{"id":344880,"date":"2025-08-13T01:50:00","date_gmt":"2025-08-13T08:50:00","guid":{"rendered":"https:\/\/cms-articles.softonic.io\/es\/?p=393023"},"modified":"2025-08-13T01:51:55","modified_gmt":"2025-08-13T08:51:55","slug":"ai-and-the-transformation-of-b2b-marketing","status":"publish","type":"post","link":"https:\/\/cms-articles.softonic.io\/en\/ai-and-the-transformation-of-b2b-marketing\/","title":{"rendered":"AI and the transformation of B2B marketing"},"content":{"rendered":"\n<p>Historically, <strong>the world of <a href=\"https:\/\/www.genbeta.com\/a-fondo\/todos-cursos-marketing-digital-que-hay-estos-12-a-que-yo-me-apuntaria\">B2B marketing<\/a><\/strong> has placed a strong emphasis on personalization as <strong>the key to generating qualified leads.<\/strong> However, this approach has proven to be costly and ineffective, according to new data. A recent study by Gartner reveals that 61% of buyers prefer to make their purchases without the intervention of a sales representative, and 73% avoid messages they consider irrelevant. This underscores the urgency of distinguishing between knowing a potential customer&#8217;s name and understanding when they are ready to buy.<\/p>\n\n\n<h2 class=\"wp-block-heading\">The real purchase intention<\/h2>\n\n\n<p>Artificial intelligence (AI) emerges as a solution capable of transforming this paradigm. <strong>By shifting the focus from broad personalization to AI-driven relevance, marketing and sales teams can work more effectively<\/strong> by identifying prospects who truly have purchase intent. Instead of sending messages to a wide audience, it is more effective to target those who are genuinely ready for a sales conversation.<\/p>\n\n\n<p>The traditional approach has focused on engagement metrics, creating a disconnect between marketing and sales teams. <strong>While marketing celebrates email open rates, sales complain about the low quality of leads.<\/strong> AI now allows for the analysis of behavior patterns, intent signals, and contextual data, providing a relevance score that accurately identifies those prospects who are ready to buy.<\/p>\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" src=\"https:\/\/articles-img.sftcdn.net\/auto-mapping-folder\/sites\/2\/2025\/08\/b2b33.jpg\" alt=\"\" class=\"wp-image-393025\" \/><\/figure>\n\n\n<p>This approach also promises to redefine the lead qualification process by considering not only individual activities but also their sequence and context. Therefore, <strong>the transition to a relevance model opens the door to better alignment between marketing and sales, which could result in shorter sales cycles and more predictable revenue growth.<\/strong> In this new landscape, expectations are that the adoption of AI will become essential among sales leaders in the coming years.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Historically, the world of B2B marketing has placed a great emphasis on personalization as the key to generating qualified leads. However, this approach has proven to be costly and ineffective, according to new data. A recent study by Gartner reveals that 61% of buyers prefer to make their purchases without the intervention of a sales representative, and 73% avoid messages they consider irrelevant. This underscores the urgency of distinguishing between knowing a potential customer&#8217;s name and understanding when they are ready to buy. The actual buying intent Artificial intelligence (AI) emerges as a solution [&hellip;]<\/p>\n","protected":false},"author":9317,"featured_media":344895,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","wpcf-pageviews":0},"categories":[1015],"tags":[14212,3854,3885,4608,14992],"usertag":[],"vertical":[],"content-category":[],"class_list":["post-344880","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","tag-b2b","tag-ia","tag-inteligencia-artificial","tag-marketing","tag-marketing-b2b"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/posts\/344880","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/users\/9317"}],"replies":[{"embeddable":true,"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/comments?post=344880"}],"version-history":[{"count":3,"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/posts\/344880\/revisions"}],"predecessor-version":[{"id":344957,"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/posts\/344880\/revisions\/344957"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/media\/344895"}],"wp:attachment":[{"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/media?parent=344880"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/categories?post=344880"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/tags?post=344880"},{"taxonomy":"usertag","embeddable":true,"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/usertag?post=344880"},{"taxonomy":"vertical","embeddable":true,"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/vertical?post=344880"},{"taxonomy":"content-category","embeddable":true,"href":"https:\/\/cms-articles.softonic.io\/en\/wp-json\/wp\/v2\/content-category?post=344880"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}