Data-Driven Decision Making: Integrating AI Tools with CRM Platforms

  • Authors

    • Satyendra Kumar Vanapalli Consultant, Technical Solutions at Visa Inc, USA. Author

    DOI:

    https://doi.org/10.67228/30713498/IJADSMC-2023PI7Y3L

    Published 06-06-2023

  • Data-Driven Decision Making, Artificial Intelligence, CRM Integration, Predictive Analytics, Machine Learning, Customer Relationship Management, Business Intelligence, Data Analytics, Customer Insights, Automation, Decision Support Systems, Digital Transformation

    Issue

    Vol. 6 No. 1 (2023)

    Section

    Articles

    How to Cite

    [1]
    S. K. Vanapalli, “Data-Driven Decision Making: Integrating AI Tools with CRM Platforms”, IJADSMC, vol. 6, no. 1, pp. 01–21, Jun. 2023, doi: 10.67228/30713498/IJADSMC-2023PI7Y3L.

  • Abstract

    In the digital age we are living in today, organizations are required to be able to make decisions based upon the information they have. This enables businesses to make decisions based on facts as opposed to gut feelings. Customer relationship management (CRM) technology is at the heart of this transformation. They are venues when businesses can get, assemble together, and study client data from a lot of various areas. Companies trying to figure out how customers usually responded and what their bodies really need have had their work cut out for these individuals since they started employing advanced AI methods like supervised learning, natural language processing, and standard analytics for prediction. This study looks at how AI can be used with typical CRM systems to strengthen how people conduct decisions in regular organizations, making them superior, faster, and tailored to each person. It explains how AI makes CRM more accurate by finding patterns of behavior that aren't visible, automating operations that are done countless times, and offering organizations resources to help them predict what will happen in the future so they are more capable of helping their customers and make things run easier and more efficiently. The study utilizes a pragmatic approach, utilizing an authentic case study to illustrate the procedure's functionality, the problems presented, and the methods put in place to ensure a successful implementation. This method demonstrates how a company can turn unstructured into information that is useful. The most significant outcomes show that CRM apps enabled by AI make businesses much easier to divide clients into groups, guess sales, and help customers with customer service questions. This gives the organization greater standards and an increased probability of beating other companies. The integration also assists in establishing a culture of decision-making that is more forward-thinking, where insights are mainly descriptive but also predictive as well as prescriptive. This article examines how crucial it is to link AI developments to CRM platforms in increasing numbers.

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