Are recommendations really helpful for B2C services?

Bookstore in Tokyo
Quasi-uniform distribution
Distribution with a peak a region characterized by a quasi-constant probability
“lighthouse during nighttime” by Louis Reed on Unsplash
“person holding blue card” by rawpixel on Unsplash
  • Recommendations must be discoveries and discoveries cannot confirm what a user already knows.
  • Interaction behavioral patterns can be used to understand the hidden (or latent) interest of a user
  • Feedbacks can help in refining the suggestions
  • Exploiting the refined pattern can dramatically increase the probability of conversion for uncommon items
  • Standard (or classical) recommendation strategies can be also employed as a first or a secondary approach
  • The goal of an online store or a B2C service is not to limit the access to the products/items, but to widespread them, hence, a little bit of noise can increase the discovery factor and help the customers to make up their mind (strange but true, because, in a case the user can pick a new item, in the opposite, he can decide to pursue his initial search strategy as the alternative are inadequate)

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Machine Learning, Deep Learning, Artificial Intelligence, and Data Science

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Giuseppe Bonaccorso

Giuseppe Bonaccorso

Machine Learning, Deep Learning, Artificial Intelligence, and Data Science

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