{"id":1062,"date":"2019-09-12T15:47:09","date_gmt":"2019-09-12T15:47:09","guid":{"rendered":"https:\/\/desis.osu.edu\/seniorthesis\/?p=1062"},"modified":"2019-09-12T15:47:11","modified_gmt":"2019-09-12T15:47:11","slug":"stitch-fixs-ceo-on-selling-personal-style-to-the-mass-market","status":"publish","type":"post","link":"https:\/\/desis.osu.edu\/seniorthesis\/index.php\/2019\/09\/12\/stitch-fixs-ceo-on-selling-personal-style-to-the-mass-market\/","title":{"rendered":"Stitch Fix&#8217;s CEO on Selling Personal Style to the Mass Market"},"content":{"rendered":"\n<p>Original Article:<br>Stitch Fix\u2019s CEO on Selling Personal Style to the Mass Market <br>by Katrina Lake<br>https:\/\/hbr.org\/2018\/05\/stitch-fixs-ceo-on-selling-personal-style-to-the-mass-market<\/p>\n\n\n\n<p>\u201cAt Stitch Fix our business model is simple: We send you clothing\nand accessories we think you\u2019ll like; you keep the items you want and send the\nothers back. We leverage data science to deliver personalization at scale,\ntranscending traditional brick-and-mortar and e-commerce retail experiences.\nCustomers enjoy having an expert stylist do the shopping for them and\nappreciate the convenience and simplicity of the service\u2026 Of course, making\nsomething seem simple and convenient to consumers while working profitably and\nat scale is complex. It\u2019s even more complex in the fashion retail industry,\nwhich is crowded, fickle, and rapidly changing. Other apparel retailers attempt\nto differentiate themselves through the lowest price or the fastest shipping;\nwe differentiate ourselves through personalization. The part of me that loves\ndata knew it could be used to create a better experience with apparel. After\nall, fit and taste are just a bunch of attributes: waist, inseam, material,\ncolor, weight, durability, and pattern. It\u2019s all just data. If you collect\nenough, you\u2019ll get a pretty good picture of what clothes people want\u2026 But the\npart of me that loves clothes recognized the human element in shopping\u2014the\nfeeling of finding something you weren\u2019t expecting to and delighting in the\nfact that it fits you and your budget. I saw an opportunity to combine those\ntwo elements\u2014data and human experience\u2014to create a new model for buying clothes\u2026\nHybrid Designs, our in-house clothing brand, came to life one rainy afternoon\nwhen a couple of data scientists were thinking about how to fill product gaps\nin the marketplace. For example, many female clients in their mid-40s were\nasking for capped-sleeve blouses, but that style was missing from our current\ninventory set. Fast-forward a year, and we have 29 apparel items for women and\nplus sizes that were designed by computer and meet some specific, previously\nunfilled needs our clients have\u2026 The analytical part of me loves our\nalgorithmic approach. But shopping is inherently a personal and human activity.\nThat\u2019s why we insist on combining data with a human stylist who can alter or\noverride the product assortment our styling algorithm has delivered. Our\nstylists come from a range of design and retail backgrounds, but they all have\nan appreciation for the data and feel love and empathy for our clients. Humans\nare much better than machines at some things\u2014and they are likely to stay that\nway for a long time.\u201d<\/p>\n\n\n\n<p>This article is a great overview of how technology and data\nscience can set businesses apart and drive success.\n\n\n\n\n\nsdsemih<\/p>\n\n\n\n<p><br><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Original Article:Stitch Fix\u2019s CEO on Selling Personal Style to the Mass Market by Katrina Lakehttps:\/\/hbr.org\/2018\/05\/stitch-fixs-ceo-on-selling-personal-style-to-the-mass-market \u201cAt Stitch Fix our business model is simple: We send you clothing and accessories we think you\u2019ll like; you keep the items you want and send the others back. We leverage data science to deliver personalization at scale, transcending traditional [&hellip;]<\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[31],"tags":[161,159],"class_list":{"0":"post-1062","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-business-featured","7":"tag-datascience","8":"tag-personalstyle"},"_links":{"self":[{"href":"https:\/\/desis.osu.edu\/seniorthesis\/index.php\/wp-json\/wp\/v2\/posts\/1062","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/desis.osu.edu\/seniorthesis\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/desis.osu.edu\/seniorthesis\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/desis.osu.edu\/seniorthesis\/index.php\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/desis.osu.edu\/seniorthesis\/index.php\/wp-json\/wp\/v2\/comments?post=1062"}],"version-history":[{"count":1,"href":"https:\/\/desis.osu.edu\/seniorthesis\/index.php\/wp-json\/wp\/v2\/posts\/1062\/revisions"}],"predecessor-version":[{"id":1068,"href":"https:\/\/desis.osu.edu\/seniorthesis\/index.php\/wp-json\/wp\/v2\/posts\/1062\/revisions\/1068"}],"wp:attachment":[{"href":"https:\/\/desis.osu.edu\/seniorthesis\/index.php\/wp-json\/wp\/v2\/media?parent=1062"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/desis.osu.edu\/seniorthesis\/index.php\/wp-json\/wp\/v2\/categories?post=1062"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/desis.osu.edu\/seniorthesis\/index.php\/wp-json\/wp\/v2\/tags?post=1062"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}