Companies predict consumer behavior through ‘data mining’

If you have ever used a credit card, subscribed to a magazine or signed up for a store discount card, your name is in a database somewhere.

It doesn’t pay to worry much, though. Like government agencies, businesses are much more diabolical in movies than in real life. Experts estimate that only 7 percent of companies are using the information they gather. Even fewer are smart about it – as anyone who has sifted through a pile of worthless junk mail well knows.

But that’s changing. In the past decade, the value of storing customer information has risen as new techniques have emerged to discover patterns and associations in the data. The young science of “data mining” promises companies the power to predict consumer behavior.

Unlike mutual funds – which come with the warning that past performance is no guarantee of future results – people’s past behavior is usually a pretty good predictor of what they’ll do next. If you rented an action flick last Friday and the Friday before, chances are you’ll be stopping at Blockbuster this week for another.

Transaction data – what you bought and when – is a powerful way to predict future shopping decisions, said Usama Fayyad, a onetime NASA scientist who left Microsoft to create Bellevue, Wash-based digiMine. “The only way you can understand your customer base and serve it better is to crach the code of behavioral data,” Fayyad said.

Though people like to group each other in neat categories based on race, age and ethnicity, data miners delve for connections based on behavior.

“Humans like to think about demographics: young, old, Asian or what have you. It’s easier for the human mind to understand, but behavioral data is a more powerful predictor,” Fayyad said.

The buying preference of a black man and a Latino man who both love steaks and action flicks might be more similar than those of two black men with opposing tastes. “Behavior is the most powerful diversity,” Fayyad said.

But there are a few data mining companies that do look at demographics, including Geoscape International of Miami. General manager Cesar Melgoza said Geoscape helps identify potential customers by race and ethnicity for clients that want to target those markets specifically.

His company’s tools can help provide lists of people by country of origin, ethnicity, race and socioeconomic status. Geoscape looks at the full name of a person and assigns probability-like scores to each portion to figure out country of origin. For example, if a person has a traditionally Latino first and last name, he is more likely to be Latino.

Understanding your customers is about learning what they like to buy, not which racial or ethnic group they fit into, said Todd Gutschow, co-founder of San Diego-based HNC Software Inc. “It’s not: ‘Are you African American or Caucasian?’ It’s: ‘Who are you?’ We can begin to treat people based on their individual behavior,” Guschow said.

Most of the data that companies gather is blind to race, said obert Grossman, director of the National Center for Data Mining at the University of Illinois at Chicago.

Billing records, warranty cards, coupons, store discount cards, phone surveys and Web questionnaires all help companies paint a picture of their customers that’s less about race and more about income and buying habits.

Persuading companies to actually use the data they collect is an ongoing challenge. “Companies do collect and store a heck of a lot of data, but if you ask them they do with it, the answer is typically nothing,” Fayyad said. “Companies have been starved for meaningful views into their data.”

The web has been a rich field for data mining because the shoppers leave digital trails that reveal which products they clicked on and purchased.

In the physical world, retailers like to think they can analyze their customers without the help of computers. But a large retail store might have tens of thousands to hundreds of thousands of items for sale. “It’s very hard for a human being to analyze this data,” Fayyad said. That’s why so much marketing involves cruder strategies such as bulk mailing. Data miners like to call their science the cure for junk mail.

Financial services companies are probably the most sophisticated users of computer technology, including data mining. HNC got its start in the 1980s detecting fraud among credit card users by analyzing transaction data. That’s why today if you make a purchase that’s out of the ordinary, you’re likely to get a call from your credit card company ensuring that it’s on the level.

Using data mining techniques, researchers were able to determine that certain shopping patterns indicate fraud. For example at a gas station followed by a very large purchase for a big screen TV raises a red flag. Credit card companies have learned that thieves will often test a card to see if it works before spending the big bucks.

Today, HNC is using the same techniques to predict behavior.

By: Julie Moran Alterio

Source: The Marion Star


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