IJBTT

Advancing CRM Capabilities: A Comparative Analysis of Predictive Analytics Integration
	© 2024 by IJCTT Journal
	Volume-72 Issue-6
	Year of Publication : 2024
	Authors : Jagjot Bhardwaj, Lakshmi Sahitya Cherkuri, Pan Singh Dhoni, Pradeep Aluru
	DOI :  10.14445/22312803/IJCTT-V72I6P102

How to Cite?

Jagjot Bhardwaj, Lakshmi Sahitya Cherkuri, Pan Singh Dhoni, Pradeep Aluru, "Advancing CRM Capabilities: A Comparative Analysis of Predictive Analytics Integration," International Journal of Computer Trends and Technology, vol. 72, no. 6, pp. 8-14, 2024. Crossref, https://doi.org/10.14445/22312803/IJCTT-V72I6P102

Abstract
The paper explores the incorporation of predictive analytics into Customer Relationship Management (CRM) systems and its impact on business operations and customer service. A comparison of Salesforce Einstein, Microsoft Dynamics 365 AI, and Pegasystems reveals varied capabilities in using artificial intelligence to enhance customer interactions. Focusing on Salesforce Einstein, a case study demonstrates its effectiveness in predicting hospital readmission for diabetic patients, with the eXtreme Gradient Boosting model outperforming the Generalized Linear Model. The analysis emphasizes the potential of predictive analytics to improve CRM strategies despite data handling and privacy challenges. Insights from this research indicate that correctly leveraged CRM tools with predictive analytics can lead to better decision-making and increased customer satisfaction.

Keywords
CRM, Pegasystems, Microsoft dynamics 365, Salesforce einstein.

Reference

[1] Luis Matosas-López, Selecting A CRM Solution: Choosing Between Systems and Vendors, SAGE Publications: SAGE Business Cases Originals, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Jaideep Srivastava et al., “A Case for Analytical Customer Relationship Management,” Advances in Knowledge Discovery and Data Mining, pp. 14-27, 2002.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Manisha Rathi, Anand Priyadarshini, and Ankit Rastogi, “Predictive Analysis for Customer Relationship Management,” International Journal of Digital Content Technology and its Applications, vol. 4, no. 2, pp. 95-99, 2010.
[CrossRef] [Google Scholar]
[4] Damian Ciechan, “Comparative Analysis of Frameworks and Automation Tools in Terms of Functionality and Performance on the Salesforce CRM Platform,” Journal of Computer Sciences Institute, vol. 27, pp. 154-161, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Chee Sun Lee, Cheang Peck Yeng Sharon, and Moslehpour Massoud, “Predictive Analytics in Business Analytics: Decision Tree,” Advances in Decision Sciences, vol. 26, no. 1, pp. 1-29, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Prediction: The Future of CX, McKinsey & Company, 2021. [Online]. Available: www.mckinsey.com/capabilities/growth-marketingand-sales/our-insights/prediction-the-future-of-cx.
[7] Olamide Fred, “The Role of AI in CRM: Enhancing Customer Interactions and Predictive Analytics, Nicholas Idoko, 2023. [Online]. Available: nicholasidoko.com/blog/2023/02/21/the-role-of-ai-in-crm-enhancing-customer-interactions-and-predictive-analytics/.
[8] Rajeev Sharma, et al., “Business Analytics and Competitive Advantage: A Review and a Research Agenda,” Frontiers in Artificial Intelligence and Applications, vol. 212, pp. 187-198, 2010.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Mohamoud Ali, and Yugyung Lee, “CRM Sales Prediction Using Continuous Time-Evolving Classification,” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 32, no. 1, pp. 7727-7734, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Feng Feng, “Research of Customer Relationship Management Solutions Based on Data Mining,” Conference paper, Information Engineering and Applications, vol. 154, pp. 670-675, 2012.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Minnu F. Pynadath, T.M. Rofin, and Sam Thomas, “Evolution of Customer Relationship Management to Data Mining‑Based Customer Relationship Management: A Scientometric Analysis,” Quality & Quantity, vol. 57, pp. 3241-3272, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Jaideep Srivastava et al., “A Case for Analytical Customer Relationship Management”, Advances in Knowledge Discovery and Data Mining, pp. 14-27, 2002.
[CrossRef] [Google Scholar] [Publisher Link]
[13] What is Salesforce Einstein and How Can it Improve Your Business? Retrieved, 2021. [Online]. Available: https://consleague.com/salesforce-einstein/
[14] What is Salesforce Einstein Discovery? (And How to Use It). Retrieved, 2021. [Online]. Available: https://rainmakercloud.com/what-is-salesforce-einstein-discovery-and-how-to-use-it/
[15] Using Predictive Analytics to Increase Customer Value, Retrieved, 2021, [Online]. Available: https://www.pega.com/products/crm-applications/customer-decision-hub/
[16] Stephanie Dart, Introducing Next-Generation AI and Copilot Capabilities for ERP - Microsoft Dynamics 365 Blog, Microsoft Dynamics 365 Blog, 2023. [Online]. Available: https://cloudblogs.microsoft.com/dynamics365/bdm/2023/06/15/introducing-next-generation-ai-and-microsoft-dynamics-365-copilot-capabilities-for-erp/
[17] Kamal Changezi, The Impact of Artificial Intelligence on Microsoft Dynamics 365, 2023. [online]. Available: https://www.direction.biz/blogs/the-impact-of-artificial-intelligence-on-microsoft-dynamics-365/
[18] Alphabold, AI in CRM: Exploring Microsoft Dynamics 365 Benefits, 2023. [Online]. Available: https://www.alphabold.com/ai-in-crm-exploring-microsoft-dynamics-365-benefits/
[19] John Clore et al., “Diabetes 130-US Hospitals for Years 1999-2008,”UCI Machine Learning Repository, 2014.
[CrossRef] [Publisher Link]
[20] Christina George, Salesforce vs Microsoft Dynamics vs SugarCRM: Which is the Winner? 2024. [Online]. Available: https://www.selecthub.com/customer-relationship-management/salesforce-com-vs-microsoft-dynamics-vs-sugarcrm/.
[21] Mike Vizard, Pega vs Salesforce: 2022 CRM Software Comparison, 2019. [Online]. Available: https://www.itbusinessedge.com/applications/pega-crm-vs-salesforce/