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The promise (and pitfalls) of current recommendation engines

NOTE: You can right-click all images to view a larger version. Left-click to go to data source.  Value As arbitrary as they often seem, “35 percent of what consumers purchase on Amazon come from recommendations” —  McKinsey The very small percentage of site visits (7%) that resulted in a click on a recommendation is testament […]

Goodbye Tribes. Hello Clans (Vectors rule over scalar systems)

The Tribes recommendation algorithm as outlined in my filed patent has been superseded by Clans. Clans represents a far more potent method with the enhanced ability to more easily extend to a wider variety of products and to make better predictions of purchase behavior based on multiple products. However, Tribes was limited by its reliability […]

Beyond Genetics: How Saliva Affects Your Unique Way Of Experiencing Wine

Recommendation Insights has previously described the many ways that genetic variations determine any single individual’s wine taste experience: Inherited Taste Chaos Sabotages Recommendations. Now comes this very well-written article that expands that concept: Spit and image: How saliva customizes your wine tasting experience: “Not seeing eye to eye on a wine’s flavor isn’t just about […]

Turning White Wine Into Red: Recommendation Failures & The Alchemy Of Context

“[N]o event or object is ever experienced in perfect, objective isolation. It is instead subject to our past experiences, our current mood, our expectations, and any number of incidental details—an annoying neighbor, a waiter who keeps banging your chair, a beautiful painting in your line of sight. With something like wine, all sorts of societal […]

Wine And Music Are A Lot Alike & So Are The Ways Their Recommendation Systems Fail

Wine and music: please our senses, touch our emotions, beg to be shared, are deeply engrained in how we define ourselves and, can determine how other people judge us. Because of those factors, every recommendation system in use today — including those deployed by Pandora, Spotify, Slacker and other online music sites — fail because of: […]

Machine Learning + Big Data + Tribes = Happier Consumers & Fewer Regulation Hassles

Complaints about the use of personal information for everything from predictive product recommendations to credit ratings and consumer credit card interest rates have provoked lawsuits,  increasing consumer outrage,  and a growing chorus of demands for tighter governmental controls. The greater accuracy of the Tribes algorithm plus its ability to perform in a totally anonymous data […]

Next Glass: A Step In Solving Wine Rating’s Genetic Issues

NOTE: This article uses “wine” to avoid having to type “beer or wine” everywhere. But, unless noted otherwise, a reference to wine refers to both beer and wine. The Next Glass wine and beer selection app is a step toward more accurate wine recommendations, but faces several substantial hurdles on the path to accuracy, scalability […]