Quecst: Quick and Easy Customer Segmentation Tool
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Background

"Team Quecst" is a hard-working research team at the Qatar Computing Research Institute, Hamad Bin Khalifa University. The Team is actively contributing to segmentation analytics. This page contains Team Quecst's peer-reviewed research contributions elating to segmentation analytics

For research collaboration, please contact Dr. Jim Jansen, email: bjansen@hbku.edu.qa.


Segmentation Analytics research contributions

Jansen, B. J., Jung, S.G., Ramirez Robillos, D., and Salminen, J. (2021) Too Few, Too Many, Just Right: Creating the Necessary Number of Segments for Large Online Customer PopulationsElectronic Commerce Research and Applications, 49, Article 101083.

Jansen, B. J., Jung, S.G., Chowdhury, S., and Salminen, J. (2021) Persona Analytics: Analyzing the stability of online segments and content interests over time using non-negative matrix factorizationExpert Systems with Applications, 185, Article 115611.

Marzouk, O., Salminen, J., Zhang, P., and Jansen, B. J. (2021) Which Message? Which Channel? Which Customer?: Exploring Response Rates in Multi-Channel Marketing Using Short Form AdvertisingData and Information Management.

Thirumuruganathan, S., Salminen, J., Jung, S. G., Ramirez Robillos, D., and Jansen, B. J. (2021) Forecasting the Nearly Unforecastable: Why Aren’t Airline Bookings Adhering to the Prediction Algorithm?Electronic Commerce Research21, 73–100 https://doi.org/10.1007/s10660-021-09457-0

Salminen, J., Sercan, S., Jung, S.G., and Jansen, B. J. (2021) Comparing Persona Analytics and Social Media Analytics for a User-Centric Task Using Eye-Tracking and Think-Aloud. CHItaly2021, 11-13 July 2021, Remote via Internet & ​Bozen-Bolzano, Italy.

Jung, S.G., Salminen, J., and Jansen, B. J. (2021) Persona Analytics: Implementing Mouse-tracking for an Interactive Persona System. ACM CHI Conference on Human Factors in Computing Systems (CHI2021), Yokohama, Japan. 8-13 May. Article No.: 342.

Jansen, B. J., Salminen, J. O., & Jung, S. (2020). Making Meaningful User Segments from Datasets Using Product Dissemination and Product ImpactData and Information Management. doi: https://doi.org/10.2478/dim-2020-0048

Salminen, J., Jung, S.G., Chowdhury. S., Ramirez-Robillos, D., and Jansen, B. J.  (2020) Things Change: Comparing Results Using Historical Data and User Testing for Evaluating a Recommendation Task. ACM CHI Conference on Human Factors in Computing Systems (CHI'20) (Extended Abstract), Honolulu, HI, USA. 25–30 April, 1–7.

An, J., Kwak, H., Salminen, J., Jung, S.G., and Jansen, B. J. (2018) Customer segmentation using online platforms: isolating behavioral and demographic segments for persona creation via aggregated user dataSocial Network Analysis and Mining. 8(1), 54.

Jansen, B. J., Jung, S.G., Salminen, J., An, J. and Kwak, H. (2018) Combining Behavioral and Demographic Information to Segment Online Audiences: Experiments with a YouTube Channel. 5th International Conference 'Internet Science' (INSCI'2018) St. Petersburg, Russia, 24-26 October. 141-153.

Jung, S., An, J., Kwak, H., Salminen, J., and Jansen, B. J. (2017) Inferring social media users’ demographics from profile pictures: A Face++ analysis on Twitter users, International Conference on Electronic Business (ICEB 2017), Dubai, UAE. p. 140-145. 4-8 December. 

Jansen, B. J., An, J., Kwak, H., Salminen, J.O., and Jung, S.G. (2017) Viewed by Too Many or Viewed Too Little: Using Information Dissemination for Audience Segmentation. Association for Information Science and Technology Annual Meeting 2017 (ASIST2017). Washington, DC. p. 189-196. 27 Oct. - 1 Nov.