Recommendation algorithms are remarkably good at pattern matching. They are, almost universally, bad at understanding taste. The difference between those two things is bigger than most platforms would like to admit.<\/p>\n\n\n\n
Pattern matching isn’t the same as understanding why<\/strong><\/p>\n\n\n\n An algorithm can observe that people who bought Item A also frequently bought Item B. What it generally can’t do is understand why<\/em> \u2014 whether it’s because they share a genuine aesthetic sensibility, because they’re functionally related, or because they were both on sale in the same week. Correlation is easy to detect. The underlying reasoning behind a person’s taste is far harder to model, because taste isn’t a fixed set of rules. It’s a shifting, contextual, often contradictory thing that even the person holding it might struggle to fully explain.<\/p>\n\n\n\n Taste changes faster than the data can track<\/strong><\/p>\n\n\n\n Most recommendation systems are built on historical behaviour \u2014 what you’ve bought, browsed, or lingered on before. But taste evolves. The style someone loved eighteen months ago might feel embarrassing to them now. An algorithm trained heavily on past behaviour risks trapping someone in a version of themselves they’ve already moved past, endlessly recommending more of what used to interest them rather than genuinely helping them find where their taste is heading next.<\/p>\n\n\n\n The difference between “similar” and “resonant”<\/strong><\/p>\n\n\n\n Algorithms are excellent at finding items that are objectively similar \u2014 same category, same colour palette, same price bracket. They’re far worse at understanding resonance \u2014 why a particular combination of details makes something feel exactly right to a specific person, in a way that a technically similar item somehow doesn’t. That gap is where a huge amount of genuinely disappointing “personalised” recommendations come from. Technically accurate. Emotionally flat.<\/p>\n\n\n\n Why this actually matters for shopping<\/strong><\/p>\n\n\n\n When taste gets flattened into “people who liked X also liked Y,” the entire experience of discovery narrows. You see more of what’s statistically adjacent to what you already have, and less of what might genuinely delight you precisely because it’s unexpected. The algorithm optimises for confidence, not surprise \u2014 and surprise is often where the best purchases actually come from.<\/p>\n\n\n\n Building AI that respects taste, rather than merely pattern-matching around it, means being honest about the limits of what data alone can capture. It means leaving room for genuine discovery rather than an increasingly narrow loop of “more of the same.” That’s a harder problem to solve than simple correlation. It’s also the more honest one \u2014 and the one actually worth building toward.<\/p>\n\n\n\n #AI #RecommendationSystems #Ecommerce #AICommerce #ConsumerPsychology #ShopWithMore #ArtificialIntelligence<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":" Recommendation algorithms are remarkably good at pattern matching. They are, almost universally, bad at understanding taste. The difference between those two things is bigger than\u2026<\/p>\n","protected":false},"author":1,"featured_media":112,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-111","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-shopwithmore-news"],"_links":{"self":[{"href":"https:\/\/shopwithmore.co.uk\/blog\/wp-json\/wp\/v2\/posts\/111","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/shopwithmore.co.uk\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/shopwithmore.co.uk\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/shopwithmore.co.uk\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/shopwithmore.co.uk\/blog\/wp-json\/wp\/v2\/comments?post=111"}],"version-history":[{"count":1,"href":"https:\/\/shopwithmore.co.uk\/blog\/wp-json\/wp\/v2\/posts\/111\/revisions"}],"predecessor-version":[{"id":113,"href":"https:\/\/shopwithmore.co.uk\/blog\/wp-json\/wp\/v2\/posts\/111\/revisions\/113"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/shopwithmore.co.uk\/blog\/wp-json\/wp\/v2\/media\/112"}],"wp:attachment":[{"href":"https:\/\/shopwithmore.co.uk\/blog\/wp-json\/wp\/v2\/media?parent=111"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/shopwithmore.co.uk\/blog\/wp-json\/wp\/v2\/categories?post=111"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/shopwithmore.co.uk\/blog\/wp-json\/wp\/v2\/tags?post=111"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
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