Combining machine learning and Service Design to improve customer experience

Niko Reunanen, Zeynep Falay von Flittner, Virpi Roto, Kirsikka Vaajakallio

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

Abstrakti

Service design is an effective approach for service-based businesses to improve customer experience. However, Double Diamond design process has limitations in identifying the development areas with most business impact. Combining service design process with machine learning presents a new opportunity for alleviating the aforementioned limitation. We present a case from a European service design agency and a Nordic life insurance company to describe the utilization of machine learning in the beginning of the service design process. With this new process we were able to quantify business impact of different customer experience factors and focus the design effort towards the most potential area. Additionally, we increased the buy-in from top management by enhancing the credibility of the qualitative approach with numeric evidence of customer experience data. The work resulted in increased Net Promoter Score for the client organization.
AlkuperäiskieliEnglanti
OtsikkoServDes.2020 Tensions, Paradoxes, Plurality
AlaotsikkoConference Proceedings
JulkaisupaikkaMelbourne
Sivumäärä10
TilaJulkaistu - joulukuuta 2020
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaService Design and Service Innovation Conference - RMIT University & online, Melbourne, Austraalia
Kesto: 2 helmikuuta 20215 helmikuuta 2021
https://servdes2020.org/

Conference

ConferenceService Design and Service Innovation Conference
LyhennettäServDes
MaaAustraalia
KaupunkiMelbourne
Ajanjakso02/02/202105/02/2021
www-osoite

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