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    <title>topic Re: What is the best methodology for building a financial product propensity model... in SAS Data Science</title>
    <link>https://communities.sas.com/t5/SAS-Data-Science/What-is-the-best-methodology-for-building-a-financial-product/m-p/179801#M2140</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hey Omer,&lt;/P&gt;&lt;P&gt;Sounds like a nice project. How did you come up with the 6-month observation window, just business knowledge? You can back up that decision with time series analysis or just testing for any seasonality. 6-months could make sense as long as it accounts for high sale seasons like Christmas, special promotions or holidays.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;What do you mean with using a decision tree to reduce the size of your data? variable selection? you have a better understanding from this thread &lt;A __default_attr="58368" __jive_macro_name="thread" class="jive_macro jive_macro_thread" href="https://communities.sas.com/"&gt;&lt;/A&gt; correct?&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Without knowing too much about the data, you might need to assess what works best for your definitions of active/inactive and how often they go from one to another. It might make sense to have a model for actives, inactive for less than 2 quarters, inactive 2-4 quarters, and inactives more than a year. Establishing those segments will add a lot of value to your business and to your models.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Good luck!&lt;/P&gt;&lt;P&gt;Miguel&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Thu, 05 Jun 2014 17:09:28 GMT</pubDate>
    <dc:creator>M_Maldonado</dc:creator>
    <dc:date>2014-06-05T17:09:28Z</dc:date>
    <item>
      <title>What is the best methodology for building a financial product propensity model...</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/What-is-the-best-methodology-for-building-a-financial-product/m-p/179800#M2139</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hi recently i have started a new project which targets to identify propensity to purchase of any financial product for every active customer. However i am not sure on what methodlogy to follow... &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Here is my plan &lt;/P&gt;&lt;P&gt;- First i will go to 6 months prior to today, and set my flag on ownership of specific product on T-6 mthns&lt;/P&gt;&lt;P&gt;- Then i will collect data as of T-6 mthns (or should i take today's data) &lt;/P&gt;&lt;P&gt;-I will take every specific product's data on my datamart expect the data related to my target variable.. &lt;/P&gt;&lt;P&gt;-I will employ a decision tree to make a reduction in data size&lt;/P&gt;&lt;P&gt;-Then i will built my propensity model on&amp;nbsp; outcomes of previous model &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;is that made sense? &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;LAstly i am not sure that &lt;/P&gt;&lt;P&gt;do i have to estimate model on all active customer segment or all customer segment. Hence if i calculated my scores on all customer segment many of the individuals will exhibit "0" value for many product ownership and that will&amp;nbsp; deteriorate my models consistency..&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;am i right? &lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Sun, 01 Jun 2014 15:17:09 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/What-is-the-best-methodology-for-building-a-financial-product/m-p/179800#M2139</guid>
      <dc:creator>omerzeybek</dc:creator>
      <dc:date>2014-06-01T15:17:09Z</dc:date>
    </item>
    <item>
      <title>Re: What is the best methodology for building a financial product propensity model...</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/What-is-the-best-methodology-for-building-a-financial-product/m-p/179801#M2140</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hey Omer,&lt;/P&gt;&lt;P&gt;Sounds like a nice project. How did you come up with the 6-month observation window, just business knowledge? You can back up that decision with time series analysis or just testing for any seasonality. 6-months could make sense as long as it accounts for high sale seasons like Christmas, special promotions or holidays.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;What do you mean with using a decision tree to reduce the size of your data? variable selection? you have a better understanding from this thread &lt;A __default_attr="58368" __jive_macro_name="thread" class="jive_macro jive_macro_thread" href="https://communities.sas.com/"&gt;&lt;/A&gt; correct?&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Without knowing too much about the data, you might need to assess what works best for your definitions of active/inactive and how often they go from one to another. It might make sense to have a model for actives, inactive for less than 2 quarters, inactive 2-4 quarters, and inactives more than a year. Establishing those segments will add a lot of value to your business and to your models.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Good luck!&lt;/P&gt;&lt;P&gt;Miguel&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 05 Jun 2014 17:09:28 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/What-is-the-best-methodology-for-building-a-financial-product/m-p/179801#M2140</guid>
      <dc:creator>M_Maldonado</dc:creator>
      <dc:date>2014-06-05T17:09:28Z</dc:date>
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