{"id":7241,"date":"2014-03-26T01:15:21","date_gmt":"2014-03-25T19:45:21","guid":{"rendered":"http:\/\/blog.fusioncharts.com\/?p=7241"},"modified":"2026-01-20T14:40:49","modified_gmt":"2026-01-20T09:10:49","slug":"how-walmart-uses-data-visualization-to-convert-real-time-social-conversations-into-inventory","status":"publish","type":"post","link":"https:\/\/www.fusioncharts.com\/blog\/how-walmart-uses-data-visualization-to-convert-real-time-social-conversations-into-inventory\/","title":{"rendered":"Walmart: Social Buzz to Inventory with Data Visualization 2013"},"content":{"rendered":"More than 245 million customers visit their 10,900 stores and ten websites worldwide each week. In the fiscal year 2013, Walmart had sales of approximately $466 billion and employed 2.2 million associates. It is undeniably a name to be reckoned with in the retail sector.\r\n\r\n<img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-7510\" title=\"Walmart\" src=\"https:\/\/www.fusioncharts.com\/blog\/wp-content\/uploads\/gallery\/blog\/2014\/03\/Wal-mart-Taking-Hits-and-Plunging.jpg\" alt=\"Walmart\" width=\"819\" height=\"505\" srcset=\"\/blog\/wp-content\/uploads\/2014\/03\/Wal-mart-Taking-Hits-and-Plunging.jpg 1024w, \/blog\/wp-content\/uploads\/2014\/03\/Wal-mart-Taking-Hits-and-Plunging-150x92.jpg 150w\" sizes=\"auto, (max-width: 819px) 100vw, 819px\" \/>\r\n\r\nData-driven decisions are more of the norm than the exception at Walmart. A large portion of their data efforts are based on social data\u2014tweets, blogs, pins, comments, shares, and so on. The team at <a href=\"https:\/\/www.walmartlabs.com\/\" target=\"_blank\" rel=\"noopener noreferrer\">WalmartLabs<\/a>.is in charge of mining all of that data to generate retail-related insights.\r\n\r\nThis is the first post in our <em><b><a href=\"https:\/\/www.fusioncharts.com\/blog\/\" target=\"_blank\" rel=\"noopener noreferrer\">Data Visualization Spotlight<\/a><\/b><\/em> series, in which we show how various organizations use data visualization and analytics to solve day-to-day problems.\u00a0You can replicate this tutorial using a <a href=\"https:\/\/www.fusioncharts.com\/charts\/realtime-charts\/line-chart\">Data Visualization Tool<\/a> and see how the data converts to real-time social conversations into inventory.\r\n\r\n<!--more-->\r\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_71 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\"><p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<\/div><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.fusioncharts.com\/blog\/how-walmart-uses-data-visualization-to-convert-real-time-social-conversations-into-inventory\/#Capturing_the_Social_Retail_Pulse_Through_Data_Visualization\" title=\"Capturing the Social Retail Pulse Through Data Visualization\">Capturing the Social Retail Pulse Through Data Visualization<\/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.fusioncharts.com\/blog\/how-walmart-uses-data-visualization-to-convert-real-time-social-conversations-into-inventory\/#_%E2%80%9COMG_dis_is_sooo_coool_i_luv_ma_new_fone%E2%80%9D%E2%80%94_Challenges_and_the_way_forward\" title=\"\u00a0\u201cOMG!!! dis is sooo coool!\u00a0 i luv ma new fone.\u201d\u2014 Challenges and the way forward\">\u00a0\u201cOMG!!! dis is sooo coool!\u00a0 i luv ma new fone.\u201d\u2014 Challenges and the way forward<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.fusioncharts.com\/blog\/how-walmart-uses-data-visualization-to-convert-real-time-social-conversations-into-inventory\/#Final_Thoughts\" title=\"Final Thoughts\">Final Thoughts<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.fusioncharts.com\/blog\/how-walmart-uses-data-visualization-to-convert-real-time-social-conversations-into-inventory\/#Reference\" title=\"Reference\">Reference<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.fusioncharts.com\/blog\/how-walmart-uses-data-visualization-to-convert-real-time-social-conversations-into-inventory\/#What_to_Read_Next\" title=\"What to Read Next\">What to Read Next<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"Capturing_the_Social_Retail_Pulse_Through_Data_Visualization\"><\/span><b>Capturing the Social Retail Pulse Through Data Visualization<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\r\nAs Arun Prasath, Principal Engineer, WalmartLabs, points out in <a href=\"https:\/\/www.walmartlabs.com\/2013\/01\/11\/the-walmartlabs-social-media-analytics-project\/\" target=\"_blank\" rel=\"noopener noreferrer\">an article,<\/a><em> \u201cSocial Media Analytics is all about mining retail-related insights from social channels, a perilous and personally exciting task to us. When our team spent the 22nd of November feverishly following the social retail pulse on Black Friday, we knew the world wasn\u2019t preparing for an apocalypse.