<?xml version="1.0" encoding="UTF-8"?>
<article article-type="research-article" xml:lang="en" xmlns:xlink="http://www.w3.org/1999/xlink">
<front>
<journal-meta>
<journal-id journal-id-type="publisher">global-journal-of-management-and-business-research-e-marketing</journal-id>
<journal-title-group>
<journal-title>Global Journal of Management and Business Research - E: Marketing</journal-title>
</journal-title-group>
<issn publication-format="print">0975-5853</issn>
<issn publication-format="electronic">2249-4588</issn>
<publisher><publisher-name>Global Journals Publishing Group Incorporated</publisher-name></publisher>
<self-uri xlink:href="https://globaljournals.org/journal-seo-export/jats/56826.xml" />
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.34257/GJMBREVOL20IS5PG1</article-id>
<article-id pub-id-type="publisher-id">56826</article-id>
<title-group>
<article-title>A Guide towards Building Effective, Metrics-Driven and Mathematical Sales Segmentation Models for an Enterprise B2B SaaS Business</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>Iyer</surname><given-names>Venketesh</given-names></name><xref ref-type="aff" rid="aff1" />
</contrib>
<contrib contrib-type="author"><name><surname>Perevali</surname><given-names>Rahul</given-names></name></contrib>
</contrib-group>
<aff id="aff1">UNITED STATES, University of California, Berkeley</aff>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2020-01-15">
<day>15</day>
<month>01</month>
<year>2020</year>
</pub-date>
<volume>20</volume>
<issue>E5</issue>
<fpage>1</fpage>
<lpage>7</lpage>
<abstract><p>The paper’s goal is to help B2B SaaS companies attain two primary goals -1. Leverage best-in-class business firmographic data for building territory segmentation models 2. Balance the models against the most effective sales metrics, and 3. Understand and optimize for territory disruption year over year due to change in the scale of business. In the paper, we build a model based on the most fundamental building blocks of any SaaS business. The analytical model helps the sales operations, revenue operations and sales departments understand the main drivers of territory disruption and, build balanced territory segments to ensure equitable financial targets for sales reps.</p></abstract>
<kwd-group kwd-group-type="author-generated">
<kwd>sales operations</kwd>
<kwd>sales strategy</kwd>
<kwd>analytics</kwd>
<kwd>territory operations</kwd>
<kwd>segmentation</kwd>
<kwd>territory carving</kwd>
</kwd-group>
<self-uri content-type="pdf" xlink:href="https://globaljournals.org/GJMBR_Volume20/1-A-Guide-towards-Building.pdf" />
<self-uri content-type="html" xlink:href="https://globaljournals.org/scholarly-articles/a-guide-towards-building-effective-metrics-driven-and-mathematical-sales-segmentation-models-for-an-enterprise-b2b-saas-business/" />
</article-meta>
</front>
<body>
<sec>
<title>Full Text</title>
<p>The paperâ€™s goal is to help B2B SaaS companies attain two primary goals - 1. Leverage best-in-class business firmographic data for building territory segmentation models 2. Balance the models against the most effective sales metrics, and 3. Understand and optimize for territory disruption year over year due to change in the scale of business. In the paper, we build a model based on the most fundamental building blocks of any SaaS business.</p>
</sec>
</body>
</article>