Personalization in Salesforce CRM with AI: How AI/ML Can Enhance Customer Interactions through Personalized Recommendations and Automated Insights

Authors

  • Vasanta Kumar Tarra Lead Engineer at Guidewire Software, USA. Author

DOI:

https://doi.org/10.63282/3050-922X.IJERET-V5I4P106

Keywords:

Article Structure: Personalization in Salesforce CRM with AI, Salesforce CRM, AI in CRM, Machine Learning, Personalized Customer Experience, Automated Insights, Predictive Analytics, Customer Relationship Management, Recommendation Systems, Salesforce Einstein AI

Abstract

Artificial intelligence (AI) and machine learning (ML) are reshining corporate-customer connections and also improving CRM systems to be more intelligent, understandable, and customized. Leading in customer relationship management, Salesforce CRM leverages artificial intelligence to increase client engagement, streamline operations, and enhance organizational performance. Driven by Einstein AI, Salesforce's AI-driven capabilities help businesses foresee consumer needs, streamline labor-intensive operations, and offer very customized experiences. By means of smart recommendations accelerating sales team deal completion and by automating tasks reducing human labor, thereby improving productivity and customer attention. AI improves CRM interactions. This paper explores how artificial intelligence in Salesforce CRM influences customer interactions, user experiences, and business success. We will examine how tools including predictive analytics, chatbots, and intelligent automation help companies not only meet but exceed demand from customers. This talk will assist you to completely understand how artificial intelligence-driven personalization in Salesforce could improve relationships, raise sales performance, and give a competitive advantage in the new digital economy. This knowledge of AI-driven CRM technologies will help salespeople, marketers, and business leaders in a customer-centric environment keep a competitive advantage. Businesses are always seeking methods to improve consumer interactions and provide tailored experiences in the fast-paced digital environment of today. Here is where Machine Learning (ML) and Artificial Intelligence (AI) help to transform Customer Relationship Management (CRM) systems like Salesforce. AI-driven tools included in Salesforce CRM enable companies to better grasp consumer demands, forecast behavior, and automatically run interactions. Salesforce has changed how companies communicate with consumers with the arrival of products like Einstein AI making engagement smarter, faster, and more simple. AI-driven insights help companies to suggest pertinent items, customize marketing campaigns, and automate repetitive processes, so enhancing customer satisfaction and productivity

References

[1] Nair, Sonal, et al. "Enhancing Sales Performance with AI-Powered Voice Assistants: Leveraging Natural Language Processing and Reinforcement Learning Algorithms." Journal of AI ML Research 9.4 (2020).

[2] Kupunarapu, Sujith Kumar. "AI-Enabled Remote Monitoring and Telemedicine: Redefining Patient Engagement and Care Delivery." International Journal of Science And Engineering 2.4 (2016): 41-48.

[3] Oladele, Oluwaseyi. "AI-Driven Customer Journey Mapping for Enhanced Product Lifecycle Management and Sales Forecasting." (2023).

[4] Chaganti, Krishna. "Adversarial Attacks on AI-driven Cybersecurity Systems: A Taxonomy and Defense Strategies." Authorea Preprints.

[5] Latinovic, Zoran, and Sharmila C. Chatterjee. "Achieving the promise of AI and ML in delivering economic and relational customer value in B2B." Journal of Business Research 144 (2022): 966-974.

[6] Sangaraju, Varun Varma. "Optimizing Enterprise Growth with Salesforce: A Scalable Approach to Cloud-Based Project Management." International Journal of Science And Engineering 8.2 (2022): 40-48.

[7] Paschen, Jeannette, Matthew Wilson, and João J. Ferreira. "Collaborative intelligence: How human and artificial intelligence create value along the B2B sales funnel." Business Horizons 63.3 (2020): 403-414.

[8] Fatouretchi, Max. The The Art of CRM: Proven strategies for modern customer relationship management. Packt Publishing Ltd, 2019.

