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<oembed><version>1.0</version><provider_name>Team Acua</provider_name><provider_url>https://acua.qcri.org/blog</provider_url><author_name>Kaushik</author_name><author_url>https://acua.qcri.org/blog/author/kaushik/</author_url><title>Customer Data Mining for Lifestyle Segmentation - Team Acua</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="4wPe0JeRia"&gt;&lt;a href="https://acua.qcri.org/blog/customer-data-mining-for-lifestyle-segmentation/"&gt;Customer Data Mining for Lifestyle Segmentation&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://acua.qcri.org/blog/customer-data-mining-for-lifestyle-segmentation/embed/#?secret=4wPe0JeRia" width="600" height="338" title="&#x201C;Customer Data Mining for Lifestyle Segmentation&#x201D; &#x2014; Team Acua" data-secret="4wPe0JeRia" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script&gt;
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</html><description>Introduction and the Research Problem V.L. Migueis, A.S. Camanho, and Joao Falcao e Cunha proposed a study titled &#x201C;Customer Data Mining for Lifestyle Segmentation&#x201D; published in the Journal of Expert Systems with Applications, published by Elsevier in 2012. The study discusses that maintaining a good relationship with the customer base ensures companies gain a competitive&hellip; Continue reading Untitled</description><thumbnail_url>https://quecst.qcri.org/blog/wp-content/uploads/2022/01/fgg1.jpg</thumbnail_url></oembed>
