International Journal of Computer
Trends and Technology

Research Article | Open Access | Download PDF

Volume 72 | Issue 10 | Year 2024 | Article Id. IJCTT-V72I10P120 | DOI : https://doi.org/10.14445/22312803/IJCTT-V72I10P120

A Novel Approach to Incorporating LLMs in Mid-size Organizations for Customer Insight Generation Using Tree of Thoughts Methodology

Apurva Shrivastava, Aditya Patil, Alokita Garg, Amruta Hebli

Received Revised Accepted Published
06 Sep 2024 08 Oct 2024 22 Oct 2024 31 Oct 2024

Citation :

Apurva Shrivastava, 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 (IJCTT), 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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