Mining customer satisfaction on b2b online platforms using service quality and web usage metrics
Paper in proceeding, 2020

In order to distinguish themselves from their competitors, software service providers constantly try to assess and improve customer satisfaction. However, measuring customer satisfaction in a continuous way is often time and cost intensive, or requires effort on the customer side. Especially in B2B contexts, a continuous assessment of customer satisfaction is difficult to achieve due to potential restrictions and complex provider-customer-end user setups. While concepts such as web usage mining enable software providers to get a deep understanding of how their products are used, its application to quantitatively measure customer satisfaction has not yet been studied in greater detail. For that reason, our study aims at combining existing knowledge on customer satisfaction, web usage mining, and B2B service characteristics to derive a model that enables an automated calculation of quantitative customer satisfaction scores. We apply web usage mining to validate these scores and to compare the usage behavior of satisfied and dissatisfied customers. This approach is based on domain-specific service quality and web usage metrics and is, therefore, suitable for continuous measurements without requiring active customer participation. The applicability of the model is validated by instantiating it in a real-world B2B online platform.

b2b

data analytics

customer satisfaction

web usage mining

Author

Iris Figalist

Siemens

Marco Dieffenbacher

University of Erlangen-Nuremberg (FAU)

Isabella Eigner

University of Erlangen-Nuremberg (FAU)

Jan Bosch

Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers), Software Engineering for Testing, Requirements, Innovation and Psychology

Helena Holmström Olsson

Malmö university

Christoph Elsner

Siemens

Proceedings - Asia-Pacific Software Engineering Conference, APSEC

15301362 (ISSN)

Vol. 2020-December 435-444 9359262

27th Asia-Pacific Software Engineering Conference
Singapore, Singapore,

Subject Categories

Other Engineering and Technologies not elsewhere specified

Software Engineering

Computer Systems

DOI

10.1109/APSEC51365.2020.00052

More information

Latest update

3/26/2021