Methodological foundations of a universal approach to business communication language analytics based on large language models

The article substantiates the feasibility of using large language models (LLMs) as a fundamentally new tool in business-oriented language analytics tasks. Unlike traditional rule-based approaches and dictionary methods, which are characterized by low flexibility and limited ability for contextual interpretation, as well as classical machine learning algorithms that require large volumes of labeled data and quickly lose relevance in a dynamic business environment, LLMs provide comprehensive multiparametric analysis of communications. Their scientific novelty lies in the ability to integrate semantic, contextual, and emotional dimensions of interaction, while also taking into account industry-specific features without the need to develop narrowly specialized models. The study systematizes applied tasks of language analytics implemented through LLMs, including automatic dialogue summarization, script compliance control, intent identification, thematic tagging, sentiment analysis, lead qualification, upselling and cross-selling opportunity detection, handling of interrupted communications, and customer satisfaction analysis. For each task, universal prompts with dynamic parameters are proposed, enabling adaptation of instructions to the specifics of individual business domains. Particular emphasis is placed on three sectors with critical dependence on language analytics — automotive dealerships, healthcare institutions, and banking services. This approach makes it possible to combine the standardization of analytical procedures with domain-specific detailing for each industry. The practical value of the study lies in the development of a unified methodological framework for integrating LLM-based language analytics into CRM systems, quality control modules, management dashboards, and regulatory reporting. The use of dynamic parameters ensures both universality and scalability of the approach, opening prospects for its application in a wider range of business areas where client communication is a key factor in ensuring unit economics efficiency and enhancing enterprise competitiveness.

Zhukovskyi, Dmytro

цифрова економіка

Національний університет "Полтавська політехніка імені Юрія Кондратюка"

info:eu-repo/semantics/article

application/pdf

https://journals.nupp.edu.ua/eir/article/view/3919

Economics and region; No. 3(98) (2025): Economics and region; 208-215

uk

https://journals.nupp.edu.ua/eir/article/view/3919/3270

http://creativecommons.org/licenses/by-nc/4.0