\u201d<\/em>\r\n\r\n<img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-large wp-image-7508\" title=\"Walmart blackfriday trend\" src=\"https:\/\/www.fusioncharts.com\/blog\/wp-content\/uploads\/gallery\/blog\/2014\/03\/Walmart-blackfriday-trend-1024x299.png\" alt=\"Walmart blackfriday trend\" width=\"1024\" height=\"299\" \/><em>Fig: By using real-time data visualization, the team observed a clear upswing in Walmart-related social buzz on 22<sup>nd<\/sup> November 2012, which gently reminded them of the promise that lay hidden deep within the treasure of the social data goldmine.<\/em> Image Source: @WalmartLabs blog\r\n\r\nIn an age where information-sharing is easy, thanks to social media, such social buzz typically precedes all-important product launches. People are frequently expressing their views about the latest smartphone or the coolest video game hitting the shelf. WalmartLabs taps this social buzz and helps buyers plan their inventory and assortment.\r\n\r\nArun Prasath cites the following example. A few days ahead of its launch, Sony\u2019s Android phone Xperia Z showed a similar spike in social activity.\r\n\r\n<img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-7511\" title=\"Walmart Xperia Z trend\" src=\"https:\/\/www.fusioncharts.com\/blog\/wp-content\/uploads\/gallery\/blog\/2014\/03\/Xperia-Z-trend.png\" alt=\"Walmart Xperia Z trend\" width=\"917\" height=\"649\" srcset=\"\/blog\/wp-content\/uploads\/2014\/03\/Xperia-Z-trend.png 917w, \/blog\/wp-content\/uploads\/2014\/03\/Xperia-Z-trend-150x106.png 150w\" sizes=\"auto, (max-width: 917px) 100vw, 917px\" \/><em>Fig: Such insights gathered through data visualization and social media analytics help its buyers make smarter decisions ahead of time. Image Source: @WalmartLabs blog<\/em>\r\n\r\nWalmartLabs uses such spikes in social network chatter to predict demand for out-of-the-ordinary products, too. In 2011, the team correctly anticipated heightened customer interest in cake-pop makers. They did so based on social media conversations on Facebook and Twitter. A few months later, it noticed a growing interest in electric juicers. This interest was linked to the popularity of the juice-crazy documentary <em>Fat, Sick, and Nearly Dead.<\/em> The team sends these data to Walmart&#8217;s buyers, who then use it to make their purchasing decisions.\r\n\r\n<img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-large wp-image-7509\" title=\"Walmart Social Media Analytics dashboard\" src=\"https:\/\/www.fusioncharts.com\/blog\/wp-content\/uploads\/gallery\/blog\/2014\/03\/walmart-social-1024x764.jpg\" alt=\"walmart social media analytics dashboard\" width=\"1024\" height=\"764\" \/><em>Fig: The Social Media Analytics dashboard for buyers gives them better insight into consumers\u2019 thoughts on products. Image Source: Gigaom.com<\/em>\r\n\r\nWalmart\u2019s buyers also get a sense of what they should stock online and in stores by checking out pins on Pinterest. Top pins feed into a social-media analytics dashboard for buyers. So do the reports from Twitter that engineers have created by visualizing and analyzing Twitter feeds. Buyers can see when the number of tweets on, say, gel nail polish peaked and see the most popular colors in which locations.\r\n<h2><span class=\"ez-toc-section\" id=\"_%E2%80%9COMG_dis_is_sooo_coool_i_luv_ma_new_fone%E2%80%9D%E2%80%94_Challenges_and_the_way_forward\"><\/span><b><em>\u00a0\u201cOMG!!! dis is sooo coool!\u00a0 i luv ma new fone.\u201d<\/em><\/b><b><em>\u2014 <\/em>Challenges and the way forward<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\r\nThe language used in social forums is heavily unstructured, informal, and often ungrammatical. Mining petabytes of such social data to filter out relevant data points and then map them to meaningful retail products is difficult. Popular text analytics and natural language processing techniques based on standard language models do not suffice.