Pulmuone Uses AI to Monitor Customer Reactions... Develops In-House Customer Experience Analysis Platform

Pulmuone employees are analyzing customer response data using the 'VOC·Review Analysis System' to hold new product development meetings. Photo by Pulmuone

[Asia Economy Reporter Song Seung-yoon] Pulmuone announced on the 4th that it has developed a 'VOC (Voice of Customer)·Review Analysis System' that precisely analyzes customer experience data and will utilize it in the product development process to enhance customer satisfaction.

The system developed by Pulmuone scientifically and systematically analyzes customer experience data generated during the online purchase process using AI (Artificial Intelligence) technology to derive meaningful conclusions. Pulmuone has been enhancing its data-driven customer experience management capabilities by utilizing this system in beta version for product analysis of some key products. Subsequently, through its proprietary technology, it has advanced the data analysis techniques and expanded the applicable product range to officially launch the system.

The system incorporates advanced proprietary technologies such as data analysis, AI, and NLP (Natural Language Processing). Pulmuone plans to use this analysis system for analyzing customer reviews and selecting the best reviews within its own online store, Shop Pulmuone.

Customer response data, analyzed systematically and scientifically through this system, is also linked to product improvement and development processes. Consumer product review posts are classified into 32 attributes specialized for the food industry by the VOC·Review Analysis System, enabling a more objective understanding of product strengths and weaknesses. Team members can view customer response data at a glance through the dashboard within the system. Pulmuone plans to quickly and accurately recognize points for improvement requested by many customers to improve products and actively reflect these in new product development.

It also becomes possible to analyze trends of F&B products sold on e-commerce platforms and explore optimal pricing for its own products. The system automatically monitors prices of products distributed online to identify the optimal product price for enhancing customer satisfaction. By integrating machine learning technology, it can even predict future demand.

A Pulmuone official said, "With the rapid increase in non-face-to-face grocery shopping over the past 2-3 years, effectively measuring customer responses online has become important, leading to the establishment of a data-driven customer response analysis system." He added, "Going forward, we will accelerate digital transformation (DX) across all business areas by introducing various digital services, including systems that analyze consumer data."

This content was produced with the assistance of AI translation services.