Real-world product deployment of adaptive push notification scheduling on smartphones

Tadashi Okoshi, Kota Tsubouchi, Hideyuki Tokuda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

The limited attentional resource of users is a bottleneck to delivery of push notifications in today's mobile and ubiquitous computing environments. Adaptive mobile notification scheduling, which detects opportune timings based on mobile sensing and machine learning, has been proposed as a way of alleviating this problem. However, it is still not clear if such adaptive notifications are effective in a large-scale product deployment with real-world situations and configurations, such as users' context changes, personalized content in notifications, and sudden external factors that users commonly experience (such as breaking news). In this paper, we construct a new interruptibility estimation and adaptive notification scheduling with redesigned technical components. From the deploy study of the system to the real product stack of Yahoo! JAPAN Android application and evaluation with 382,518 users for 28 days, we confirmed several significant results, including the maximum 60.7% increase in the users' click rate, 10 times more gain1compared to the previous system, significantly better gain in the personalized notification content, and unexpectedly better performance in a situation with exceptional breaking news notifications. With these results, the proposed system has officially been deployed and enabled to all the users of Yahoo! JAPAN product environment where more than 10 million Android app users are enjoying its benefit.

Original languageEnglish
Title of host publicationKDD 2019 - Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
PublisherAssociation for Computing Machinery
Pages2792-2800
Number of pages9
ISBN (Electronic)9781450362016
DOIs
Publication statusPublished - 2019 Jul 25
Event25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2019 - Anchorage, United States
Duration: 2019 Aug 42019 Aug 8

Publication series

NameProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Conference

Conference25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2019
Country/TerritoryUnited States
CityAnchorage
Period19/8/419/8/8

Keywords

  • Attention management
  • Interruption overload
  • Middleware
  • Push notification
  • Real-world deployment
  • Smartphone

ASJC Scopus subject areas

  • Software
  • Information Systems

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