• Title/Summary/Keyword: VOC(Voice Of Customer)

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Intelligent VOC Analyzing System Using Opinion Mining (오피니언 마이닝을 이용한 지능형 VOC 분석시스템)

  • Kim, Yoosin;Jeong, Seung Ryul
    • Journal of Intelligence and Information Systems
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    • v.19 no.3
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    • pp.113-125
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    • 2013
  • Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.

VOC Summarization and Classification based on Sentence Understanding (구문 의미 이해 기반의 VOC 요약 및 분류)

  • Kim, Moonjong;Lee, Jaean;Han, Kyouyeol;Ahn, Youngmin
    • KIISE Transactions on Computing Practices
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    • v.22 no.1
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    • pp.50-55
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    • 2016
  • To attain an understanding of customers' opinions or demands regarding a companies' products or service, it is important to consider VOC (Voice of Customer) data; however, it is difficult to understand contexts from VOC because segmented and duplicate sentences and a variety of dialog contexts. In this article, POS (part of speech) and morphemes were selected as language resources due to their semantic importance regarding documents, and based on these, we defined an LSP (Lexico-Semantic-Pattern) to understand the structure and semantics of the sentences and extracted summary by key sentences; furthermore the LSP was introduced to connect the segmented sentences and remove any contextual repetition. We also defined the LSP by categories and classified the documents based on those categories that comprise the main sentences matched by LSP. In the experiment, we classified the VOC-data documents for the creation of a summarization before comparing the result with the previous methodologies.

CTQ derived using the new Module device convergence and QFD can be mounted on the dominance Products : Focusing on the sparkling water purifier Case (시장지배제품에 장착 가능한 새로운 Module장치 융합 및 QFD를 활용한 CTQ 도출 : 탄산수 정수기 사례를 중심으로)

  • Song, In-Cheol;Hwang, Dong-Ryong;Lee, Seung-Hee
    • Journal of Digital Convergence
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    • v.13 no.5
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    • pp.195-204
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    • 2015
  • This paper CTQ(Critical to Quality) to draw, aim to derive a key quality factor reflects the customer's requirements by utilizing the QFD technique for sparkling water purifier device that combines the new module. Tasting participants, consumers and New Module device intended for developers who develop and conduct a survey and FGI (Focus Group Interview) VOC(Voice of Customer) to draw, drawn by the EC through the developer VOC and EC (Engineering Characteristic) and charts the relationship between the phases was prepared HOQ(House of Quality). Sparkling water purifier through the HOQ chart certain taste, sound, running water, CO2 cylinder replacement cycle, we obtain results that element is an important quality factors such as ease of use. These factors are closely related to each component regulators and Module device (mixing) associated with the taste of water, booster pumps, and deliver results that the solenoid is considered the most critical part.

A Study on Product Quality Characteristics Based on VOC Analysis (VOC 분석에 기반 한 제품품질특성에 관한 연구)

  • Lee, Keun-Woo;Lee, Jae-Kwang
    • Proceedings of the Safety Management and Science Conference
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    • 2010.04a
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    • pp.303-313
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    • 2010
  • 본 연구는 음식물처리기 제품품질을 구성하는 차원 및 속성을 VOC(voice of customer)분석을 통해서 도출하고 소비자의 특성에 따라 음식물 처리기 제품품질 속성의 중요도 차이에 대한 분석과 고객만족에 영향을 미치는 품질속성에 대하여 분석하였다. 그 결과 소비자의 특성에 따라 음식물 처리기 제품품질 속성의 중요도의 차이와 고객만족에 영향을 미치는 품질속성을 도출하였으며, 본 연구 결과는 향후 음식물 처리기 제품개발에 고객의 니즈를 반영하는데 도움이 될 것으로 기대된다.

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Development of An Ergonomic Product Development Process Reflecting Quantified Customer Preference (정량화된 고객 선호도를 체계적으로 반영하기 위한 인간공학적 제품 개발 프로세스)

  • Im, YoungJae;Jung, Eui S.;Park, SungJoon
    • Journal of Korean Institute of Industrial Engineers
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    • v.34 no.1
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    • pp.66-78
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    • 2008
  • In the past, Manufacturers used to determine the quality of products, but the trend of today's market becomesmore into customer-driven. As a result, demands from customers are becoming more diverse and complicated,and most companies are obligated to meet their needs. As one of the effort to achieve their satisfaction,companies are now emphasizing activities to find out what customers specifically want and extract voice ofcustomer(VOC). This study attempts to develop an ergonomic product development process as a method tomaximally reflect the VOC. In order to meet this goal, ergonomic design guidelines, which are possible to beclassified according that user's human characteristics, will be recommended. Even now, there are numerousdesign guidelines already existing in the ergonomics literature. However, it is not realistically feasible to reviewall of those guidelines, and some of them are even conflicting with each other. Therefore, in this paper, theproduct development process, which prioritizes the human characteristics that reflect customer needs and appliesthe design guidelines that meet the most important ones, will be suggested. Finally, the research was described toshow the validity of the product development process through an example of a mobile phone development case.

