“Know” Your Mobile Customers: A Design Approach To An Android-Based Mobile Analytics Tool

Qiqi Jiang, Lele Kang

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

There is no doubt that we are living in the mobile age. Massive commercial data from mobile users provide huge potential opportunities for both merchants and researchers. However, compared with Web analytics, how to analyze the mobile data is still under debate. Some companies have adopted similar measurements or metrics to those that have been used in Web analytics tools to depict mobile activities. However, such measurements might bias the interpretation because the behaviors on mobile devices are fundamentally different from behaviors in an online context. Hence, we propose a prototype of an Android-based mobile analytics tool with novel mechanisms for better observing user behaviors in the mobile context, by which the individual behavioral data can be captured at the activity level. The detailed design, such as prototype structure, data structure, specific classes or methods, and sample codes, will be provided. In addition, some potential research opportunities will be elaborated. Furthermore, the practical value of our proposed prototype will be discussed.
There is no doubt that we are living in the mobile age. Massive commercial data from mobile users provide huge potential opportunities for both merchants and researchers. However, compared with Web analytics, how to analyze the mobile data is still under debate. Some companies have adopted similar measurements or metrics to those that have been used in Web analytics tools to depict mobile activities. However, such measurements might bias the interpretation because the behaviors on mobile devices are fundamentally different from behaviors in an online context. Hence, we propose a prototype of an Android-based mobile analytics tool with novel mechanisms for better observing user behaviors in the mobile context, by which the individual behavioral data can be captured at the activity level. The detailed design, such as prototype structure, data structure, specific classes or methods, and sample codes, will be provided. In addition, some potential research opportunities will be elaborated. Furthermore, the practical value of our proposed prototype will be discussed.
LanguageEnglish
Title of host publicationPACIS 2018 Proceedings
EditorsMotonari Tanabu, Dai Senoo
Number of pages9
Place of PublicationAtlanta, GA
PublisherAssociation for Information Systems. AIS Electronic Library (AISeL)
Date2018
Article number75
StatePublished - 2018
EventThe 22nd Pacific Asia Conference on Information Systems. PACIS 2018 - Yokohama Royal Park Hotel, Yokohama, Japan
Duration: 26 Jun 201830 Jun 2018
Conference number: 22
http://pacis2018.org/

Conference

ConferenceThe 22nd Pacific Asia Conference on Information Systems. PACIS 2018
Number22
LocationYokohama Royal Park Hotel
CountryJapan
CityYokohama
Period26/06/201830/06/2018
SponsorAssociation for Information Systems
Internet address

Cite this

Jiang, Q., & Kang, L. (2018). “Know” Your Mobile Customers: A Design Approach To An Android-Based Mobile Analytics Tool. In M. Tanabu, & D. Senoo (Eds.), PACIS 2018 Proceedings [75] Atlanta, GA: Association for Information Systems. AIS Electronic Library (AISeL).
Jiang, Qiqi ; Kang, Lele. / “Know” Your Mobile Customers : A Design Approach To An Android-Based Mobile Analytics Tool. PACIS 2018 Proceedings. editor / Motonari Tanabu ; Dai Senoo. Atlanta, GA : Association for Information Systems. AIS Electronic Library (AISeL), 2018.
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Jiang, Q & Kang, L 2018, “Know” Your Mobile Customers: A Design Approach To An Android-Based Mobile Analytics Tool. in M Tanabu & D Senoo (eds), PACIS 2018 Proceedings., 75, Association for Information Systems. AIS Electronic Library (AISeL), Atlanta, GA, Yokohama, Japan, 26/06/2018.

“Know” Your Mobile Customers : A Design Approach To An Android-Based Mobile Analytics Tool. / Jiang, Qiqi ; Kang, Lele.

PACIS 2018 Proceedings. ed. / Motonari Tanabu; Dai Senoo. Atlanta, GA : Association for Information Systems. AIS Electronic Library (AISeL), 2018. 75.

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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Jiang Q, Kang L. “Know” Your Mobile Customers: A Design Approach To An Android-Based Mobile Analytics Tool. In Tanabu M, Senoo D, editors, PACIS 2018 Proceedings. Atlanta, GA: Association for Information Systems. AIS Electronic Library (AISeL). 2018. 75.