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    <title>topic Solution Accelerator Series | Survival Analysis for Churn and Lifetime Value in Announcements</title>
    <link>https://community.databricks.com/t5/announcements/solution-accelerator-series-survival-analysis-for-churn-and/m-p/157675#M822</link>
    <description>&lt;P&gt;&lt;SPAN&gt;Survival analysis is a set of &lt;/SPAN&gt;&lt;STRONG&gt;statistical methods&lt;/STRONG&gt;&lt;SPAN&gt; used to examine and predict the time until an event happens. This &lt;/SPAN&gt;&lt;STRONG&gt;Survival Analysis for Churn and Lifetime Value &lt;/STRONG&gt;&lt;SPAN&gt;Solution Accelerator shows how these techniques can be used to predict churn, calculate lifetime value and better understand the factors that &lt;/SPAN&gt;&lt;STRONG&gt;influence the customer lifecycle&lt;/STRONG&gt;&lt;SPAN&gt;.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;FONT size="4"&gt;&lt;STRONG&gt;With this Accelerator, you get&lt;/STRONG&gt;&lt;/FONT&gt;&lt;/P&gt;
&lt;UL&gt;
&lt;LI aria-level="1"&gt;&lt;STRONG&gt;Ready-to-use resources:&lt;/STRONG&gt;&lt;A href="https://notebooks.databricks.com/notebooks/CME/Survival_Analysis/index.html?itm_source=www&amp;amp;itm_category=solutions&amp;amp;itm_page=survival-analysis-for-churn-and-lifetime-value&amp;amp;itm_location=body&amp;amp;itm_component=cta-image-block&amp;amp;itm_offer=index.html#Survival_Analysis_1.html" target="_self"&gt; &lt;STRONG&gt;pre-built code, sample data and step-by-step instructions ready to go in a Databricks notebook&lt;/STRONG&gt;&lt;/A&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;UL&gt;
&lt;LI aria-level="1"&gt;&lt;STRONG&gt;Understand customer lifecycle drivers:&lt;/STRONG&gt;&lt;SPAN&gt; Identify which factors contribute most to extending the customer lifecycle.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;UL&gt;
&lt;LI aria-level="1"&gt;&lt;STRONG&gt;Predict churn risk: &lt;/STRONG&gt;&lt;SPAN&gt;Identify which customers are at risk of churning.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;UL&gt;
&lt;LI aria-level="1"&gt;&lt;STRONG&gt;Support spend decisions: &lt;/STRONG&gt;&lt;SPAN&gt;Optimize marketing spend based on the ratio of lifetime value to cost of acquisition.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;P class="p8i6j01 paragraph"&gt;&lt;A style="background-color: #ff3621; color: white; padding: 10px 20px; text-decoration: none; border-radius: 5px; font-weight: bold; display: inline-block;" href="https://www.databricks.com/solutions/accelerators/survival-analysis-for-churn-and-lifetime-value?itm_source=www&amp;amp;itm_category=solutions&amp;amp;itm_page=accelerators&amp;amp;itm_location=body&amp;amp;itm_component=general-asset-card&amp;amp;itm_offer=survival-analysis-for-churn-and-lifetime-value" target="_blank" rel="noopener"&gt;&lt;span class="lia-unicode-emoji" title=":link:"&gt;🔗&lt;/span&gt;&amp;nbsp;Launch Solution Accelerator&amp;nbsp;&lt;span class="lia-unicode-emoji" title=":backhand_index_pointing_left:"&gt;👈&lt;/span&gt;&lt;/A&gt;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Tue, 26 May 2026 13:41:44 GMT</pubDate>
    <dc:creator>Tushar_Parekar</dc:creator>
    <dc:date>2026-05-26T13:41:44Z</dc:date>
    <item>
      <title>Solution Accelerator Series | Survival Analysis for Churn and Lifetime Value</title>
      <link>https://community.databricks.com/t5/announcements/solution-accelerator-series-survival-analysis-for-churn-and/m-p/157675#M822</link>
      <description>&lt;P&gt;&lt;SPAN&gt;Survival analysis is a set of &lt;/SPAN&gt;&lt;STRONG&gt;statistical methods&lt;/STRONG&gt;&lt;SPAN&gt; used to examine and predict the time until an event happens. This &lt;/SPAN&gt;&lt;STRONG&gt;Survival Analysis for Churn and Lifetime Value &lt;/STRONG&gt;&lt;SPAN&gt;Solution Accelerator shows how these techniques can be used to predict churn, calculate lifetime value and better understand the factors that &lt;/SPAN&gt;&lt;STRONG&gt;influence the customer lifecycle&lt;/STRONG&gt;&lt;SPAN&gt;.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;FONT size="4"&gt;&lt;STRONG&gt;With this Accelerator, you get&lt;/STRONG&gt;&lt;/FONT&gt;&lt;/P&gt;
&lt;UL&gt;
&lt;LI aria-level="1"&gt;&lt;STRONG&gt;Ready-to-use resources:&lt;/STRONG&gt;&lt;A href="https://notebooks.databricks.com/notebooks/CME/Survival_Analysis/index.html?itm_source=www&amp;amp;itm_category=solutions&amp;amp;itm_page=survival-analysis-for-churn-and-lifetime-value&amp;amp;itm_location=body&amp;amp;itm_component=cta-image-block&amp;amp;itm_offer=index.html#Survival_Analysis_1.html" target="_self"&gt; &lt;STRONG&gt;pre-built code, sample data and step-by-step instructions ready to go in a Databricks notebook&lt;/STRONG&gt;&lt;/A&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;UL&gt;
&lt;LI aria-level="1"&gt;&lt;STRONG&gt;Understand customer lifecycle drivers:&lt;/STRONG&gt;&lt;SPAN&gt; Identify which factors contribute most to extending the customer lifecycle.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;UL&gt;
&lt;LI aria-level="1"&gt;&lt;STRONG&gt;Predict churn risk: &lt;/STRONG&gt;&lt;SPAN&gt;Identify which customers are at risk of churning.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;UL&gt;
&lt;LI aria-level="1"&gt;&lt;STRONG&gt;Support spend decisions: &lt;/STRONG&gt;&lt;SPAN&gt;Optimize marketing spend based on the ratio of lifetime value to cost of acquisition.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;P class="p8i6j01 paragraph"&gt;&lt;A style="background-color: #ff3621; color: white; padding: 10px 20px; text-decoration: none; border-radius: 5px; font-weight: bold; display: inline-block;" href="https://www.databricks.com/solutions/accelerators/survival-analysis-for-churn-and-lifetime-value?itm_source=www&amp;amp;itm_category=solutions&amp;amp;itm_page=accelerators&amp;amp;itm_location=body&amp;amp;itm_component=general-asset-card&amp;amp;itm_offer=survival-analysis-for-churn-and-lifetime-value" target="_blank" rel="noopener"&gt;&lt;span class="lia-unicode-emoji" title=":link:"&gt;🔗&lt;/span&gt;&amp;nbsp;Launch Solution Accelerator&amp;nbsp;&lt;span class="lia-unicode-emoji" title=":backhand_index_pointing_left:"&gt;👈&lt;/span&gt;&lt;/A&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Tue, 26 May 2026 13:41:44 GMT</pubDate>
      <guid>https://community.databricks.com/t5/announcements/solution-accelerator-series-survival-analysis-for-churn-and/m-p/157675#M822</guid>
      <dc:creator>Tushar_Parekar</dc:creator>
      <dc:date>2026-05-26T13:41:44Z</dc:date>
    </item>
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