[9] Sangeeta Anand, and Sumeet Sharma. “Leveraging AI-Driven Data Engineering to Detect Anomalies in CHIP Claims”. Los Angeles Journal of Intelligent Systems and Pattern Recognition, vol. 1, Apr. 2021, pp. 35-55

[10] Wolf, Christine T. "AI Ethics and Customer Care: Some Considerations from the Case of “Intelligent Sales”." (2020).

[11] Chaganti, Krishna Chaitanya. "AI-Powered Threat Detection: Enhancing Cybersecurity with Machine Learning." International Journal of Science And Engineering 9.4 (2023): 10-18.

[12] Rusthollkarhu, Sami, et al. "Managing B2B customer journeys in digital era: Four management activities with artificial intelligence-empowered tools." Industrial Marketing Management 104 (2022): 241-257.

[13] Guduru, Venkat Sumanth. "Building a 360-Degree Customer View with Salesforce Data Cloud." Journal of Marketing & Supply Chain Management. SRC/JMSCM-E103. DOI: doi. org/10.47363/JMSCM/2023 (2) E103 J Market & Supply Chain Managem 2.4 (2023): 2-5.

[14] Núñez, María Torre. "The Implementation Of AI In Marketing." Universidad Pontificia de Comillas (2021).

[15] Varma, Yasodhara, and Manivannan Kothandaraman. “Optimizing Large-Scale ML Training Using Cloud-Based Distributed Computing”. International Journal of Artificial Intelligence, Data Science, and Machine Learning, vol. 3, no. 3, Oct. 2022, pp. 45-54

[16] Yasodhara Varma. “Scalability and Performance Optimization in ML Training Pipelines”. American Journal of Autonomous Systems and Robotics Engineering, vol. 3, July 2023, pp. 116-43

[17] Mehdi Syed, Ali Asghar, and Erik Anazagasty. “Ansible Vs. Terraform: A Comparative Study on Infrastructure As Code (IaC) Efficiency in Enterprise IT”. International Journal of Emerging Trends in Computer Science and Information Technology, vol. 4, no. 2, June 2023, pp. 37-48

[18] Sangaraju, Varun Varma. "UI Testing, Mutation Operators, And the DOM in Sensor-Based Applications."

[19] Sreedhar, C., and Varun Verma Sangaraju. "A Survey On Security Issues In Routing In MANETS." International Journal of Computer Organization Trends 3.9 (2013): 399-406.

[20] Kupunarapu, Sujith Kumar. "AI-Driven Crew Scheduling and Workforce Management for Improved Railroad Efficiency." International Journal of Science And Engineering 8.3 (2022): 30-37.

[21] Anand, Sangeeta. “Designing Event-Driven Data Pipelines for Monitoring CHIP Eligibility in Real-Time”. International Journal of Emerging Research in Engineering and Technology, vol. 4, no. 3, Oct. 2023, pp. 17-26

[22] Kupunarapu, Sujith Kumar. "AI-Enhanced Rail Network Optimization: Dynamic Route Planning and Traffic Flow Management." International Journal of Science And Engineering 7.3 (2021): 87-95.

[23] Sciammarelli, Jessica Araujo. "THE USE CASE OF ARTIFICIAL INTELLIGENCE IN MARKETING AND SALES." REVISTA FOCO 16.5 (2023): e02060-e02060.

[24] Sangeeta Anand, and Sumeet Sharma. “Leveraging ETL Pipelines to Streamline Medicaid Eligibility Data Processing”. American Journal of Autonomous Systems and Robotics Engineering, vol. 1, Apr. 2021, pp. 358-79

[25] Chaganti, Krishna C. "Advancing AI-Driven Threat Detection in IoT Ecosystems: Addressing Scalability, Resource Constraints, and Real-Time Adaptability."

