Technology Review reports on a number of new developments in retail, e-commerce, analytical marketing and data-mining/artifical intelligence-type techniques. The article makes a lot of points (see link below) but here's a short excerpt:
One of the most intriguing areas of research involves figuring out which customers are worth the trouble of wooing in the first place. In its Haifa, Israel, research lab, IBM is designing advanced statistical and machine-learning models that will differentiate customers according to their future value.
Researcher Amit Fisher developed one such model by studying a year’s worth of activity at one of Israel’s leading e-auction sites. From such factors as the number, frequency, and value of their transactions, Fisher was able to classify Internet users into different categories—along the lines of bargain hunter, repeater, one-timer, defector, valuable customer—and assign an economic value to each category. The model then sought to predict from just a few visits where a new user was likely to end up a year or more down the road. “We compared the customer ranking that was generated by our model to the true ranking of the customer according to their purchases,” says Fisher. In trials involving groups of more than 1,000 users, he notes, the model correlated almost perfectly with actual data collected from the auction site. Programs that seek to assess a customer’s lifetime value are not new; however, IBM says that Fisher’s model, which is being developed for commercial use through several of IBM’s businesses, is the first to make an accurate assessment of a customer’s future value based on just a few visits. What’s more, such a model is “domain adjustable,” Fisher says. It could be used in banking to determine whether to issue a loan or a credit card. Or it could be employed by retailers to target promotions to potential best customers and give priority to those customers during times of peak demand.
Fisher’s model works with minimal personal data and takes into account only a few variables. But for retailers bent on amassing much more complete data about their customers—and then using that information to “maximize” lifetime customer value through highly targeted ads and promotions—the data-mining challenge is far trickier, says Edwin Pednault, a staff researcher in IBM’s data analytics research group. “Now I want to take much more information into account,” says Pednault—who has been working on a model that would do just that.
Instead of looking at effects of marketing campaigns separately, as traditional data mining has done, Pednault’s model examines the patterns of a customer’s activity, such as the types of products she likes, how she responds to promotions, and her price sensitivity. When a company has that kind of information about its customers, says Pednault, it can begin to ask, “How are my actions motivating them to change from one [buying] state to another?” In studies of one major department store chain, IBM showed that using Pednault’s model to predict the effects of snail mail marketing—alerting customers about sales, store events, and new items from their favorite product lines or styles—resulted in a 7 to 8 percent increase in store revenues.
The article primarily focuses on fusing e-commerce with offline shopping but these techniques can be applied to any industry that has large numbers of individual customers conducting large numbers of transactions.
Another interesting bit:
A farther-out approach—bringing e-commerce to the supermarket shopping cart—is being tested by Stop and Shop of Quincy, MA, which operates 350 supermarkets in the Northeast. Dubbed Shopping Buddy, the technology consists of a wireless computer and data management system developed by IBM in partnership with the supermarket chain and software maker Cuesol, also of Quincy.
The paperback-book-sized device, introduced early last year at three stores near Boston, is installed in shopping cart handles. To use it, a shopper scans in his loyalty card; a simple graphical interface then appears, displaying such features as sale items and a customer favorites list. On the favorites list are the names of the things the shopper buys most frequently, whether he buys them in the store or has them delivered to his house by Peapod—which, in a neat post-bubble twist, Stop and Shop’s parent company now owns. The device creates a map of the store and displays a suggested route. Infrared beacons on the ceiling track the cart’s location, so the device can automatically alert the customer if any of his favorite items are on sale in the aisle he is currently browsing. The interface also lets the shopper wirelessly order cold cuts from the deli; an alert sounds when they are ready. Finally, an attached imaging scanner lets the shopper scan items as he puts them in the cart; as the cart fills, a running total is displayed. When it comes time for checkout, the cashier scans the shopper’s loyalty card, and all of the items in the cart are listed on the register screen. This saves time for both the shopper and the cashier.
I know a small company that aims to launch a similar service in Singapore. Watch this space.
Analytical marketing is a nascent opportunity across Asia for a number of reasons:
- Very few companies, whether in retail, banking, telecoms or elsewhere, are using these techniques. So this is an opportunity to steal a march over one's competitors.
- Preferences, cultures and transaction behaviour vary widely across even small sub-regions of Asia. Targeted marketing is the best or perhaps the only way to consistently make profits across such fragmented markets. Spending dollars on mass-media ad campaigns probably has pitiful RoI, if any.
- The long tail effect combines with the bottom of the pyramid concept. There are massive opportunities in serving low-income customer segments. But these can only be served profitably by targeted marketing efforts.
- Marketing campaigns targeted at wealthier customers could actually dissuade BOP customers from trying out the product. ("Oh, it looks expensive." or "I want shampoo but not in such a big bottle.")
- Or if the product being sold is meant specifically for low-income customers (e.g., microfinance), the cost of an ad campaign would probably not be justified, even if the product otherwise exhibits profit potential.
- Areas such as telecoms have seen booming growth in Asia. Telcos have not had to worry too much about customer acquisition and retention. But some countries are quickly approaching saturation point and growth is leveling off. Analytical marketing is the way forward.
Link: E-Commerce Gets Smarter
