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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Growth in the Age of the Customer : A Comparative Case Study on Leveraging Emotion, Engagement and Loyalty

Kindblom, Helena, Renström, Victoria January 2018 (has links)
With the significant shifts and upheaval in the marketplace due to digitalisation, and evolving customer behaviour, it is becoming increasingly imperative for businesses to build and maintain strong connections with their customers. This new business setting causes major implications for companies’ formulation of strategies. Therefore, this thesis aims to map out points-of-parity and points-of-difference with regards to how two companies leverage customer emotion, customer engagement and customer loyalty in order to achieve growth, which is defined as the stages of customer acquisition, customer development and customer retention. In addition, the purpose is to explore advocacy and its role for igniting further growth. The study is conducted in the form of a comparative case study of two digital B2C companies: the media company Freeda and the food delivery service Deliveroo. The Framework for Customer Growth and the Cycle of Advocacy-Ignited Growth guide the analysis. The main findings include that companies’ core propositions determine their emotional strategy as well as personalisation being considered the most significant aspect of customer engagement. Moreover, the role of advocacy can be taken on by various stakeholders and is not limited solely to customers.
2

Människan och chattboten : En kvalitativ studie om hur människors känslor och upplevelser påverkas vid kundtjänstinteraktion med chattbotar

Mauritzson, Amanda, Andersson, Alicia January 2022 (has links)
Emotion AI är ett forskningsområde som syftar till att teknik ska kunna känna igen och reagera på mänskliga känslotillstånd, vilket kan implementeras i form av chattbotar. Chattbotens roll är idag framträdande inom kundtjänstområdet och används för att stärka kundservice. Tidigare forskning visar att det råder brist av kvalitativa studier om hur chattbotar responderar på och hanterar känslor som uppstår när människor interagerar med chattbotar i vardagen. Syftet med studien är därav att skapa förståelse för hur känslor hanteras av chattbotar och vilka upplevelser som genereras vid kundtjänstinteraktion mellan människa och chattbot.  Studien antog en kvalitativ ansats och inleddes genom en förstudie som identifierade fyra chattbotar, vilka användes vidare till intervjustudien. Datainsamlingen har genomförts med hjälp av semistrukturerade intervjuer och kompletterades med observation. Analysen identifierade fyra typer av upplevelser av chattbotarnas förmåga att respondera på känslointeraktion: bekräftelse, missförstånd, problemlösning och ideal chattbot. Studien diskuterar hur chattbotar påverkar människans känsloupplevelse och hur chattbotar bör designas i kundtjänstinteraktion. Slutsatsen är att det inte finns behov att utveckla chattbotar med väldigt komplex känsloförmåga och känslomässig förståelse har visats vara sekundärt i kundtjänstinteraktion. Dock bör chattbotar designas med en enklare form av känslomässig förmåga eftersom det kan skapa mervärde genom att kunderna känner sig förstådda. / Emotion AI is a research area aimed at technology recognizing and reacting to human emotions, which can be implemented in the form of chatbots. The chatbot's role is today prominent in the field of customer service and is used to strengthen customer service. Previous research shows that there is a lack of qualitative studies on how chatbots respond to and manage emotions that arise when people interact with chatbots in their everyday life. The purpose of the study is therefore to create an understanding of how emotions are handled by chatbots and what experiences are generated during customer service interaction between humans and chatbots.  The study adopted a qualitative approach and was initiated through a feasibility study that identified four chatbots, which were used for the interview study. The data collection was carried out using semi-structured interviews and supplemented by observation. The analysis identified four types of experiences of chatbots' ability to respond to emotional interaction: affirmation, misunderstanding, problem-solving, and ideal chatbot. The study discusses how chatbots affect the human emotional experience and how chatbots should be designed for customer service interaction. The bottom line is that there is no need to develop chatbots with very complex emotional abilities and emotional understanding has been shown to be secondary in the customer service interaction. However, chatbots should be designed with a simpler form of emotional ability as it can create added value in the form of making customers feel understood.

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