Enough has already been said about the scary amount of information about us that others know through social networks. Admittedly, being the social animals that we are, we tend to take this scare with a pinch of salt and probably think hard to write a witty one-liner and post it as a status message aiming to get 20 'like's. Hence this article does not in any way force you to forbid social networking. All it tried to do is to make us aware of how the information we let loose can be used (read sold). I, being one of the so-called social animals myself, start this article with my witty one-liner.
Social network indulgence is subject to privacy risks. Please read data mining carefully before updating status !
Social networks strive to influence and arrange contact and information sharing of many people. Meanwhile they also develop statistical tools to eavesdrop and sell information to the giant ears of the businessmen who eternally want that elusive root cause. This is normal statistical analysis. These sites also sell information to another set of giant business ears which want fodder to run their predictive machines. Fed by information input about us through social networks, marketers decide what to say to whom and whom to say what.
Let us look at five ways in which social networks can mint money through predictive analytics.
Matchmaking/Recruiting : Some HR professionals say that finding the right employee is like finding the right spouse. In that light, companies are serial polygamists and the society wants it that way for the greater good too. Social networks act as the perfect matchmakers to match right employees with right bosses. Information is available from both parties and all the sites have to do is run an intelligent match probability for the applicants and tell employers! LinkedIn does it and rightly so we flock there. As recruiting happens this way, the literal matchmaking happens in two ways through social networks, though only one will earn revenues for them. The matrimony sites do the same by predicting the matching accuracy for both parties. Social networks can feed them the vital information about the parties for the matrimony sites to enhance their 'happily married through us' rate. The other non-revenue generating mode will be well known to all social animals who got a date from a person who they just met online. In this case, the networks can only hope that they both have a great date and update the world about the experience soon after for them to sell their status messages.
Sentiment Analysis: Social networks are just the right sources to analyse public sentiments now. Every major happening goes through a round of social network discussions before dying from public memory (which is happening at a very rapid case now). Who will be interested to know these sentiments? Politicians, New product launchers, Policy makers etc. Customers with big purses, really ! Social networks make merry. These customers can also identify popular influencers through these predictions and strategise their actions to gain their favour. Twitter is a good example. From the days of celebrities in Twitter, now we see Twitter celebrities who rose to fame only through their 140 characters. Social networks are also trying their hand at predicting election results. This link will explain it interestingly.
Market fluctuations: Sentiments do not only play a major role in politics and product launches. They rule the stock market! Social networks simply adopt the same predictive power to mint money in the stock market. Tweets and updates by traders who are directly facing the full impact of sentiments offer the information for the networks to predict which share will be bear/bull the next day.
Recommendation Engines: We all have studied in eight standard physics that an ideal engine is not practically possible. Well, recommendation engines aided by predictive powers of social networks are threatening to break that rule by their scarily close-to-thought suggestions. They are fast becoming mind readers aided by predictive statistics.
Location Based Marketing: They know what we speak, what we think and what we feel. So naturally they know where we are. Social networks can also predict where we will be as individuals or groups. Marketers can use this predictions to reach before us there and wait for us to roll out their irresistible offers. Imagine you take great pains to gather information online and fix a perfect secluded honeymoon in the Bahamas, only to end up being greeted by a South-Indian restaurant waiting for you there at the airport with his "I knew you will come here now and I knew you will miss your favourite Masala dosa. Why don't you try our Dosa?" dialogue. Not totally impossible !
Thanks to Dr Rodo Kotorov's article for providing good references.
Cheers
GS
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