{"id":16295,"date":"2019-12-16T03:21:23","date_gmt":"2019-12-16T02:21:23","guid":{"rendered":"http:\/\/demolucia.eurolab.es\/?p=16295\/"},"modified":"2026-03-24T13:17:01","modified_gmt":"2026-03-24T12:17:01","slug":"plaza-eboli-reinventing-malls-proximity-marketing","status":"publish","type":"post","link":"https:\/\/flameanalytics.com\/en\/plaza-eboli-reinventing-malls-proximity-marketing\/","title":{"rendered":"Plaza Eboli: Reinventing mall\u00b4s proximity marketing"},"content":{"rendered":"<p><b><\/b>Plaza \u00c9boli\u00b4s Marketing team already launches <a href=\"https:\/\/flameanalytics.com\/en\/omnichannel-marketing\/\"><strong>tailored campaigns<\/strong><\/a> in an agile and simple way to its customers. Thanks to Flame, it has begun to create hypersegmented audiences by demographic, geographic and behavioral data to which it sends personalized communications. Then, it is possible to measure its effectiveness, attribution and impact.<br \/>\n<!--more--><\/p>\n<p>With Flame, Plaza \u00c9boli has begun to conduct better segmented and more accurate marketing campaigns, directing messages (promotions, offers and discounts) to the public that is interested at the right time (when they enter the mall, when they leave, on his birthday, etc.). With this, Plaza \u00c9boli has managed to build <strong>customer loyalty, increase return on investment (ROI) and improve business performance.<\/strong><\/p>\n<p>Likewise, Plaza \u00c9boli has promoted the massive collection of visitor data &#8211;<strong>BIG DATA<\/strong>&#8211; (data\u00a0about\u00a0traffic, passers-by, visits, capture rate, average times of stay, repetition rate or fidelity, etc.) that the mall manages and analyzes optimally thanks to Flame.<\/p>\n<p><img fetchpriority=\"high\" decoding=\"async\" class=\"alignnone size-full wp-image-16292\" src=\"https:\/\/flameanalytics.com\/wp-content\/uploads\/2019\/10\/ccplaza-eboli.png\" alt=\"\" width=\"728\" height=\"350\" \/><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Plaza \u00c9boli\u00b4s Marketing team already launches tailored campaigns in an agile and simple way to its customers. Thanks to Flame, it has begun to create hypersegmented audiences by demographic, geographic and behavioral data to which it sends personalized communications. Then, it is possible to measure its effectiveness, attribution and impact.<\/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":[605,619],"tags":[474],"class_list":["post-16295","post","type-post","status-publish","format-standard","hentry","category-case-studies","category-shopping-malls-case-studies","tag-case-studies"],"acf":[],"_links":{"self":[{"href":"https:\/\/flameanalytics.com\/en\/wp-json\/wp\/v2\/posts\/16295","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=16295"}],"version-history":[{"count":1,"href":"https:\/\/flameanalytics.com\/en\/wp-json\/wp\/v2\/posts\/16295\/revisions"}],"predecessor-version":[{"id":89142,"href":"https:\/\/flameanalytics.com\/en\/wp-json\/wp\/v2\/posts\/16295\/revisions\/89142"}],"wp:attachment":[{"href":"https:\/\/flameanalytics.com\/en\/wp-json\/wp\/v2\/media?parent=16295"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/flameanalytics.com\/en\/wp-json\/wp\/v2\/categories?post=16295"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/flameanalytics.com\/en\/wp-json\/wp\/v2\/tags?post=16295"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}