{"id":5111,"date":"2019-07-12T06:43:46","date_gmt":"2019-07-12T01:13:46","guid":{"rendered":"https:\/\/www.vue.ai\/blog\/?p=5111"},"modified":"2024-01-10T20:39:11","modified_gmt":"2024-01-10T15:09:11","slug":"enriching-catalog-data-with-ai-and-automation","status":"publish","type":"post","link":"https:\/\/www.vue.ai\/blog\/vuetag\/enriching-catalog-data-with-ai-and-automation\/","title":{"rendered":"Catalog Data Enrichment with AI and Automation"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_65 counter-hierarchy ez-toc-counter ez-toc-transparent ez-toc-container-direction\">\n<p class=\"ez-toc-title\">Table of Contents<\/p>\n<label for=\"ez-toc-cssicon-toggle-item-69de81197667c\" class=\"ez-toc-cssicon-toggle-label\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/label><input type=\"checkbox\"  id=\"ez-toc-cssicon-toggle-item-69de81197667c\" checked aria-label=\"Toggle\" \/><nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.vue.ai\/blog\/vuetag\/enriching-catalog-data-with-ai-and-automation\/#going-traditional-to-digital\" title=\"Going Traditional To Digital\">Going Traditional To Digital<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.vue.ai\/blog\/vuetag\/enriching-catalog-data-with-ai-and-automation\/#data-discrepancies\" title=\"Data Discrepancies\">Data Discrepancies<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.vue.ai\/blog\/vuetag\/enriching-catalog-data-with-ai-and-automation\/#-studies-show-that-poor-data-is-costing-fashion-e-commerce-business-6-of-their-annual-revenue-thats-an-expected-459-billion-chunk-by-the-year-2022\" title=\"|| Studies show that poor data is costing fashion e-commerce business 6% of their annual revenue. That\u2019s an expected $45.9 Billion chunk by the year 2022.\">|| Studies show that poor data is costing fashion e-commerce business 6% of their annual revenue. That\u2019s an expected $45.9 Billion chunk by the year 2022.<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.vue.ai\/blog\/vuetag\/enriching-catalog-data-with-ai-and-automation\/#catalog-data-enrichment\" title=\"Catalog Data Enrichment\">Catalog Data Enrichment<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.vue.ai\/blog\/vuetag\/enriching-catalog-data-with-ai-and-automation\/#rich-product-data-generation\" title=\"Rich Product Data Generation\">Rich Product Data Generation<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.vue.ai\/blog\/vuetag\/enriching-catalog-data-with-ai-and-automation\/#ai-as-a-solution\" title=\"AI As A Solution\">AI As A Solution<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.vue.ai\/blog\/vuetag\/enriching-catalog-data-with-ai-and-automation\/#the-vuetag-solution\" title=\"The VueTag Solution\">The VueTag Solution<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.vue.ai\/blog\/vuetag\/enriching-catalog-data-with-ai-and-automation\/#read-more-about-automated-catalog-management-solution\" title=\"Read More About Automated Catalog Management Solution\">Read More About Automated Catalog Management Solution<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<span class=\"rt-reading-time\" style=\"display: block;\"><span class=\"rt-label rt-prefix\">Reading Time: <\/span> <span class=\"rt-time\">4<\/span> <span class=\"rt-label rt-postfix\">minutes<\/span><\/span><p><span style=\"font-weight: 400;\">At a glance, building and maintaining a product catalog can seem like a tactical task. But there is more to look into this matter than what meets the eye.\u00a0<\/span><span style=\"font-weight: 400;\">Whether you are a manufacturer, retailer, supplier, or distributor, quality of catalog data makes all the difference in sale. From automating digital merchandising to counterfeit product identification, Today, computer vision\u2019s role has expanded into every part of retail i.e, right from managing inventory to in-store aids to making smarter decisions. One of the areas in the retail industry where automation comes into play, is Catalog Data Enrichment which allows retailers to generate and handle data effectively.\u00a0<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"going-traditional-to-digital\"><\/span><b>Going Traditional To Digital<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Moving data from a traditional brick-and-mortar store set up to an online store can seem like a daunting task. From designing the eCommerce website and persona, to ensuring all your products are tagged and displayed accurately, to preparing content for marketing strategies, moving to the eCommerce world is a complex process, but a very important one, especially in the digital age. Retailers often struggle with inconsistent data across products owing to different sources like third party and vendors. Fixing data quality becomes something of paramount importance since it affects the data across the retail system itself.