Towards a Mobile Technical Customer Service Support Platform

Author(s):  
Michael Fellmann ◽  
Deniz Özcan ◽  
Michel Matijacic ◽  
Gerald Däuble ◽  
Michael Schlicker ◽  
...  
2014 ◽  
Vol 687-691 ◽  
pp. 4840-4843
Author(s):  
Huan Zhao ◽  
Qiu Hong Wu

In the era of the Internet as the core of globalization the interaction of enterprises, enterprises are faced with a series of thorny issues about how to make social relations resources into corporate sales and development resources. In the past Management strategy is from product-centric to customer-centric. If the companies want to survival and development, we must establish a good relationship with closely customers. By a good corporate credit, high quality products, quality service, to attract new and old customers to standardize the management, warm and caring, and efficient services to support management to maintain the loyalty of the old and new customers. In the Internet environment CRM is an important part of the customer service support management. Online customer service support for management information systems will be enterprise customer-facing portal. A comprehensive customer service support management information system can enhance the competitiveness of enterprises, increase sales, enhance corporate image. Customer service support management is to ensure customer satisfaction and customer interests. How to give full play to the advantage of customer service in the Internet environment to support management information system. And how to enhance customer service in the Internet environment to support the management interface of the customer satisfaction, improve the enterprise's customer retention will become an issue of concern. In the above context, customer service support management information system came into being. The system is provide feedback record inquiries and task allocation to provide customers with more personalized service to help companies achieve customer intelligence decision analysis.


2011 ◽  
pp. 571-590
Author(s):  
Quan Thanh Tho ◽  
Hui Siu Cheung ◽  
A. C.M. Fong

This chapter discusses Semantic Web support for customer services. Customer service support is an important operation for most multinational manufacturing companies. It provides installation, inspection, and maintenance support for their worldwide customers. However, knowledge integrated in customer service support systems is typically closed in terms of exchanging information. Therefore, the systems do not easily share, reuse, or exchange knowledge. It causes difficulty when customers seek service support for products produced by various companies. In this chapter, we propose to incorporate Semantic Web services into customer service systems to solve such problems. In our system, KSOM neural network is first used to mine knowledge from reported cases. Then, ontology is used as a semantic representation for knowledge discovered and Semantic Web services are used to make constructed ontology accessible from different systems. As a result, users can use semantic knowledge distributed across various sources on the Internet to solve their problems. Performance evaluation on the system is also present in the chapter.


2000 ◽  
Vol 38 (1) ◽  
pp. 1-13 ◽  
Author(s):  
S.C. Hui ◽  
G. Jha

Author(s):  
Quan Thanh Tho ◽  
Hui Siu Cheung ◽  
A. C.M. Fong

This chapter discusses Semantic Web support for customer services. Customer service support is an important operation for most multinational manufacturing companies. It provides installation, inspection, and maintenance support for their worldwide customers. However, knowledge integrated in customer service support systems is typically closed in terms of exchanging information. Therefore, the systems do not easily share, reuse, or exchange knowledge. It causes difficulty when customers seek service support for products produced by various companies. In this chapter, we propose to incorporate Semantic Web services into customer service systems to solve such problems. In our system, KSOM neural network is first used to mine knowledge from reported cases. Then, ontology is used as a semantic representation for knowledge discovered and Semantic Web services are used to make constructed ontology accessible from different systems. As a result, users can use semantic knowledge distributed across various sources on the Internet to solve their problems. Performance evaluation on the system is also present in the chapter.


2021 ◽  
Author(s):  
Margherita Mori

This chapter aims at providing a framework for analysis on evolutionary trends in finance that have to do with technological progress and especially with artificial intelligence (AI) applications. The starting point can be identified with a survey on how they have modified the business areas involving banking and financial services and on what can be expected – in terms of future strategic shifts and behavioral changes – on both the supply and the demand sides. The next step revolves around a wider and deeper investigation on the role that virtual assistants have started to – and are likely to further – play in the areas under scrutiny: special attention is requested upon the provision of enhanced customer service support, including conversational AI and sound branding; implications encompass developments that are on the cards, based upon digitalization as a must – not just an option – as shown by the Covid-19 pandemic. Conclusions allow to emphasize the significance, advancing features and value of this conceptual paper, as it leads to sort out best practices and success stories that are worth disseminating and replicating to benefit not only individuals and enterprises having direct interest in them, but society as a whole.


2011 ◽  
Vol 12 (4) ◽  
pp. 70 ◽  
Author(s):  
Jes S. Boronico ◽  
Andre Zirkler ◽  
Philip H. Siegel

<span>Rapidly increasing computer systems complexity has caused many companies to increase awareness of customer services. Many firms in the computer hardware and/or software industries have devoted increased effort towards customer service through the development of help desk support systems. Help desk support systems development currently face a number of problems, including escalating growth in customer usage, high staff turn-over, maintaining service quality and controlling costs. Industry has responded by providing additional staff training, increasing systems automation, and introducing knowledge based tools. These actions have increased help desk efficiency, but fail to provide a quantitative means for optimizing help desk operations. This paper addresses this problem through the development of a mathematical model which minimizes expected help desk costs by considering both operational costs and social costs. This model provides a basic framework through which policy makers may analyze the effectiveness of capacity decisions as they apply to help desk support systems in a multi-echelon, networked service station.</span>


2021 ◽  
pp. 100016
Author(s):  
Sandeep Dwarkanath Pande ◽  
Pramod Pandurang Jadhav ◽  
Rahul Joshi ◽  
Amol Dattatray Sawant ◽  
Vaibhav Muddebihalkar ◽  
...  

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