Over the last few years, unless you were in a very remote part of the marketing world, the term “Big Data” has become increasingly prominent. Just what is it? How important is it going forward in the discipline of Consumer Behavior and the world of Advertising and Marketing?
To me, Big Data is the legitimate heir to popular terms of the new century such as dot.com, social media, and wireless. It means a lot of data. No joke! That is it!
The issue to me is not that we have more data than ever before, a great deal more of it, but we have far more analyses. A tremendous amount more.
The driving force of this marketing or sales revolution is not the massive data itself. It is the AVAILABILITY of the information. To repeat, Big Data means more analyses, but, at the same time, it also means more bad analyses as well. In today’s world, there is no way to escape people crunching numbers (I have done it forever). And now, marketers and analysts have vastly more numbers to review.
Today, by employing Big Data, marketers, especially online players, know a great about their regular customers and they are constantly fine tuning their methods. A friend said that he is searching for the holy grail of communication--making the right offer to the right person at the right time.
How do they do it? To wildly oversimplify, they essentially get needed information two ways:
1) Loyalty cards--This is clearly the most direct way for a marketer to learn your shopping habits. Retailers “bribe you” in essence, by obtaining your personal data with rebates, gifts, or other benefits. The best example that I have ever found was a few years back when JPMorgan Chase issued an Amazon credit card. The carrot that they offered was that you received three reward points for every dollar purchased on Amazon with the Chase Amazon card. All other purchases received one point for each dollar spent with the card. With a powerful incentive in place, a large number of people put much of their expenditures on that one card and used Amazon more often. So, in crude terms, Amazon gets the platinum mine and you get the shaft. Only a few would think this. Most would say they get the benefits of a souped-up Amazon reward plan. A handful, generally very mature would worry about privacy. The younger demographic by a rate of 95% to 5% would opt for convenience over privacy. So, with the loyalty card Amazon has a rather clear view of your spending habits. They can customize offers to you and others like you to push you over the edge and grab a deal.
2) Loyal or Regular Customers--A retailer or company site will graze through your past shopping records and look for clues to your shopping behavior. If you come up without a clearcut profile, they will link you with customers who “look like” you in some way or share several demographic characteristics. This leap of faith is known as PROXY DATA and can include basics such as age, income, nine digit zip, education, subscriptions to selected magazines and even if you have a cat or a dog. The mountain of Proxy Data that is being built up almost defies description. Companies have massive databases that cover nearly 75% of all US Households. They peddle this information to many takers and slice it up in infinite variations. A few examples are:
1) The basics such as age, gender, education, income and ethnicity
2) Consumption data--What do this household spend on liquor, fine wine, even ice cream. Ice Cream? A quick story. On Saturday, my wife sent me to a toney grocery store to pick up two items. As I passed the ice cream section, the marketer in me stopped. They had a brand unfamiliar to me that was selling for $7.25 cents a pint. I laughed to myself and wondered who would be buying ice cream priced at over $50 a gallon. An instant later, a very beautifully dressed woman said, “Excuse me, sir, may I get in to the freezer.” As she put two pints of the designer ice cream into her shopping cart, she smiled and told me that her daughter was home for Thanksgiving break and just loved this ice cream. I very quickly drew a demographic profile of the lovely mom. Coincidentally, we checked out at almost the same time and left the store simultaneously. My hunch was correct. She hopped in to a new Land Rover and, as she drove away, I saw a sticker on the rear window for both Brown University and Williams College. With that, I could narrow her home to one of three zip codes. If I can do that by inspection, imagine what a marketer can do with a few dozen data points!
3) Lifestyle data--How often have you moved (average home stay is seven years in the US) and how long is your marriage and is it your first.
4) Neighborhood information--How long do people commute to work and how many own their dwellings
In 2008, when the economy appeared to be in shambles, the great Chris Anderson wrote a magazine article entitled “The End of Theory.” Anderson is the author of THE LONG TAIL (a book which I highly recommend) and is the former editor of WIRED Magazine. It was the first article that really brought the concept of Big Data into the mainstream. His thesis was that data would become so big and so complete that models to reach target prospects or even project sales forecasts would be obsolete.
To quote, the lead passage from his article we find: “This is a world where massive amounts of data and applied mathematics replace every other tool that might be brought to bear. Out of every theory of human behavior, from linguistics to sociology. Forget taxonomy, ontology, and psychology. Who knows why people do what they do? The point is that they do it and we can track and measure it with unprecedented fidelity. With enough data, the numbers speak for themselves.”
Now, that you have looked up the definitions of taxonomy and ontonology, let us continue.
If you study Consumer Behavior with any depth, you soon realize that the true causes for buying defy simple measurement. With so much data available, we may weigh various data points incorrectly and make unwarranted assumptions.
Big Data is wildly useful but it cannot tell you why fads occur or why all of us at one time or another make impulsive purchases. Statisticians refer to these as LATENT FACTORS as they cannot be seen or observed. Is Anderson totally right about the future of Big Data? I doubt it for one big reason. My favorite statistician, Kaiser Fung, put it beautifully when he wrote, “It is just hopeless to distill the kaleidoscope of human behavior in to a set of equations.”
What does this mean for the future of both Consumer Behavior as a marketing discipline and for the future of Integrated Marketing Communications? Plenty, but the impact of Big Data is not clearcut. One could make a safe bet that as logarithms improve marketers will depend more on online and mobile options to reach people. Traditional media has to struggle even more than they do today. Facebook may grow in stature as the word of mouth it provides re products and services will help while legacy media flounders.
Remember, that statistics are no substitute for judgement but unbiased analyses should be a great help to marketers going forward.
If you would like to contact Don Cole directly, you may reach him at email@example.com