IJBTT

A Novel Approach to Incorporating LLMs in Mid-size Organizations for Customer Insight Generation Using Tree of Thoughts Methodology
	© 2024 by IJCTT Journal
	Volume-72 Issue-10
	Year of Publication : 2024
	Authors : Apurva Srivastava, Aditya Patil, Alokita Garg, Amruta Hebli
	DOI :  10.14445/22312803/IJCTT-V72I10P120

How to Cite?

Apurva Srivastava, Aditya Patil, Alokita Garg, Amruta Hebli, "A Novel Approach to Incorporating LLMs in Mid-size Organizations for Customer Insight Generation Using Tree of Thoughts Methodology," International Journal of Computer Trends and Technology, vol. 72, no. 10, pp. 127-140, 2024. Crossref, https://doi.org/10.14445/22312803/IJCTT-V72I10P120

Abstract
This paper presents a novel approach for mid-size organizations to leverage Large Language Models (LLMs) [2] for generating actionable insights from customer reviews and comments using the Tree of Thoughts (ToT) methodology [3]. LLMs have emerged as powerful tools for various text analytics tasks as natural language processing evolves. [1,2] However, their adoption in mid-size organizations has been limited due to resource constraints and technical complexities [14, 15]. The proposed cost-effective and efficient method leverages the ToT approach to optimize LLM usage for customer feedback analysis in resource-constrained environments. Our method significantly improves insight generation and computational efficiency compared to traditional approaches while requiring minimal LLM expertise [20]. Through a case study, this paper illustrates our approach's practical applications and benefits, providing a roadmap for mid-size organizations to harness the power of LLMs in their customer feedback analysis workflows [21].

Keywords
Customer insights, Large language models, Mid-size organizations, Natural language processing, Tree of thoughts

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