TY - GEN
T1 - Kaleidoscope
T2 - 39th IEEE International Conference on Distributed Computing Systems, ICDCS 2019
AU - Wang, Pengfei
AU - Varvello, Matteo
AU - Kuzmanovic, Aleksandar
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - Today's webpages development cycle consists of constant iterations with the goal to improve user retention, time spent on site, and overall quality of experience. Big companies like Google, Facebook, Amazon, etc. invest a lot of time and money to perform online testing. The prohibitive costs of these approaches are an entry barrier for smaller players. Further, the lack of a substantial user-base can be problematic to ensure statistical significance within a reasonable duration. In this paper we propose Kaleidoscope, an automated tool to evaluate Web features at a large scale, quickly, accurately, and at a reasonable price. Kaleidoscope can test two crucial user-perceived Web features - the style and page loading. As far as we know, it is the first testing tool to replay page loading by controlling visual changes on a webpage. Kaleidoscope allows to concurrently load a webpage in two versions (e.g., different fonts, with vs without ads) that are shown to a participant side-by-side. Further, Kaleidoscope also allows a participant to interact with each webpage version and provide feedback, e.g., respond to a questionnaire previously prepared by an 'experimenter'. Kaleidoscope supports both voluntary and paid testers from FigureEight, a popular crowdsourcing platform. Using hundreds of FigureEight testers, we validate that Kaleidoscope matches the accuracy of trusted in-lab tests while providing results about 12x faster (and arguably at a lower cost) than A/B testing. Finally, we showcase how to use Kaleidoscope's page loading feature to study the user-perceived page load time (uPLT) of a webpage.
AB - Today's webpages development cycle consists of constant iterations with the goal to improve user retention, time spent on site, and overall quality of experience. Big companies like Google, Facebook, Amazon, etc. invest a lot of time and money to perform online testing. The prohibitive costs of these approaches are an entry barrier for smaller players. Further, the lack of a substantial user-base can be problematic to ensure statistical significance within a reasonable duration. In this paper we propose Kaleidoscope, an automated tool to evaluate Web features at a large scale, quickly, accurately, and at a reasonable price. Kaleidoscope can test two crucial user-perceived Web features - the style and page loading. As far as we know, it is the first testing tool to replay page loading by controlling visual changes on a webpage. Kaleidoscope allows to concurrently load a webpage in two versions (e.g., different fonts, with vs without ads) that are shown to a participant side-by-side. Further, Kaleidoscope also allows a participant to interact with each webpage version and provide feedback, e.g., respond to a questionnaire previously prepared by an 'experimenter'. Kaleidoscope supports both voluntary and paid testers from FigureEight, a popular crowdsourcing platform. Using hundreds of FigureEight testers, we validate that Kaleidoscope matches the accuracy of trusted in-lab tests while providing results about 12x faster (and arguably at a lower cost) than A/B testing. Finally, we showcase how to use Kaleidoscope's page loading feature to study the user-perceived page load time (uPLT) of a webpage.
KW - A/B testing
KW - Crowdsourcing
KW - Page loading
KW - Quality of Experience
KW - Web testing
UR - http://www.scopus.com/inward/record.url?scp=85072701920&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85072701920&partnerID=8YFLogxK
U2 - 10.1109/ICDCS.2019.00195
DO - 10.1109/ICDCS.2019.00195
M3 - Conference contribution
AN - SCOPUS:85072701920
T3 - Proceedings - International Conference on Distributed Computing Systems
SP - 1971
EP - 1982
BT - Proceedings - 2019 39th IEEE International Conference on Distributed Computing Systems, ICDCS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 7 July 2019 through 9 July 2019
ER -