{"id":16354,"date":"2020-02-24T02:32:44","date_gmt":"2020-02-24T01:32:44","guid":{"rendered":"http:\/\/demolucia.eurolab.es\/?p=16354\/"},"modified":"2026-03-24T13:17:01","modified_gmt":"2026-03-24T12:17:01","slug":"pompeii-use-big-data-retail-sector","status":"publish","type":"post","link":"https:\/\/flameanalytics.com\/en\/pompeii-use-big-data-retail-sector\/","title":{"rendered":"Pompeii: Use of Big Data in the retail sector"},"content":{"rendered":"<p>Pompeii evaluated Flame&#8217;s value proposition because he wanted to<strong> know and better understand their clients\u00b4behavior<\/strong>: how they interact at the points of sale and how they behave. Pompeii\u00a0wanted to<strong> anticipate their customers\u00b4demands<\/strong> in order to serve them better, boost sales and generate loyalty, increasing the engagement towards their brand.<br \/>\n<!--more--><\/p>\n<p>Pompeii was aware that, in a markedly digital environment like the current one, in which the consumption habits are perfectly monitored, correctly managing the Big Data generated by their points of sale could represent <strong>the key to the\u00a0business\u00b4success<\/strong>.<\/p>\n<p>Pompeii found the solution in Flame analytics. Now they have access to a huge volume of information on <strong>their customers\u00b4behavior<\/strong> (number of passers-by, visits, length of stay, loyalty rate, conversion rate, etc.) but, The most important thing is that they are analyzing and learning to take advantage of this data and, in this way, to apply it successfully to their promotion and sales strategies.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Pompeii evaluated Flame&#8217;s value proposition because he wanted to know and better understand their clients\u00b4behavior: how they interact at the points of sale and how they behave. Pompeii\u00a0wanted to anticipate their customers\u00b4demands in order to serve them better, boost sales and generate loyalty, increasing the engagement towards their brand.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[605,618],"tags":[474],"class_list":["post-16354","post","type-post","status-publish","format-standard","hentry","category-case-studies","category-retail-case-studies","tag-case-studies"],"acf":[],"_links":{"self":[{"href":"https:\/\/flameanalytics.com\/en\/wp-json\/wp\/v2\/posts\/16354","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/flameanalytics.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/flameanalytics.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/flameanalytics.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/flameanalytics.com\/en\/wp-json\/wp\/v2\/comments?post=16354"}],"version-history":[{"count":2,"href":"https:\/\/flameanalytics.com\/en\/wp-json\/wp\/v2\/posts\/16354\/revisions"}],"predecessor-version":[{"id":89143,"href":"https:\/\/flameanalytics.com\/en\/wp-json\/wp\/v2\/posts\/16354\/revisions\/89143"}],"wp:attachment":[{"href":"https:\/\/flameanalytics.com\/en\/wp-json\/wp\/v2\/media?parent=16354"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/flameanalytics.com\/en\/wp-json\/wp\/v2\/categories?post=16354"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/flameanalytics.com\/en\/wp-json\/wp\/v2\/tags?post=16354"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}