Customer Care Service Research Articles

Customer Care Service Management is Moving Forward to Achieve Sustainable Customer Retention in Every Industry. Does it play a Role to Increase Brand Retention?

Customer Care Service Management is Moving Forward to Achieve Sustainable Customer Retention in Every Industry. Does it play a Role to Increase Brand Retention?

Managing value co-creation in consumer service systems within smart retail settings

The study proposes a holistic approach to consumer service systems and “collective intelligence” by investigating the Collective Knowledge Systems (CKSs) and the Social Semantic Web (SSW) platform as enablers for value co-creation. Our paper makes progress exploring on value co-creation within smart retail settings focusing on customer care service. A request management based on semantic web applications improves business processes, exchange relevant information with stakeholders spreading the collected intelligence at multiple levels (consumers, customer service, retailers). Modeling service systems as CKS allows retailers and customers to co-create value that is “semanticized” and exploited as an improvement of the service itself.

A Distinct Voice Descriptive Shopping Cart - Integrated with Gmap and Responsive Customer Care Service

E-commerce promotes economic process by facultative on-line retailers to vie at intervals a worldwide market state of affairs. These unit essential success factors that led to tell apart an honest business on the web and this information could allow reaching a vital competitive advantage for business property. As several disciplines area unit concerned, once determinative essential success factors, e-commerce needs an efficient co-ordination and integration in an exceedingly cooperative means. In e-commerce, still as in the other scheme, the breaking down of some desegregation parts could provoke a collapse on the total system. The varied stakeholders concerned in an exceedingly given business ought to, therefore, be concerned and work along to realize a prime quality product that totally satisfies the tip customer’s wants and desires. to fulfill the on top of demand, this paper proposes a multi-perspective essential success issues (MPCSF) model for on-line looking and it achieves accessibility and geo abstraction in style and usability factor.

Churn Forecasting Model for South African Pre-Paid Service Providers

Telecommunication companies globally confront with rising problems of customer agitations. Inadequacy of telecoms’ rendered services, delivered products and many other causes, result to the difficult moments telecoms face. These problems have further degenerated to customers leaving from one network provider to the other, in quest for improved satisfaction. Churn is the term used to describe this customers’ resultant movement, due to agitation caused by inadequate operations. The Republic of South Africa (RSA) telecoms presently face this social problem called churn. To understand what causes customer churn, deep studies on varied literature on customer churn revealed the reasons behind this movement, i.e. churn factors. A developed customer experience questionnaire from these studied factors identified the main churn causing factors in RSA telecoms. This questionnaire eased the obtaining of data-records from respondents in South Africa, used in creating varied datasets. Using the varied datasets, a Bayesian networks’ model developed detected and evaluated churn likelihood in these different telecoms. This model proved to have more predicting potentials and relevance in our present days. Three factors revealed to impact more on customer churn in South Africa, by way of the predictions carried out by the derived model. These factors are: Friends & Family Deals on Networks (FFD), Customer Care Service (CCS), and Offers & Promotions (OP).

WORKING OF ACONTEXT-AWARE CONVERSATIONAL ENTITY

Abstract — Introduction of new technologies in to the world is increasing rapidly and in order to assist the users to get equipped with such technologies industries are providing customer care services. Contacting a customer care service is subjective to several overheads of selecting options from a listed set, waiting for the switching between selections and awaiting the support of a customer care executive as the process usually requires a human intervention. Hence, a substitute for a personnel is required by the IT industries in order to automate the communication process in assisting the customers. Chatbots with context aware question-answering capabilities can be viewed as a good solution to such customer-care assistance. Development of a chatbot and the complexities involved in getting it to work effectively is delineated in this paper.

Development of Commuter Booking Software for Road Transport Company

Industry is an organization that had been in existence and Businesses within this industry have a much greater amount of exposure to the public than many other industries. About 80% of the nation people use this medium as a means of their transit, either goods from one place to the other. Besides it's widely used, it faces a lot of challenges, because most organizations in the business use manual approach of handling their Customers information. The research paper addresses this approach and it is achieved by providing an automated system for processing customer's information. Programming is performed using PHP Platform, and MySQL 4.1. Online Customer Care Service is created using wired and wireless LAN networks

