{"id":88176,"date":"2022-08-30T09:19:00","date_gmt":"2022-08-30T09:19:00","guid":{"rendered":"https:\/\/barc.com\/de\/?p=88176"},"modified":"2024-10-11T10:48:27","modified_gmt":"2024-10-11T10:48:27","slug":"using-product-and-consumer-data-in-fashion","status":"publish","type":"post","link":"https:\/\/barc.com\/de\/using-product-and-consumer-data-in-fashion\/","title":{"rendered":"How product and consumer data can be used for deriving fashion outfits"},"content":{"rendered":"\n<p>The sales performance of a fashion product is highly dependent on its ability to be combined with other products in the range to create an outfit. Determining complementary products not only helps to better understand and plan the demand, but also provides a huge opportunity for product recommendations.<\/p>\n\n\n\n<p>Therefore,\u00a0<strong>Dr. Ren\u00e9 G\u00f6tz, Senior Data Scientist at adidas<\/strong>, gave a presentation about the exciting topic \u201eHow product and consumer data can be used for deriving fashion outfits.\u201c<\/p>\n\n\n\n<p>Because \u201eoutfit recommandations could be challenging\u201c, Ren\u00e9 and his team analyze different data sources to provide the best outfit combination for their customers.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Watch an excerpt from the presentation here, in which he explains more about the procedure at adidas: &nbsp;<\/strong><\/h4>\n\n\n\n<figure class=\"wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\"><div class=\"wp-block-embed__wrapper\">\n<div class=\"BorlabsCookie _brlbs-cb-youtube\"><div class=\"_brlbs-content-blocker\"> <div class=\"_brlbs-embed _brlbs-video-youtube\"> <img decoding=\"async\" class=\"_brlbs-thumbnail\" src=\"https:\/\/barc.com\/wp-content\/plugins\/borlabs-cookie\/assets\/images\/cb-no-thumbnail.png\" alt=\"YouTube\"> <div class=\"_brlbs-caption\"> <p>Mit dem Laden des Videos akzeptieren Sie die Datenschutzerkl\u00e4rung von YouTube.<br><a href=\"https:\/\/policies.google.com\/privacy\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">Mehr erfahren<\/a><\/p> <p><a class=\"_brlbs-btn _brlbs-icon-play-white\" href=\"#\" data-borlabs-cookie-unblock role=\"button\">Video laden<\/a><\/p> <p><label><input type=\"checkbox\" name=\"unblockAll\" value=\"1\" checked> <small>YouTube immer entsperren<\/small><\/label><\/p> <\/div> <\/div> <\/div><div class=\"borlabs-hide\" data-borlabs-cookie-type=\"content-blocker\" data-borlabs-cookie-id=\"youtube\"><script type=\"text\/template\">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<\/script><\/div><\/div>\n<\/div><\/figure>\n\n\n\n<p>Ren\u00e9\u2019s talk was divided into two parts. In the first minutes he gave an overview on relevant data sources and preprocessing techniques. After that, Ren\u00e9 presented Machine Learning methods, that can make use of the data to produce the final recommendations.<\/p>\n\n\n\n<p>Although the data analysis is often a big secret in a company that is only discussed internally, Ren\u00e9 shared at the DATA festival in Munich a lot of insights and thoughts of his team.<br>This is why his presentation received a lot of encouragement and questions from other data scientists.<\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The sales performance of a fashion product is highly dependent on its ability to be combined with other products in the range to create an outfit. Determining complementary products not only helps to better understand and plan the demand, but also provides a huge opportunity for product recommendations. Therefore,\u00a0Dr. Ren\u00e9 G\u00f6tz, Senior Data Scientist at [&hellip;]<\/p>\n","protected":false},"author":615,"featured_media":47280,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[49],"tags":[],"plus":[],"content_typ":[209],"layoutvorlage":[],"class_list":["post-88176","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-science","content_typ-artikel"],"acf":[],"_links":{"self":[{"href":"https:\/\/barc.com\/de\/wp-json\/wp\/v2\/posts\/88176","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/barc.com\/de\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/barc.com\/de\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/barc.com\/de\/wp-json\/wp\/v2\/users\/615"}],"replies":[{"embeddable":true,"href":"https:\/\/barc.com\/de\/wp-json\/wp\/v2\/comments?post=88176"}],"version-history":[{"count":1,"href":"https:\/\/barc.com\/de\/wp-json\/wp\/v2\/posts\/88176\/revisions"}],"predecessor-version":[{"id":110429,"href":"https:\/\/barc.com\/de\/wp-json\/wp\/v2\/posts\/88176\/revisions\/110429"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/barc.com\/de\/wp-json\/wp\/v2\/media\/47280"}],"wp:attachment":[{"href":"https:\/\/barc.com\/de\/wp-json\/wp\/v2\/media?parent=88176"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/barc.com\/de\/wp-json\/wp\/v2\/categories?post=88176"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/barc.com\/de\/wp-json\/wp\/v2\/tags?post=88176"},{"taxonomy":"plus","embeddable":true,"href":"https:\/\/barc.com\/de\/wp-json\/wp\/v2\/plus?post=88176"},{"taxonomy":"content_typ","embeddable":true,"href":"https:\/\/barc.com\/de\/wp-json\/wp\/v2\/content_typ?post=88176"},{"taxonomy":"layoutvorlage","embeddable":true,"href":"https:\/\/barc.com\/de\/wp-json\/wp\/v2\/layoutvorlage?post=88176"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}