Author
Listed:
- Oyenmwen Umoren
- Paul Uche Didi
- Oluwatosin Balogun
- Ololade Shukrah Abass
- Oluwatolani Vivian Akinrinoye
Abstract
The increasing complexity of consumer behavior and the demand for hyper-personalized experiences have driven organizations to adopt integrated digital solutions across their sales and marketing ecosystems. This review critically evaluates Customer Relationship Management (CRM) systems, Marketing Automation tools, and Engagement Platforms to understand their comparative influence on optimizing data-driven sales funnel performance. Emphasis is placed on how each category contributes to lead generation, nurturing, conversion, and customer retention by leveraging behavioral data, predictive analytics, and omnichannel strategies. The study synthesizes key features, technological capabilities, and performance metrics across these platforms, drawing from academic and industry literature to provide a strategic framework for their implementation. Particular focus is placed on scalability, AI-enhanced personalization, campaign automation, and cross-functional integration within digital marketing ecosystems. The paper aims to assist business leaders, marketers, and technologists in identifying the most suitable solution stack for their funnel optimization goals, ensuring sustainable customer engagement and revenue growth in a data-centric digital economy.
Suggested Citation
Oyenmwen Umoren & Paul Uche Didi & Oluwatosin Balogun & Ololade Shukrah Abass & Oluwatolani Vivian Akinrinoye, 2024.
"A Comparative Evaluation of CRM, Marketing Automation, and Engagement Platforms in Driving Data-Driven Sales Funnel Performance,"
International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 10(4), pages 672-697, August.
Handle:
RePEc:jbh:ijsrcs:v10:y2024:i4:id:1642
DOI: 10.32628/CSEIT25113493
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT25113493
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