Enhancing CRM Accuracy Using Large Language Models (LLMs) in Salesforce Einstein GPT
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V2I4P109Keywords:
Customer Relationship Management (CRM), Salesforce Einstein GPT, Large Language Models, AI-driven CRM, Predictive analytics, Intelligent automation, Data accuracy, Customer insights, NLP in CRM, Context-aware recommendationsAbstract
Customer Relationship Management (CRM) systems have emerged as essential software to deal with client interaction, enhance customer satisfaction and boost revenues. Nevertheless, conventional CRM systems tend to have problems like lack of fully filled inputs, communication and automation and thus has hindered accuracy of the system and inefficiencies when performing operations. The advent of Large Language Models (LLMs), especially of the transformer type, such as GPT, allows extending CRM platforms to include intelligent, contextual, and adaptive functions. The present paper unravels the implementation of LLMs in Salesforce Einstein GPT printing higher accuracy of the CRM Devision through a more detailed analysis of customer data, the automatic production of responses, prognosis, and deepened communication processes. We discuss an end-to-end system to adopt LLMs during CRM operations, propose architecture and middle-ware layers and perform empirical analysis of real CRM data. We have found that data completeness, product relevancy and customer satisfaction have improved measurably as a result of applying generative AI in our CRM tank settings, and thus demonstrating the transformational potential of the approach. These results are corroborated by a case study of the telecommunication sector that indicates steep improvements in the customer response period and ticket costing rates. This paper ends with the discussion of the challenges, i.e., hallucination, data privacy, and domain adaption and the best practices of deploying LLMs in enterprise CRM systems. These findings indicate that, under adequate governance and integration design, LLMs are capable of increasing CRM precision to the extent that organizations will no longer have to adopt reactive attitudes toward managing their customers but can instead manage them with a proactive and customized approach
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