Nowadays, search engines are also eager to infer the intentions of those who search.įor example, in "Google Suggest," which Google provides as a trial, from the moment users start entering keywords in the search window, "Is this the keyword you want to search for?" > And suggest possible keywords and refined keywords. This is quite smart because my mobile phone is learning my daily activities. Simply enter one character and he will recommend (recommend) that "I don't want to enter this word next time." In a familiar example, the character conversion function of mobile phones is the same. In the United States, even on major news and information sites, "people who are watching this news are also reading this news," or "people who are reading this blog post are also reading that blog post. The trend of inferring user intentions is not limited to EC sites. We infer customers' intentions and recommend products that are suitable for each customer. The sales have stopped increasing just by arranging a lot of products, so we are trying to put the best selling products in the most visible places.Īlso, the recommendation engine is actively introduced in place of the clever staff. However, recently, online shopping “EC (e-commerce) sites” are gradually approaching convenience stores. By thoroughly studying the behavior patterns of customers, the height of product shelves and the display location of products are determined. Convenience store shelving is famous for being extremely precise.Ĭarefully selecting hot-selling products based on the data collected by the "POS system".
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