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Today, reviewing large catalogs manually, is a time consuming process. Retailers must switch to faster tagging methods to ensure their products GTM faster thereby keeping up with the industry. Automating this tagging process yields rich and robust tags.<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"data-discrepancies\"><\/span><b>Data Discrepancies<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Data discrepancies exist throughout the retail process. Identifying and tackling them at the very beginning, ensures that the data across your system is consistent, clean and rich. Having poor quality images, duplicate images of the same product, multiple image types or images not conforming to the brand guidelines, maintaining one excel sheet for all the products, mixing up the SKU numbers are all common problems that retailers face due to inconsistent data.\u00a0<\/span><\/p>\n<blockquote>\n<h3><span class=\"ez-toc-section\" id=\"-studies-show-that-poor-data-is-costing-fashion-e-commerce-business-6-of-their-annual-revenue-thats-an-expected-459-billion-chunk-by-the-year-2022\"><\/span><em>|| Studies show that poor data is costing fashion e-commerce business 6% of their annual revenue. That\u2019s an expected $45.9 Billion chunk by the year 2022.<\/em><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<\/blockquote>\n<p><span style=\"font-weight: 400;\">Manually labelling is time consuming, erroneous and lacks uniformity. Studies show that it takes more than 30 hours a week to tag just 200-300 products.\u00a0<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"catalog-data-enrichment\"><\/span><strong>Catalog Data Enrichment<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Catalog Data Enrichment using AI and automation can reap many benefits. Aside from getting clean, rich and consistent tags, automating the process also yields deeper insight into catalog data. With minimal manual intervention, clean, consistent tags and SEO-ready tags increase catalog quality and visibility, improving product discovery. Automated product tagging increases your business\u2019s operation efficiency and ensures a seamless product discovery experience for the shoppers. Having accurate and relevant product content increases engagement and reduces bounce rate of the website.\u00a0<\/span><\/p>\n<figure id=\"attachment_5119\" aria-describedby=\"caption-attachment-5119\" style=\"width: 750px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-5119\" src=\"https:\/\/www.vue.ai\/blog\/wp-content\/uploads\/2019\/07\/Screenshot-2019-07-10-at-1.20.55-PM-300x259.png\" alt=\"\" width=\"750\" height=\"647\" srcset=\"https:\/\/www.vue.ai\/blog\/wp-content\/uploads\/2019\/07\/Screenshot-2019-07-10-at-1.20.55-PM-300x259.png 300w, https:\/\/www.vue.ai\/blog\/wp-content\/uploads\/2019\/07\/Screenshot-2019-07-10-at-1.20.55-PM.png 495w\" sizes=\"(max-width: 750px) 100vw, 750px\" \/><figcaption id=\"caption-attachment-5119\" class=\"wp-caption-text\">Source: Webinar, Vue.ai\u00ae<\/figcaption><\/figure>\n<h2><span class=\"ez-toc-section\" id=\"rich-product-data-generation\"><\/span><b>Rich Product Data Generation<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Rich product data sells. Having optimised for search, it scores well for readability, and has robust metadata. These metadata tags result in highly specific, SEO friendly keywords. It helps the retailer to curate ensembles and highlight the right merchandise for the right customer by understanding their personal shopping preferences. Using these fashion specific keywords for SEO and Adword tags helps increase catalog invisibility across marketing and sales channels. Product discovery is also maximized through image and search text on site. The visual tags are augmented with textual tags to allow for more precision and relevance in search results, leading to an enhanced browsing experience for the customers. It also provides a deeper insight on trends in sales data for better inventory and forecasting decisions.<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"ai-as-a-solution\"><\/span><b>AI As A Solution<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Using computer vision, visual AI and NLP systems produces clean and consistent data. Catalog assessment is the first step of the process, which identifies missing or incorrect metadata. Following which, Catalog audit, the second step, identifies the source of the product image, i.e., if it is a catalog garment, a model image or a social media professional\u2019s image. This helps the retailer understand their inventory structure and enables them to make better decisions. Automation engines verify if the product images and its associated metadata are aligned. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">The Image Search and Image Recognition engines identify duplicates within the catalog or across different catalogs from multiple sellers which is crucial for an accurate assessment of the inventory. Effective <a href=\"https:\/\/www.vue.ai\/industries\/ai-in-ecommerce\/\">catalog management<\/a> means that retailers can keep track of SKUs and as a result plan inventory better. AI &#8211; enabled tagging, the third step, extracts visual attributes beyond just color or pattern, and detects category, pattern, neckline and even dress length. The NLP systems generate non-visual tags that create apt product titles and descriptions.<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"the-vuetag-solution\"><\/span><b>The VueTag Solution<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><b>VueTag<\/b><span style=\"font-weight: 400;\"> is an AI-powered image recognition solution that automatically tags products by extracting accurate, detailed product attributes from images at a fraction of time and cost. The AI tagging engines extracts visual attributes from the products to create tags while the NLP engines generate the title and descriptions. This makes the QA process easier and efficient. The tagged data can then be exported as a CSV or XLS file, or integrated via API or into any PIM\/CMS systems.<\/span><\/p>\n<figure id=\"attachment_5114\" aria-describedby=\"caption-attachment-5114\" style=\"width: 750px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/www.vue.ai\/solutions\/automated-product-tagging\/\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-5114\" src=\"https:\/\/www.vue.ai\/blog\/wp-content\/uploads\/2019\/07\/Screenshot-2019-07-10-at-12.34.37-PM-300x168.png\" alt=\"\" width=\"750\" height=\"420\" srcset=\"https:\/\/www.vue.ai\/blog\/wp-content\/uploads\/2019\/07\/Screenshot-2019-07-10-at-12.34.37-PM-300x168.png 300w, https:\/\/www.vue.ai\/blog\/wp-content\/uploads\/2019\/07\/Screenshot-2019-07-10-at-12.34.37-PM-768x430.png 768w, https:\/\/www.vue.ai\/blog\/wp-content\/uploads\/2019\/07\/Screenshot-2019-07-10-at-12.34.37-PM.png 1010w\" sizes=\"(max-width: 750px) 100vw, 750px\" \/><\/a><figcaption id=\"caption-attachment-5114\" class=\"wp-caption-text\">Source: Vue.ai\u00ae<\/figcaption><\/figure>\n<p><span style=\"font-weight: 400;\">Manually tagging 10,000 products with approximately 8 tags per product will cost you a lot of time and money (approx. 1 month with up to 3 people working on it). It will also result in tags that are inconsistent, and erroneous. Switching to VueTag, an <a href=\"https:\/\/www.vue.ai\/solutions\/automated-product-tagging\/\">automated tagging solutio<\/a>n tags products in real time, saving you 90% of human and operational costs. It also yields consistent and highly accurate tags, thereby improving your overall catalog quality. Features like Bulk Edit help you review large quantities at once, saving you even more time and effort!\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Learn more about Product Catalog Data Enrichment data with AI and Automation from our webinar with Forrester&gt;&gt;<\/span><\/p>\n<h3><span class=\"ez-toc-section\" id=\"read-more-about-automated-catalog-management-solution\"><\/span><b>Read More About<\/b><a href=\"https:\/\/www.vue.ai\/industries\/ai-in-ecommerce\/\"> <b>Automated Catalog Management<\/b><\/a><b> Solution<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n","protected":false},"excerpt":{"rendered":"<p><span class=\"rt-reading-time\" style=\"display: block;\"><span class=\"rt-label rt-prefix\">Reading Time: <\/span> <span class=\"rt-time\">4<\/span> <span class=\"rt-label rt-postfix\">minutes<\/span><\/span> At a glance, building and maintaining a product catalog can seem like a tactical task. But there is more to look into this matter than what meets the eye.\u00a0Whether you are a manufacturer, retailer, supplier, or distributor, quality of catalog data makes all the difference in sale. From automating digital merchandising to counterfeit product identification,  &#8230;<\/p>\n","protected":false},"author":23,"featured_media":5577,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[145],"tags":[17,170,7,302,303],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v22.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Catalog Data Enrichment with AI and Automation | Vue.ai<\/title>\n<meta name=\"description\" content=\"Learn more about Product Catalog Data Enrichment data with AI and Automation from Vue.ai&#039;s catalog management solutions.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.vue.ai\/blog\/vuetag\/enriching-catalog-data-with-ai-and-automation\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" 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