Multiple topic identification in human/human conversations

The paper deals with the automatic analysis of real-life telephone conversations between an agent and a customer of a customer care service (ccs). The application domain is the public transportation system in Paris and the purpose is to collect statistics about customer problems in order to monitor the service and decide priorities on the intervention for improving user satisfaction.Of primary importance for the analysis is the detection of themes that are the object of customer problems. Themes are defined in the application requirements and are part of the application ontology that is implicit in the ccs documentation.Due to variety of customer population, the structure of conversations with an agent is unpredictable. A conversation may be about one or more themes. Theme mentions can be interleaved with mentions of facts that are irrelevant for the application purpose. Furthermore, in certain conversations theme mentions are localized in specific conversation segments while in other conversations mentions cannot be localized. As a consequence, approaches to feature extraction with and without mention localization are considered.Application domain relevant themes identified by an automatic procedure are expressed by specific sentences whose words are hypothesized by an automatic speech recognition (asr) system. The asr system is error prone. The word error rates can be very high for many reasons. Among them it is worth mentioning unpredictable background noise, speaker accent, and various types of speech disfluencies.As the application task requires the composition of proportions of theme mentions, a sequential decision strategy is introduced in this paper for performing a survey of the large amount of conversations made available in a given time period. The strategy has to sample the conversations to form a survey containing enough data analyzed with high accuracy so that proportions can be estimated with sufficient accuracy.Due to the unpredictable type of theme mentions, it is appropriate to consider methods for theme hypothesization based on global as well as local feature extraction. Two systems based on each type of feature extraction will be considered by the strategy. One of the four methods is novel. It is based on a new definition of density of theme mentions and on the localization of high density zones whose boundaries do not need to be precisely detected.The sequential decision strategy starts by grouping theme hypotheses into sets of different expected accuracy and coverage levels. For those sets for which accuracy can be improved with a consequent increase of coverage a new system with new features is introduced. Its execution is triggered only when specific preconditions are met on the hypotheses generated by the basic four systems.Experimental results are provided on a corpus collected in the call center of the Paris transportation system known as ratp. The results show that surveys with high accuracy and coverage can be composed with the proposed strategy and systems. This makes it possible to apply a previously published proportion estimation approach that takes into account hypothesization errors.

Automatic Speech Recognition in Mobile Customer Care Service

In the project an automatic speech system is used in mobile customer care services. In existing mobile customer care services, customer have to wait for 4 to 5 minutes to get into the option what they want to inquire. Based on the requirement, we go for filtering the incoming calls. Persons who require particular data are dynamically move to speech recognition system that identifies the type of the enquiry chosen. Speech recognition is the one which dynamically identifies the individual speaking based on analyzing the speech waves. It helps in identifying the voice of the speaker to know the recognized user. It also helps in accessing services like telephone banking, mobile shopping, database services and securing the information which is confidential.

Organ and Tissue Donation in Migrants: Advanced Course for Cross-Cultural Mediators

Between 2004 and 2010 in Piedmont (Italy Northern Region) 1556 brain-death situations were reported, including 113 (7.3%) in migrants as potential organ and tissue donors. The health staff often has to face migrants, who show great cultural differences and language difficulties. The Molinette Hospital Customer Care Service, the Piedmont Regional Tissue and Organ Procurement Coordination Agency (RPC), and the Cross-Cultural Mediators Association (CMA) organized a special course for intercultural mediators, to decrease misunderstandings between the health staff and the migrants' families and to improve professional communication. In 2011, 28 cultural-linguistic mediators representing different groups of migrants in Piemonte took part in a specific course. Over a 5 month period they were informed about emotional and communicative aspects, proper to the moment of death, as well as organ donation as an intercultural field, the professional role of the mediator, the clinical and forensic aspects of brain death and donation, and the psychological aspects of organ donation. The course was organized by cultural-linguistic mediators of the CMA, the staff of the RPC and the teachers at Turin University. The list of the 21 mediators who passed the final exam was given to organ and tissue donation hospital co-ordinators in Piedmont, so that if necessary, they could obtain the cooperation of these qualified people.

Detection and Interpretation of Opinion Expressions in Spoken Surveys

This paper describes a system for automatic opinion analysis from spoken messages collected in the context of a user satisfaction survey. Opinion analysis is performed from the perspective of opinion monitoring. A process is outlined for detecting segments expressing opinions in a speech signal. Methods are proposed for accepting or rejecting segments from messages that are not reliably analyzed due to the limitations of automatic speech recognition processes, for assigning opinion hypotheses to segments and for evaluating hypothesis opinion proportions. Specific language models are introduced for representing opinion concepts. These models are used for hypothesizing opinion carrying segments in a spoken message. Each segment is interpreted by a classifier based on the Adaboost algorithm which associates a pair of topic and polarity labels to each segment. The different processes are trained and evaluated on a telephone corpus collected in a deployed customer care service. The use of conditional random fields (CRFs) is also considered for detecting segments and results are compared for different types of data and approaches. By optimizing the choice of the strategy parameters, it is possible to estimate user opinion proportions with a Kullback-Leibler divergence of 0.047 bits with respect to the true proportions obtained with a manual annotation of the spoken messages. The proportions estimated with such a low divergence are accurate enough for monitoring user satisfaction over time.

Methodology for customer relationship management

Customer relationship management (CRM) is a customer-focused business strategy that dynamically integrates sales, marketing and customer care service in order to create and add value for the company and its customers.This change towards a customer-focused strategy is leading to a strong demand for CRM solutions by companies. However, in spite of companies’ interest in this new management model, many CRM implementations fail. One of the main reasons for this lack of success is that the existing methodologies being used to approach a CRM project are not adequate, since they do not satisfactorily integrate and complement the strategic and technological aspects of CRM.This paper describes a formal methodology for directing the process of developing and implementing a CRM System that considers and integrates various aspects, such as defining a customer strategy, re-engineering customer-oriented business processes, human resources management, the computer system, management of change and continuous improvement.