Beyond search and recommendation engines

When searching for information, being it for a book recommendation, what the next hot tech product will be or the best recommendation for a restaurant in your neighborhood, the traditional way was to start with a search engine like Google, Bing or Yahoo. With the proliferation of smart phones, and with that dedicated apps that performed mostly single purpose recommendations, the paradigm still remained the same. As a consumer, you had to trust that when you ask or Yelp about the best Indian Restaurant near you, the results would be unbiased and fit your expectations.

Though we can assume that for the most part, this would be true, the one important thing to realize is that any recommendation should be taken with a grain of salt. Why you may ask? Because of the profit motif. In the era of Google Ad-Sense and syndicated ad-networks that track you across the web to present more targeted advertising, identifying alternative options to finding information other than traditional avenues are important.

This is where Social Media became a big player. I’m not talking about Facebook or Twitter’s ad platforms, but rather, about the connections you form in those social networks. The study of these social networks focuses on the social structure of relationships around a person, group, or organization affects beliefs or behaviors. Translated, this means shared attributes and levels of trust that cannot easily be formed by companies using branding. Perhaps Apple showed great promise forming a cult around its products that highlighted a high level of trust and shared attributes among its followers. This is however not an easy feat, and most companies will never attain such cult status for their product offerings.

So this leaves a company with two options. Either bow to the always-changing guidelines and rules around search engine optimization (SEO) or focus efforts on getting your products into the social networks of target costumers. Perhaps the best known term for the second option is getting your product to be “viral” which indicates it’s spreading like a disease around social networks. This by itself has become a huge area of investment for companies as well working to ensure their products are being liked, shared, re-tweeted etc.

So then the question is – what do you need to enter this area of product promotion that does not rely on a Google algorithm to ensure you rank higher on a search page than the competition? The answer as I see it; Social and Behavioral Psychology to research and create models that can be used to test hypothesis, using tools such as Statistical Modeling, Predictive Analytics and Big Data. A few years ago I came to this realization and found myself going back to school to study Psychology with a emphasis on Social, Behavioral and Cognitive areas that I can utilize to analyze and create models to both test hypothesis and make predictions. Currently, I’m working on the second part of my toolset, and that is being able to take action on the theoretical aspects of Behavior Modeling by studying Predictive Analytics at Northwestern University. The Masters of Science in Predictive Analytics (MSPA) program is one of only a few applied statistical programs available from top tier schools in the USA, and with the predicted shortcoming of Data Scientists in the future it is perhaps one of the best investments I have made in myself in a long time.

With this blog, I will share various topics that I find interesting, as well as discoveries I make while working through the MSPA program as well as professional experience in the areas of Big Data, Data Science and Software Engineering. Naturally, I have some personal interest that I engage in and is part of my life such as the Martial Arts, Zen Buddhism and healthy living through exercise and a cruelty free diet. Thank you for reading all the way to the end of this firs post on my new blog site and feel free to comment and connect with me on the various social sites.

 Beyond search and recommendation engines

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