Amazon Taps AI To Figure Out Why Customers Buy Seemingly Irrelevant Products

Why do customers buy products seemingly irrelevant to their web and voice assistant searches? That's a good question -- and one a team of Amazon researchers sought to answer in a study scheduled to be presented at the upcoming ACM Web Search and Data Mining conference in February. From a report: In it, they say that their analyses -- which looked at purchases and "engagements," the latter defined as interactions like sending search results to cell phones and adding products to shopping carts -- suggests customers are partial to products that are broadly popular or cheaper than products relevant to a given search query. Additionally, they say people are much more likely to buy or engage with irrelevant products in a few categories -- such as toys and digital products -- than in categories like beauty products and groceries. "Product search algorithms, like the ones that help customers place orders through [our Alexa assistant], aim at returning the products that are most relevant to users' queries, where relevance is usually interpreted as 'anything that satisfies the users' need,' wrote Laine Lewin-Eytan, senior manager of applied research in the Alexa Shopping group, in a blog post. "A common way to estimate customers' satisfaction is to rely on the judgment of human annotators. (We annotate a very small fraction of 1% of interactions.)"