Personalization Dan Saunders

Daniel Saunders

May 5, 2020
Many approaches to ranking a list of products or search results are based on assigning a score to each item and sorting in descending order—in other words, greedy sorting approaches. In e-commerce, predictive models place the product that the customer is most likely to be interested in at the top, followed by the second most likely product, and so forth. But shopkeepers in physical stores know that shelf arrangement is key, and that product appeal is not a fixed quality: it can actually change depending on the context in which a product appears. For example, placing a cheaper item next to an expensive item of the same category could show them both off to their best advantage, highlighting the thriftiness of one and the luxuriousness of the other. When shelves are perfectly arranged, even if some individual products sell less, the store as a whole will make more sales. This phenomenon has been studied in marketing psychology under the heading of context effects, including such phenomena as the attraction, compromise, and similarity effects.
8 Min Read
February 20, 2018
Right now, Wayfair has about 86,000 rugs available for purchase. On the first page of our rug category page, however, we only have room for the top 48. You see even fewer if you don’t happen to scroll or swipe down. When it comes to our customer’s experience, what we choose to place at the top makes a big difference! At present, we don’t explicitly showcase a diverse array of products. On browse pages for categories such as rugs, couches, or coffee tables, we instead combine personalized recommendations with the general popularity of products.
7 Min Read