A Case Study on the Analysis of Travel Agencies' Internal VOC Data (여행사 내부 VOC 데이터 분석 사례 연구)

  • Kang, Minshik;Kong, Hyousoon;Song, Eunjee
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.861-863
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    • 2016
  • 대부분의 기업은 경영전략을 결정하는데 고객의 소리(VOC:Voice of Customer)를 매우 중요한 정보로 사용하고 있기 때문에 기업들은 다양한 방법으로 고객과의 관계증진을 위해 VOC 데이터를 이용하고 있다. 그러나 수집된 내부VOC 데이터에서 많은 정성적인 데이터를 포함하고 있으므로 분석하는 데는 한계가 있다. 본 논문에서는 최근 소셜 빅 데이터를 분석하는데 사용하고 있는 시스템을 이용하여 다른 업종에 비해 고객이 다양하고 서비스가 매우 중요한 여행사 내부 VOC를 분석한다. 적용 사례로서 국내 대표적인 여행사에 직접 적용하여 분석한 결과를 제시한다. 본 연구 결과 빅 데이터 분석 도구를 다른 서비스업종의 내부 VOC의 정성적인 데이터를 분석하는데 활용할 수 있는 가능성을 보여주었다고 사료된다.

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Transition of Service Paradigm from Service Recovery to Proactive Service (사후 서비스에서 선제적 서비스로 서비스 패러다임의 전환)

  • Rhee, Hyunjung;Kim, Hyangmi;Rhee, Chang Seop
    • The Journal of the Korea Contents Association
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    • v.20 no.4
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    • pp.396-405
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    • 2020
  • In this study, we used the big data of Voice of Customer (VOC) related to high-speed Internet products to look at the causes of perceived quality and the possibility of proactive service. In order to verify the possibility of proactive service, we collected VOC data from 13 facilities and equipment of a mobile communication service company, and then conducted 𝒙2 test to verify that there was a statistically significant difference between the actual VOC observation values and expected values. We found statistical evidence that proactive service is possible through real-time monitoring for the six disability alarms among the 13 facilities and equipment, which are FTTH-R Equipment ON/OFF, FTTH-EV Line Error Detection, Port Faulty, FTTH-R Line Error Detection, Network Loop Detection, and Abnormal Limiting Traffic. Companies are able to adopt the proactive service to improve their market share and to reduce customer service costs. The results of this study are expected to contribute to the actual application of industry in that it has diagnosed the possibility of proactive service in the telecommunication service sector and further suggested suggestions on how to provide effective proactive service.

The Impact of Transforming Unstructured Data into Structured Data on a Churn Prediction Model for Loan Customers

  • Jung, Hoon;Lee, Bong Gyou
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.12
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    • pp.4706-4724
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    • 2020
  • With various structured data, such as the company size, loan balance, and savings accounts, the voice of customer (VOC), which is text data containing contact history and counseling details was analyzed in this study. To analyze unstructured data, the term frequency-inverse document frequency (TF-IDF) analysis, semantic network analysis, sentiment analysis, and a convolutional neural network (CNN) were implemented. A performance comparison of the models revealed that the predictive model using the CNN provided the best performance with regard to predictive power, followed by the model using the TF-IDF, and then the model using semantic network analysis. In particular, a character-level CNN and a word-level CNN were developed separately, and the character-level CNN exhibited better performance, according to an analysis for the Korean language. Moreover, a systematic selection model for optimal text mining techniques was proposed, suggesting which analytical technique is appropriate for analyzing text data depending on the context. This study also provides evidence that the results of previous studies, indicating that individual customers leave when their loyalty and switching cost are low, are also applicable to corporate customers and suggests that VOC data indicating customers' needs are very effective for predicting their behavior.

Reliability Analysis of VOC Data for Opinion Mining (오피니언 마이닝을 위한 VOC 데이타의 신뢰성 분석)

  • Kim, Dongwon;Yu, Song Jin
    • Journal of Intelligence and Information Systems
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    • v.22 no.4
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    • pp.217-245
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    • 2016
  • The purpose of this study is to verify how 7 sentiment domains extracted through sentiment analysis from social media have an influence on business performance. It consists of three phases. In phase I, we constructed the sentiment lexicon after crawling 45,447 pieces of VOC (Voice of the Customer) on 26 auto companies from the car community and extracting the POS information and built a seven-sensitive domains. In phase II, in order to retain the reliability of experimental data, we examined auto-correlation analysis and PCA. In phase III, we investigated how 7 domains impact on the market share of three major (GM, FCA, and VOLKSWAGEN) auto companies by using linear regression analysis. The findings from the auto-correlation analysis proved auto-correlation and the sequence of the sentiments, and the results from PCA reported the 7 sentiments connected with positivity, negativity and neutrality. As a result of linear regression analysis on model 1, we indentified that the sentimental factors have a significant influence on the actual market share. In particular, not only posotive and negative sentiment domains, but neutral sentiment had significantly impacted on auto market share. As we apply the availability of data to the market, and take advantage of auto-correlation of the market-related information and the sentiment, the findings will be a huge contribution to other researches on sentiment analysis as well as actual business performances in various ways.

Design for ILS in Ammunition Development applying QFD Method (QFD를 활용한 탄약 ILS 효율화 방안 연구)

  • Lee, Seung-Mok;Park, Young-Won
    • Journal of the Korean Society of Systems Engineering
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    • v.5 no.2
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    • pp.1-9
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    • 2009
  • This paper proposes an effective method on the DFILS(Design for Integrated Logistics Support) in ammunition development applying QFD(Quality Function Deployment) method. The goal of this research is to define the Design for ILS approach at the start of the ammunition development and to yield a set of reusable requirements. Based on 000mm High-Explosive(Warship ammunition) development work, a QFD software tool, CUPID, was used to analyze and define the field force's requirements. Additionally, a set of reusable requirements are identified and defined for use during the Design for ILS development phase in the next-generation ammunition development process. These set of requirements that consider both the priority and importance of the VOC(Voice of Customer) will contribute to the early phase of the ammunition development to implement the Design for ILS specialty engineering effort.

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