Designing and implementing a system that suggests managers about pricing based on customer value with topic modeling techniques and text mining

in today's competitive world, pricing, as one of the 4 elements of marketing mix, plays a key role in the success or failure of companies. Based on theoretical principles, in value-based pricing, companies calculate the distinct value of their products from customer insights. The purpose of this research, which is based on design science, is to design and implement a system to help competitive pricing based on customer value by categorizing and analyzing customer emotions with the aim of maximizing profits. choice of this research is The hoteling industry , in which customer opinions and values play key rule. In this research, first, it has been tried to identify and classify important and valuable items in the minds of the customers of these 5-star hotels in Tehran by the method of topic modeling with LDA algorithm. Then, in each category, each customer's comments are tagged, and these comments processed with different text mining algorithms. Then the accuracy of the algorithms calculated. the deep learning algorithm with 0.9 accuracy had the highest accuracy of calculations. Finally, the analysis of sentiments with the available data was performed by the system designed in the previous step and acceptable results were obtained. The application of the proposed system is to identify the value of hotels in the minds of target customers over competitors and to help value-based pricing.