{"id":6944,"date":"2025-09-18T07:02:24","date_gmt":"2025-09-18T07:02:24","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2025\/09\/18\/analysis-of-sales-shift-in-retail-with-causal-impact-a-case-study-at-carrefour\/"},"modified":"2025-09-18T07:02:24","modified_gmt":"2025-09-18T07:02:24","slug":"analysis-of-sales-shift-in-retail-with-causal-impact-a-case-study-at-carrefour","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2025\/09\/18\/analysis-of-sales-shift-in-retail-with-causal-impact-a-case-study-at-carrefour\/","title":{"rendered":"Analysis of Sales Shift in Retail with Causal Impact: A Case Study at Carrefour"},"content":{"rendered":"<p>    Analysis of Sales Shift in Retail with Causal Impact: A Case Study at Carrefour<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n    <!-- no image --><br \/>\n \t<BR><br \/>\n<BR><\/BR><\/p>\n<div>\n<p>Applying causal inference to measure the effect of product unavailability on retail sales at Carrefour<\/p>\n<p>The post <a href=\"https:\/\/towardsdatascience.com\/analysis-of-sales-shift-in-retail-with-causal-impact-a-case-study-at-carrefour\/\">Analysis of Sales Shift in Retail with Causal Impact: A Case Study at Carrefour<\/a> appeared first on <a href=\"https:\/\/towardsdatascience.com\/\">Towards Data Science<\/a>.<\/p>\n<\/div>\n<p> \t<BR><br \/>\n <BR><\/BR><br \/>\n    Thanh Li\u00eam NGUYEN<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/towardsdatascience.com\/analysis-of-sales-shift-in-retail-with-causal-impact-a-case-study-at-carrefour\/\">Go to original source<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Analysis of Sales Shift in Retail with Causal Impact: A Case Study at Carrefour Applying causal inference to measure the effect of product unavailability on retail sales at Carrefour The post Analysis of Sales Shift in Retail with Causal Impact: A Case Study at Carrefour appeared first on Towards Data Science. Thanh Li\u00eam NGUYEN Go [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[62,2363,210,83,67,70,2338],"tags":[331,3820,3819],"class_list":["post-6944","post","type-post","status-publish","format-standard","hentry","category-aimldsaimlds","category-bayesian-inference","category-causal-inference","category-data-science","category-deep-dives","category-machine-learning","category-time-series","tag-causal","tag-retail","tag-sales"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/6944"}],"collection":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/comments?post=6944"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/6944\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=6944"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=6944"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=6944"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}