Big Data: Small targets

In the 2000 film, The Patriot, Mel Gibson taught his sons the lesson of “Aim small, miss small” when using their rifles. The idea being that the error associated with a given shot is minimized if you focus on a smaller target.  With the onset of the Big Data revolution, companies should be taking this message to heart.

The product lifecycle used to be that a company identified a need, developed a product to fill that need, and then attempted to identify a target audience to market the product.  Not only did this carry significant marketing costs, the distribution of their message could be too broad to gain any traction.  What if the product wasn’t as necessary as originally thought?  What if the price is wrong because the company thought the customer base was different than it actually was?  What if the product was over- or under-engineered based on customer expectations?

Now let’s ask a different question. What if the company already knew what the customer wanted, when they wanted it, and how they wanted to see it?  Now we’re talking about the power of Big Data and predictive analytics.  The power of making business decisions based on many isolated, dissociated characteristics about the customer, that when pulled together paint a vivid, and eerily accurate picture of their spending habits.

One example I would LIKE to see, to reduce the “junk mail” I get, is for credit card companies to analyze me and effectively stop sending me offers that have no relevance. By looking at my household income, number of open revolving credit accounts, my monthly credit card spend, geography, the type of car I drive, my age, gender, hometown, or even my registered political party affiliation, they would be able to determine that I was a poor candidate to offer a 0% APR, 3% balance transfer fee credit option to. If they could then “aim small, miss small,” they could reduce their marketing efforts by 75% and increase their success rate to astronomical numbers.

The most visible example of Big Data being used to evaluate customer activity is something that Netflix is attempting to achieve with great success. They have used their viewer’s data, likes and dislikes, to design the covers of their Netflix Originals. They have determined that certain visual stimulants, when combined, cause their viewers to select and watch a show more often than not. By doing this, they can increase the ratings of their original series and ultimately their profitability.

But both of the above examples leverage existing products, and are dependent upon redesigning their marketing strategy to attract customers. What if a company designed the product from the beginning knowing they could sell to 90%+ of their target audience? Let’s say Netflix took their data to the next level. Imagine if ‘House of Cards’ was WRITTEN, DIRECTED, and PRODUCED solely because they noticed a trend in viewers who like Kevin Spacey movies, courtroom or political dramas, movies set in present day. Imagine if they used their viewers’ movie selections to determine trends in plot twists, main character age, leading actress hair color, number of curse words per episode, to write the script.

How would you feel knowing that Netflix “played” you? They would have created the show, knowing with 95% confidence that you would watch, religiously, every episode; and they would make a boatload of money while you did. Unimaginable amounts of information are generated about you every day through the things you buy, watch on TV, listen to on your way to work, or even what you search for on your smartphone while waiting in line at the post office. Additionally, access to this information by companies is easier than ever before. With new data engines enabling companies to cross-calculate these previously irrelevant characteristics and exploit the customers’ habits, wants, and needs, an air of skepticism may arise.  But short of asking the public to be more mindful of every little thing they do to prevent this data being collected altogether, we have to take on faith that companies will be responsible with our subconscious consumer desires.

This is the direction that Big Data will be taking our world. You can be skeptical of how much these companies know about you and what they are doing with that information, but, you can’t hate getting what you want.  And Big Data knows what you want.

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