Details
| Original language | English |
|---|---|
| Title of host publication | AMCIS 2019 Proceedings. 21. |
| Subtitle of host publication | ADOPTION AND DIFFUSION OF INFORMATION TECHNOLOGY (SIGADIT) |
| Publication status | Published - 2019 |
| Event | 25th Americas Conference on Information Systems, AMCIS 2019 - Cancun, Mexico Duration: 15 Aug 2019 → 17 Aug 2019 |
Abstract
Web Analytics (WA) tools offer an increasing amount of analysis options. This amount of possible data overwhelm business users who are not familiar with WA and therefore the potential of WA is not fully exploited. We address this demand of individual information needs with the development of an indicator selection process. By using participatory design methods future users from different business units are involved in order to adopt WA into their workspace through building individual WA reports. The developed iterative model consists of five main steps. After the presentation of the developed model, we demonstrate the applicability in a case study at an industrial company. The case study shows a greater adoption by the different users, as the dashboards are individually tailored to them.
Keywords
- Individual technology Adoption, Participatory design, Web analytics key performance indicators, Web traffic report development
ASJC Scopus subject areas
- Computer Science(all)
- Information Systems
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AMCIS 2019 Proceedings. 21.: ADOPTION AND DIFFUSION OF INFORMATION TECHNOLOGY (SIGADIT). 2019.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Using web analytics data
T2 - 25th Americas Conference on Information Systems, AMCIS 2019
AU - Janssen, Antje
AU - Passlick, Jens
AU - Breitner, Michael H.
N1 - Publisher Copyright: © 2019 Association for Information Systems. All rights reserved. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2019
Y1 - 2019
N2 - Web Analytics (WA) tools offer an increasing amount of analysis options. This amount of possible data overwhelm business users who are not familiar with WA and therefore the potential of WA is not fully exploited. We address this demand of individual information needs with the development of an indicator selection process. By using participatory design methods future users from different business units are involved in order to adopt WA into their workspace through building individual WA reports. The developed iterative model consists of five main steps. After the presentation of the developed model, we demonstrate the applicability in a case study at an industrial company. The case study shows a greater adoption by the different users, as the dashboards are individually tailored to them.
AB - Web Analytics (WA) tools offer an increasing amount of analysis options. This amount of possible data overwhelm business users who are not familiar with WA and therefore the potential of WA is not fully exploited. We address this demand of individual information needs with the development of an indicator selection process. By using participatory design methods future users from different business units are involved in order to adopt WA into their workspace through building individual WA reports. The developed iterative model consists of five main steps. After the presentation of the developed model, we demonstrate the applicability in a case study at an industrial company. The case study shows a greater adoption by the different users, as the dashboards are individually tailored to them.
KW - Individual technology Adoption
KW - Participatory design
KW - Web analytics key performance indicators
KW - Web traffic report development
UR - http://www.scopus.com/inward/record.url?scp=85084022005&partnerID=8YFLogxK
M3 - Conference contribution
SN - 978-0-9966831-8-0
BT - AMCIS 2019 Proceedings. 21.
Y2 - 15 August 2019 through 17 August 2019
ER -