GPS signals.
In fact, the list can be considered endless*. With this being said, it is obvious that big data is getting bigger every day.
Diamond in the rough
Sentiment analysis is the method of automatically locating and analysing digital content in real-time from across multiple channels such as Web sites, e-mails, forms and surveys in an attempt to hone in on customer sentiment that is buried within this textual data appearing every day. The goal of sentiment analysis or opinion mining is to determine the attitude, opinion, emotional state, or intended emotional communication of the message.
As is the nature of the Internet, varyingly complex and somewhat generic sentiment analysis tools are just a click away. As long as it is being talked about somewhere on the Internet, these models can and will determine the current snapshot opinion for anything the mind can conceive of.
From Facebook and Twitter, specific sentiment tools to more complex generic tools that analyse the whole Web sphere, to works of art which crawl the Web for appropriate sentiment and display them in LCD format, to using complex sentiment models to determine where earthquakes have occurred so that subscribers can be warned, to sites that will give a snapshot of how the world feels - again, the list is almost endless.
However, accurate analysis is a complicated and multi-step process. The information (nuts and bolts) that there is an interest in measuring needs to be identified and then further broken down. Yes, sentiment is interesting; however, the sentiment about what is truly important is key to determine. Is it a product, a service, a brand? This needs to be high level as well as very granular. Not just general brand information, but also the nitty-gritty of the service or product on offer. This is generally detected using a monitoring solution that recognises names, terms, and concepts and then uses natural language processing to associate sentiment and other attributes to the features.
Effective marketing strategies
While many companies nowadays are embracing the idea of social media to get their message across rapidly, many of them are completely failing to realise that marketing is no longer a one-way, structured monologue with the consumer largely in the dark.
Today's world is as small as the amount of time it takes me to press enter on my keyboard.
Nowadays, with the staggering amount of unsolicited consumer opinion being aired, that monologue has out of necessity become a dialogue.
Companies now need to make the connection:
* from data
* to insight
* to understanding
* to strategic actions
* to ROI
To ignore this form of customer interaction and analysis is, quite frankly, an unacceptable risk.
Facebook is quite possibly the best example of consumer-to-consumer transfer of opinion and information. For example, say Company A creates a company profile on Facebook. I 'like' the profile and become part of its fan base. I encourage my friends to join. The platform is primed to take advantage of my expression of positive sentiment and that expression encourages the like-minded fan base to also express themselves. However, what happens when I display negative sentiment? Unchecked and unmanaged - this could quickly develop into a public relations nightmare for Company A, especially if I have a large and loyal group of friends.
Consider that there are over 800 million active Facebook users, the average Facebook user has 130 friends and is connected to 80 pages, events and groups. There are over 3.5 billion pieces of content (Web links, news stories, blog posts, etc) shared on Facebook each week**.
Yet, somehow, in the face of this overwhelming customer presence, 95% of Facebook wall posts are not answered by brands**.
It must be understood that managing the positive and, quite crucially, the negative has become a full-time job that does not keep regular working hours. Today's world is as small as the amount of time it takes me to press enter on my keyboard. A world that is always awake. And being able to keep a finger on the pulse of a very fickle consumer base will become one of the biggest challenges facing companies this century.
This is where sentiment analysis really comes into its own. The near instantaneous, automated analysis of the sentiment that is being expressed at any given moment at any given point on the Internet is vital for the success of any company that is hoping to be successful.
Companies that can successfully harness the unlikely mix of big data, sentiment analysis and social media may just possibly, for the first time in human history, be able to mine the void.
* http://www-01.ibm.com/software/data/bigdata/
** www.digitalbuzzblog.com/social-media-statistics-stats-2012-infographic/
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