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Business Strategy Viewpoints

In Data We Trust

by Björn Bloching

Beer and Nappies: How the Customer Data Revolution Started

There were harbingers of the customer data revolution in the early 1990s—on the shelves of Wal-Mart’s stores, among other places. The world’s largest retailer had invested early in database systems, initially in order to optimize its logistics and warehousing. A number of anecdotes circulate about how the company’s marketers had their eureka moment regarding information technology. A Wal-Mart manager told us it happened like this: a smart cookie on the board never tired of stressing that in the databases’ jumble of information there were unbelievable treasures, of which no one had yet dreamed. He convinced his colleagues to set up a competition with substantial prize money. Two people in the IT department started to sift through billions of lines of receipt data, where they found surprising correlations. And what do you know? From early evening onwards, beer and nappies often ended up in the same shopping trolley. It’s not hard to find the psychological triggers behind this purchase pattern. Men on their way home are not thrilled by the thought of soon having to change nappies, so they reward themselves in advance. The two IT workers had suggested placing beer offers next to the nappy shelves. Test markets showed that impulse purchases shot up. And this simple but effective marketing measure of “shelf optimization” was introduced in all stores. The beer and nappies example is now 20 years old.

Back then, only a few large corporations had the resources for data mining—in other words, the intelligent analysis of structured data sets. The technology is more democratic now. Today, any pizza delivery service can use databases to improve customer retention. The more advanced users know what their customers are willing to pay and have an approximate idea of what and how much they purchase with the competition. Google, Amazon, Apple, eBay, and Facebook have built their global business models on (customer) data. They and their all-conquering information point to where things are going in the realm of comprehensive customer knowledge and differentiated communication.

Whales in the Sea of Data: The Age of Guessing Is Over

The customer data revolution is part of a larger change. After the personal computer and the Internet, digitalization has now reached a third stage. Data storage is becoming ever cheaper, data processing ever faster, and the algorithmic software that analyzes the data is ever more intelligent. Information scientists have dubbed this revolution “Big Data.” The data sets are growing exponentially. We are just learning how to use informational raw material in all areas of life. Data are the stepping stone to a new level of understanding; Big Data will change society, politics, and business as fundamentally as electricity and the Internet did.

Wired magazine’s founder Kevin Kelly sees the Internet as a “magic window.” Only little children had dreamed that such a window would ever exist. IT systems in the era of Big Data can do what IT visionaries foresaw decades ago. They can collect the knowledge of the world on a screen. They spot connections that are too complicated for people to grasp on their own. And they form models that use calculations of probability to give us a window into the future. Computers know us better than we know ourselves—or, at least, they are often more reliable than we are at saying how we will behave in certain situations. Based on our customer profile, car hire companies know how much petrol will be in the tank when we return the car. An analytically driven online retailer knows the probability of a regular customer buying something at a certain price. And the retailer will know how much has to be invested in personalized advertising in order to make the sale. Credit card companies can predict with a high degree of success which couples will divorce in the next five years.

There is no lack of data with which to measure reality, nor is there a lack of business-relevant data. The smartphone has removed the distinction between the online and offline worlds. It translates our day into a stream of data. Digital payment systems are ever more popular and bring purchases out of the anonymity of the bricks-and-mortar world. Businesses themselves leave ever more digital tracks and so become increasingly transparent in business-to-business markets. At the same time, we are learning to recognize patterns in the exabytes (that is, 10 to the power of 18 bytes) of publicly accessible data—for example in the relationships on social media, where the motto could be “show me your friends and I will tell you who you are.” We can use these patterns for predictive modeling in order to calculate the probable behavior of groups and individuals. The idea might not be one we are fond of, but as consumers we are predictable. The value of data grows when they are linked up. If this happens in real time, the door to a new age of customer interaction is opened. The era of intuition is over. Not only can IBM information technology beat the human all-time champions in answering ironic, trickily formulated general knowledge questions on the cult US quiz show Jeopardy!, but when IT has access to the right customer data, it also sells better than the experience and gut instinct of marketers. And that’s not someone’s opinion; it is empirically provable.

SAP’s CEO Jim Hagemann Snabe describes the challenge of data mining and business analytics in our age of huge quantities of data as the need to find the “needle in the haystack” in real time. A marketer who is well-versed in IT put it nicely when he said, “We have to find the whales in the sea of data.” Condensed into a single word or slogan like a classic ad, it might go: “Crunch! Crack the data sets!” Your own, and the easily available ones floating in that sea! If you don’t do it, others will. Analytically driven companies know the markets they can address much better than those businesses that don’t work their data sets hard; they can segment their target groups more appropriately, and they are able to interact with customers in a more personalized way as they know their customers’ needs.

Data-based marketing offers businesses a wonderful opportunity to become more intelligent than the competition. In 10 years’ time at most it will be seen as a matter of simple “hygiene” for customer data to be gathered and evaluated intelligently. In other words, companies without this capability will disappear from the market. And, moreover, customers can now crack the data too. Checking a price comparison app on your smartphone as you stand in front of a shelf is just the start.

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Further reading

Books:

  • Davenport, Thomas H., and Jeanne G. Harris. Competing on Analytics: The New Science of Winning. Boston, MA: Harvard Business School, 2007.
  • Jeffery, Mark. Data-Driven Marketing. The 15 Metrics Everyone in Marketing Should Know. Hoboken, NJ: Wiley, 2010.

Report:

  • Brynjolfsson, Erik, Lorin M. Hitt, and Heekyung Hellen Kim. “Strength in numbers: How does data-driven decision-making affect firm performance?” Sloan School of Management, April 2011. Online at: tinyurl.com/cuh3uqy [PDF].

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