[26] Patel, Amit, et al. "Enhancing Sales Efficiency Through AI: Leveraging Natural Language Processing and Reinforcement Learning for Automated Sales Tools." International Journal of AI ML Innovations 11.8 (2022).

[27] Chaganti, Krishna Chiatanya. "Securing Enterprise Java Applications: A Comprehensive Approach." International Journal of Science And Engineering 10.2 (2024): 18-27.

[28] Mehdi Syed, Ali Asghar. “Zero Trust Security in Hybrid Cloud Environments: Implementing and Evaluating Zero Trust Architectures in AWS and On-Premise Data Centers”. International Journal of Emerging Trends in Computer Science and Information Technology, vol. 5, no. 2, Mar. 2024, pp. 42-52

[29] Cyvoct, Alexandra, and Shirin Fathi. "Artificial Intelligence in Business-to-Business Sales Processes: The impact on the sales representatives and management implications." (2019).

[30] Lakshmikanthan, G., & Sreekandan Nair, S. (2024). Protecting Self-Driving Vehicles from attack threats. International Journal of Emerging Research in Engineering and Technology, 5(1), 16-20.

[31] Mehdi Syed, Ali Asghar. “Hyperconverged Infrastructure (HCI) for Enterprise Data Centers: Performance and Scalability Analysis”. International Journal of AI, BigData, Computational and Management Studies, vol. 4, no. 4, Dec. 2023, pp. 29-38

[32] Yasodhara Varma. “Managing Data Security & Compliance in Migrating from Hadoop to AWS”. American Journal of Autonomous Systems and Robotics Engineering, vol. 4, Sept. 2024, pp. 100-19

[33] Anand, Sangeeta. “Automating Prior Authorization Decisions Using Machine Learning and Health Claim Data”. International Journal of Artificial Intelligence, Data Science, and Machine Learning, vol. 3, no. 3, Oct. 2022, pp. 35-44

[34] Sangaraju, Varun Varma, and Senthilkumar Rajagopal. "Applications of Computational Models in OCD." Nutrition and Obsessive-Compulsive Disorder. CRC Press 26-35.

[35] Dunie, Rob, et al. "Magic Quadrant for intelligent business process management suites." Gartner Inc (2015).

[36] Kupunarapu, Sujith Kumar. "Data Fusion and Real-Time Analytics: Elevating Signal Integrity and Rail System Resilience." International Journal of Science And Engineering 9.1 (2023): 53-61.

[37] Chaganti, Krishna C. "Leveraging Generative AI for Proactive Threat Intelligence: Opportunities and Risks." Authorea Preprints.

[38] Sangaraju, Varun Varma. "AI-Augmented Test Automation: Leveraging Selenium, Cucumber, and Cypress for Scalable Testing." International Journal of Science And Engineering 7.2 (2021): 59-68.

[39] Mehdi Syed, Ali Asghar, and Erik Anazagasty. “AI-Driven Infrastructure Automation: Leveraging AI and ML for Self-Healing and Auto-Scaling Cloud Environments”. International Journal of Artificial Intelligence, Data Science, and Machine Learning, vol. 5, no. 1, Mar. 2024, pp. 32-43

[40] Akter, Shahriar, et al. "Transforming business using digital innovations: The application of AI, blockchain, cloud and data analytics." Annals of Operations Research (2022): 1-33.

[41] Baviskar, Kajal, et al. "Artificial intelligence and machine learning‐based manufacturing and drug product marketing." Bioinformatics tools for pharmaceutical drug product development (2023): 197-231.

Downloads

Published

2024-12-31

Issue

Section

Articles

How to Cite

1.
Tarra VK. Personalization in Salesforce CRM with AI: How AI/ML Can Enhance Customer Interactions through Personalized Recommendations and Automated Insights. IJERET [Internet]. 2024 Dec. 31 [cited 2025 Sep. 12];5(4):52-61. Available from: https://ijeret.org/index.php/ijeret/article/view/112