<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" version="2.0">
  <channel>
    <title>topic Re: Customer Engagement Model. in SAS Data Science</title>
    <link>https://communities.sas.com/t5/SAS-Data-Science/Customer-Engagement-Model/m-p/332034#M4986</link>
    <description>&lt;P&gt;I would have approached it differently. Specifically, I would have identified the customers your company considers engaged, and then build a model (using both engaged and not engaged customers) and predict "engaged".&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;To answer your second question, as long as price increases were included in the data, you should get an indication of their effects.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Art, CEO, AnalystFinder.com&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Sun, 12 Feb 2017 23:07:40 GMT</pubDate>
    <dc:creator>art297</dc:creator>
    <dc:date>2017-02-12T23:07:40Z</dc:date>
    <item>
      <title>Customer Engagement Model.</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/Customer-Engagement-Model/m-p/331982#M4984</link>
      <description>&lt;DIV class="lia-message-heading lia-component-message-header"&gt;&amp;nbsp;&lt;/DIV&gt;
&lt;P class="lia-message-dates lia-message-post-date lia-component-post-date-last-edited"&gt;Hi All,&lt;/P&gt;
&lt;DIV id="messagebodydisplay_0" class="lia-message-body"&gt;
&lt;DIV class="lia-message-body-content"&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I have built a customer engagement model using logistic regression, The approach was to take a group of customers we consider engaged, then build model to find lookalike in the customer base.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;The most important variables were as you will expect, number of visits in the last 12 weeks, number of distinct product they use in the last 12&amp;nbsp;weeks etc...I have also entered variables, like visits in the last 1 week, last 4 weeks etc but the most important were only 12 weeks var.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;My question is if there is any change , like price increase of products or any other events that will impact the purchase. How do I make sure in the model that it won't take 12 weeks to see how customers are getting disengaged etc..&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Your help would be much appreciated.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Thank You so much&lt;/P&gt;
&lt;/DIV&gt;
&lt;/DIV&gt;</description>
      <pubDate>Sun, 12 Feb 2017 20:50:08 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/Customer-Engagement-Model/m-p/331982#M4984</guid>
      <dc:creator>Question</dc:creator>
      <dc:date>2017-02-12T20:50:08Z</dc:date>
    </item>
    <item>
      <title>Re: Customer Engagement Model.</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/Customer-Engagement-Model/m-p/332034#M4986</link>
      <description>&lt;P&gt;I would have approached it differently. Specifically, I would have identified the customers your company considers engaged, and then build a model (using both engaged and not engaged customers) and predict "engaged".&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;To answer your second question, as long as price increases were included in the data, you should get an indication of their effects.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Art, CEO, AnalystFinder.com&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Sun, 12 Feb 2017 23:07:40 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/Customer-Engagement-Model/m-p/332034#M4986</guid>
      <dc:creator>art297</dc:creator>
      <dc:date>2017-02-12T23:07:40Z</dc:date>
    </item>
  </channel>
</rss>

