1.0be-inf.aihttps://be-inf.ai/deadminhttps://be-inf.ai/de/author/admin/rich600338<blockquote class="wp-embedded-content" data-secret="dHhWdtNNYo"><a href="https://be-inf.ai/de/case/predictive-analytics-churn-risk/">Ein Telekommunikationsanbieter kann nun Kunden mit hohem Abwanderungsrisiko drei Monate im Voraus identifizieren.</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://be-inf.ai/de/case/predictive-analytics-churn-risk/embed/#?secret=dHhWdtNNYo" width="600" height="338" title="„Ein Telekommunikationsanbieter kann nun Kunden mit hohem Abwanderungsrisiko drei Monate im Voraus erkennen“ – be-inf.ai" data-secret="dHhWdtNNYo" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script> /*! This file is auto-generated */ !function(d,l){"use strict";l.querySelector&&d.addEventListener&&"undefined"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!/[^a-zA-Z0-9]/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret="'+t.secret+'"]'),o=l.querySelectorAll('blockquote[data-secret="'+t.secret+'"]'),c=new RegExp("^https?:$","i"),i=0;i<o.length;i++)o[i].style.display="none";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute("style"),"height"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):"link"===t.message&&(r=new URL(s.getAttribute("src")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener("message",d.wp.receiveEmbedMessage,!1),l.addEventListener("DOMContentLoaded",function(){for(var e,t,s=l.querySelectorAll("iframe.wp-embedded-content"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute("data-secret"))||(t=Math.random().toString(36).substring(2,12),e.src+="#?secret="+t,e.setAttribute("data-secret",t)),e.contentWindow.postMessage({message:"ready",secret:t},"*")},!1)))}(window,document); //# sourceURL=https://be-inf.ai/wp-includes/js/wp-embed.min.js </script>See how a provider with 70,000 subscribers reduced revenue loss by predicting churn early. We consolidated payment history and technical logs to identify unhappy customers before they decided to leave. This proactive approach allowed the team to fix issues and keep customers loyal.