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Research Study Sets Record Straight on Recommendation Engines

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Recommendations Shopping

Recommendation engines, also known as recommendation systems or simply recommenders, are the mechanisms found on Web pages on the Internet that provide recommended pages or links to the viewer of the page. These systems often base recommendations on a user’s browsing habits, more specifically his past Web pages visited and keywords typed into built-in search engine.

For web developers, making use of recommendation engines is a lot like playing with fire, as many users find them intrusive and irritating. The key to maximizing the potential of these systems is to actually have them provide recommended content that users will find useful.

But even that is just one half of the equation, as outlined by a recent study on the behavior of Internet users with these recommendations. The researchers behind the paper sought out to understand how recommendation systems have influenced the manner in which Internet users find products and make purchases based on what they find.

The research team, led by Sylvain Castagnos team from Switzerland’s Ecole Polytechnique Federale de
Lausanne conducted a test on 18 Internet users shopping for perfume and similar products. The study showed that while Internet users still make use of conventional search systems to find information about products and possible alternatives, recommendations have a profound effect on their purchase decision making. In fact, the study found that aside from users clicking and going through recommended products up to 40 percent of the time, users bought 50 percent of the items found on recommendation engines.

Web developers will be interested to know that offering a diverse array of recommended products is just as important as providing recommendations to users based on their interests. The study found that recommendations work best if they fit what a user is looking for, but contain enough diversity that the items are different from each other in more ways than one. This way, users can explore their options and make informed purchase decisions.

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