1 publication

• Published Subscription 26 Jun 2026

  MQL Propensity Model to Predict Marketing Qualified Leads

  By Dipesh Gupta, Rahul Gupta, Santosh Jain

  Abstract: In the evolving landscape of digital marketing, accurately identifying high-potential leads remains a critical challenge due to increasing data complexity and fragmented analytical systems. This study proposes a comprehensive framework for developing a Marketing Qualified Lead (MQL) Propensity Model aimed at enhancing lead prediction accuracy and operational efficiency. By critically examining existing lead scoring methodologies across Customer Relationship Management (CRM) systems, web analytics platforms, and campaign management tools, the research …

  Published in NOLEGEIN Journal of Global Marketing · Vol. 9, Issue 2, 2026 Read article →