Almost everyone who's shopped online has had the experience of a vendor 'recommending' products that might interest you. If you're like me, you've sometimes wondered how on earth they thought you would ever want something like that! Turns out there's a lot of technology and analysis behind those recommendations. IEEE Spectrum reports:
All of these suggestions come from recommender systems. Driven by computer algorithms, recommenders help consumers by selecting products they will probably like and might buy based on their browsing, searches, purchases, and preferences. Designed to help retailers boost sales, recommenders are a huge and growing business. Meanwhile, the field of recommender system development has grown from a couple of dozen researchers in the mid-1990s to hundreds of researchers today—working for universities, the large online retailers, and dozens of other companies whose sole focus is on these types of systems.
Over the years, recommenders have evolved considerably. They started as relatively crude and often inaccurate predictors of behavior. But the systems improved quickly as more and different types of data about website users became available and they were able to apply innovative algorithms to that data. Today, recommenders are extremely sophisticated and specialized systems that often seem to know you better than you know yourself. And they’re expanding beyond retail sites. Universities use them to steer students to courses. Cellphone companies rely on them to predict which users are in danger of switching to another provider. And conference organizers have tested them for assigning papers to peer reviewers.
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Have you ever wondered what you look like to Amazon? Here is the cold, hard truth: You are a very long row of numbers in a very, very large table. This row describes everything you’ve looked at, everything you’ve clicked on, and everything you’ve purchased on the site; the rest of the table represents the millions of other Amazon shoppers. Your row changes every time you enter the site, and it changes again with every action you take while you’re there. That information in turn affects what you see on each page you visit and what e-mail and special offers you receive from the company.
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Companies like Amazon collect an immense amount of data ... about their customers. Nearly any action taken while you are logged in is stored for future use. Thanks to browser cookies, companies can even maintain records on anonymous shoppers, eventually linking the data to a customer profile when the anonymous shopper creates an account or signs in. This explosion of data collection is not unique to online vendors — Walmart is famous for its extensive mining of cash register receipt data. But an online shop is much better positioned to view and record not just your purchases but what items you considered, looked at, and rejected.
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So how well do recommenders ultimately work? They certainly are increasing online sales; analyst Jack Aaronson of the Aaronson Group estimates that investments in recommenders bring in returns of 10 to 30 percent, thanks to the increased sales they drive. And they still have a long way to go.
There's more at the link. Very interesting stuff for the geek in you.