Analysis & Commentary:

HOW ARTIFICIAL INTELLIGENCE DECODES CUSTOMER BEHAVIOR
by Lou Hirsh

Advances in artificial intelligence (AI) eventually could turbo-boost customer analytics to give companies speedier insights into individual buying patterns and a host of other consumer habits.

Artificial intelligence functions are made possible by computerized "neural networks" that simulate the same types of connections that are made in the human brain to generate thought.

Currently, the technology is used mostly to analyze data for genetics, pharmaceutical and other scientific research. "It's seeing little use in CRM right now, though I believe it has tremendous potential," Aberdeen Group vice president Bob Moran said.

Cutting-Edge Analytics

AI represents the cutting edge in data mining, a technology that uses special algorithms to extrapolate patterns from large amounts of customer information. While it is relatively new in CRM circles, data-mining that incorporates AI capabilities already is making an impact in the business world.

Among the companies studying the use of AI-enhanced mining is SAS Institute, a privately held software company specializing in business intelligence.

SAS officials claim that one client, financial services firm Dreyfus, was able to cut its customer attrition rate by more than 40 percent by using an advanced analytics program that helped identify and fix problems that were sending customers elsewhere.

Anne Milley, director of analytics strategy at SAS, said AI speeds up the analytics process and points users to deep logical patterns that algorithms alone might not pick up.

"Neural networks go after patterns that might be significant indicators of fraud," Milley said. It holds particular promise for alerting insurance companies to false claims, for example.

'Survival Modeling'

AI-enhanced analytics programs also provide "survival modeling" capabilities -- suggesting changes to products based on use. For example, customer patterns are analyzed to learn ways to extend the life of light bulbs or to help decide the correct dosage for medications.

High-tech data mining can give companies a precise view of how particular segments of the customer base react to a product or service and propose changes consistent with those findings.

"Even manufacturers are using analytics to get a clear look at what the end customer is looking for and what is driving demand," Milley said.

While current data-mining technology uses a "rules induction" process to establish patterns, AI-boosted mining can make deeper logical conclusions about affinity by further extrapolating the findings uncovered by the algorithms.

Cross-Selling Help

"If you find that some people are buying a certain pen, this tells you further that the same people have a preference for a particular brand of paper," said Michael Huang, product manager for CRM software provider Blue Martini.

Huang said that this information, in turn, will prove useful for cross-selling, targeted promotions and personalized marketing. It also can be carried over into companies' multichannel strategies.

"In the future, you're going to see a lot of software vendors looking for ways to use data at a deeper level," he said.

Aberdeen's Moran said the number of companies doing intensive research into AI-enhanced analytics -- including SearchSpace, HNC, Genalytics, Mantis and Computer Associates -- indicates it could be a major force in customer service in years to come.

"It has potential for any industry where you need access to very fine-grained information," he said.

Faster Reaction

In addition to further exploring customers' buying patterns, analytics could help companies react much more quickly to the marketplace.

According to Meta Group vice president Liz Shahnam, "intelligent agents" could let companies make real-time changes to marketing campaigns.

"New technologies would have the model refreshed on the fly based on each new incoming piece of customer information -- reaction to the campaign -- for a more targeted offer," Shahnam said.