\r\n\r\nOne of the several techniques WalmartLabs adopts to overcome this challenge is looking for several hand-verified n-grams [<a href=\"https:\/\/en.wikipedia.org\/wiki\/N-gram\" target=\"_blank\" rel=\"noopener noreferrer\">Related read: n-gram<\/a>] around brands in a significant time window.\r\n\r\nAs Prasath points out, there are several such techniques in the offing. \u00a0\u201c<em>It is only after conquering all of these multifold challenges that meaningful recommendation can be made\u2026.Our social media analytics project operates on top of a searchable index of 60 billion social documents and helps merchants at Walmart monitor sentiments and popular interests in real-time, or inquire into trends in the past. One can also see geographical variations of social sentiments and buzz levels. There are also tools that marry search trends on walmart.com, sales trends in our brick-and-mortar stores, and social buzz all in one place, to help make correlations. Together, these tools provide powerful social insights.\u201d<\/em>\r\n<h2><span class=\"ez-toc-section\" id=\"Final_Thoughts\"><\/span><b>Final Thoughts<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\r\nPeople are constantly talking about products on social media. A retailer must transform this humongous amount of social data into meaningful information and make it available in a form that their merchandisers can understand and use for assortment and inventory planning.\r\n\r\nThe secret to successful retailing is the delivery of the right product at the right place and time. And social media analytics coupled with data visualization can help the merchandiser achieve the same with remarkable results.\r\n\r\n<em>In our next post\u00a0<\/em>in<em>\u00a0the Data Visualization Spotlight series, read <a href=\"https:\/\/fusioncharts.com\/blog\/how-netflix-plans-to-improve-its-operational-visibility-with-real-time-data-visualization\/\" target=\"_blank\" rel=\"noopener noreferrer\">how Netflix plans to improve its operational visibility with dynamic data visualization<\/a>.<\/em>\r\n<h3><span class=\"ez-toc-section\" id=\"Reference\"><\/span><b>Reference<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\r\n<ul>\r\n \t<li><a title=\"The @WalmartLabs Social Media Analytics project\" href=\"https:\/\/www.walmartlabs.com\/2013\/01\/11\/the-walmartlabs-social-media-analytics-project\/\" target=\"_blank\" rel=\"noopener noreferrer\">The @WalmartLabs Social Media Analytics project<\/a><\/li>\r\n \t<li>FastCompany<\/li>\r\n \t<li><a href=\"https:\/\/gigaom.com\/2013\/03\/27\/wal-mart-is-arming-itself-for-fierce-retail-battles-with-better-search-social-streams-and-more\/\" target=\"_blank\" rel=\"noopener noreferrer\">GigaOM<\/a><\/li>\r\n<\/ul>\r\n<h3><span class=\"ez-toc-section\" id=\"What_to_Read_Next\"><\/span><b>What to Read Next<\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\r\nCheck out our 5-part series on <a href=\"https:\/\/www.fusioncharts.com\/blog\/behind-the-scenes-of-cakehr-dashboard-in-conversation-with-kaspars-upmanis\/\" target=\"_blank\" rel=\"noopener noreferrer\">Behind scenes dashboard design<\/a>, where we speak to Product Managers, Developers, and Designers of software products with kick-ass information dashboards to help you get an insider\u2019s view into their making.","protected":false},"excerpt":{"rendered":"<p>More than 245 million customers visit their 10,900 stores and ten websites worldwide each week. In the fiscal year 2013, Walmart had sales of approximately $466 billion and employed 2.2 million associates. It is undeniably a name to be reckoned with in the retail sector. Data-driven decisions are more of the norm than the exception [&hellip;]<\/p>\n","protected":false},"author":19,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[19],"tags":[105,481,381],"coauthors":[674],"class_list":["post-7241","post","type-post","status-publish","format-standard","hentry","category-showcase","tag-data-visualization","tag-social-media-analytics","tag-walmart"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Walmart: Social Buzz to Inventory with Data Visualization 2013<\/title>\n<meta name=\"description\" content=\"Learn from Walmart\u2019s data success. 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