Customer Experience Management – How to Improve the Customer Experience Management and its Measurement

The main goal of this master’s thesis was to find out, how to improve customer experience management and measurement. This study is a qualitative case study, in which the data collection method has been interviews. In addition, some of the company’s customer experience measurement methods have been analyzed. The theoretical background is applied in practice by interviewing 5 representatives from the case company. In the case company, the management has launched a customer experience focused program, and given guidelines for customer experience improvement. In the case company, customer experience is measured with different methods, one example is asking the recommendation readiness from a customer. In order to improve the customer experience management, the case company should define, what the company means with customer experience and what kind of customer experience the company is aiming to create. After the encounter, the customer should be left with feelings of satisfaction, positivity and trust. The company should focus on easiness in its processes, on top of which the processes should work fluently. The customer experience management should be improved through systematic planning, and by combining and standardizing different measures. In addition, some channel-based measures should be used. The measurement conducted should be more customer focused, and the case company should form an understanding, which touch points are the most relevant to measure.

Customer relationship management (CRM ) : Administración de las relaciones con el cliente

Tesina (Maestro en Informática Administrativa) U.A.N.L.

Das Kontextmarketing im mobilen Customer Relationship Management

Zusammenfassung Mobile Telekommunikationstechnologien verändern den Alltag, ihre Benutzer und die Geschäftswelt. Im Zuge der Mobilität haben die Nutzer von mobilen Übertragungstechnologien ein hohes Kommunikationsbedürfnis in jeglicher Situation entwickelt: Sie wollen überall und jederzeit kommunizieren und informiert sein. Dies ist auch darauf zurückzuführen, dass ein Wandel der Individualisierung – von der Person zur Situation – stattgefunden hat. Im Rahmen der Untersuchung gehen wir auf diese entscheidenden Veränderung ein und analysieren die Potenziale des Kontextmarketing im mobilen Customer Relationship Management anhand der Erringung von Wettbewerbsvorteilen durch Situationsfaktoren. Daneben zeigen wir mögliche Geschäftsmodelle und Wertschöpfungsketten auf. Abgerundet wird die Arbeit durch die Darstellung möglicher personenbezogener, technischer und rechtlicher Restriktionen.

Interoperability for eLearning Service Management and Provision

Learning Objects offer flexibility and adaptability for users to request personalised information for learning. There are standards to guide the development of learning objects. However, individual developers may customise these standards for serving different purposes when defining, describing, managing and providing learning objects, which are normally stored in heterogeneous repositories. Barriers to interoperability hinder sharing of learning services and subsequently affect quality of instructional design as learners expect to be able to receive their personalised learning content. All these impose difficulties to the users in getting the right information from the right sources. This paper investigates the interoperability issues in eLearning services management and provision and presents an approach to resolve interoperability at three levels.

Adapted customer relationship management implementation framework:facilitating value creation in nursing homes

This paper proposes a framework to support Customer Relationship Management (CRM) implementation in nursing homes. The work extends research by Cheng et al. (2005) who conducted in-depth questionnaires to identify critical features (termed value-characteristics), which are areas identified as adding the most value if implemented. Although Cheng et al. did proposed an implementation framework, summary of, and inconsistent inclusion of value-characteristics, limits the practical use of this contribution during implementation. In this paper we adapt the original framework to correct perceived deficiencies. We link the value characteristics to operational, analytical, strategic and/or collaborative CRM solution types, to allow consideration in context of practical implementation solutions. The outcome of this paper shows that, practically, a 'one solution meets all characteristic' approach to CRM implementation within nursing homes is inappropriate. Our framework, however, supports implementers in identifying how value can be gained when implementing a specific CRM solution within nursing homes; which subsequently support project management and expectation management.

Towards developing a customer relationship management (CRM) strategy for supporting pre-implementation activities in business

Effectively preparing and planning for Customer Relationship Management (CRM) strategy is critical to CRM implementation success. A lack of a common and systematic way to implement CRM means that focus must be placed on the pre-implementation stage to ensure chance of success. Although existing CRM implementation approaches evidence the need to concentrate mostly on the pre-implementation stage, they fail to address some key issues, which raises the need for a generic framework that address CRM strategy analysis. This paper proposes a framework to support effective CRM pre-implementation strategy development.

Customer retention management in the recession

The purpose of this article is to explore customer retention strategies and tactics implemented by firms in recession. Our investigations show just how big a challenge many organizations face in their ability to manage customer retention effectively. While leading organizations have embedded real-time customer life cycle management, developed accurate early warning systems, price elasticity models and ‘deal calculators’, the organizations we spoke to have only gone as far as calculating the value at risk and building simple predictive models.