Improving Post-Click User Engagement on Native Ads via Survival Analysis

Nicola Barbieri, F. Silvestri, M. Lalmas
{"title":"Improving Post-Click User Engagement on Native Ads via Survival Analysis","authors":"Nicola Barbieri, F. Silvestri, M. Lalmas","doi":"10.1145/2872427.2883092","DOIUrl":null,"url":null,"abstract":"In this paper we focus on estimating the post-click engagement on native ads by predicting the dwell time on the corresponding ad landing pages. To infer relationships between features of the ads and dwell time we resort to the application of survival analysis techniques, which allow us to estimate the distribution of the length of time that the user will spend on the ad. This information is then integrated into the ad ranking function with the goal of promoting the rank of ads that are likely to be clicked and consumed by users (dwell time greater than a given threshold). The online evaluation over live traffic shows that considering post-click engagement has a consistent positive effect on both CTR, decreases the number of bounces and increases the average dwell time, hence leading to a better user post-click experience.","PeriodicalId":20455,"journal":{"name":"Proceedings of the 25th International Conference on World Wide Web","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"57","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 25th International Conference on World Wide Web","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2872427.2883092","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 57

Abstract

In this paper we focus on estimating the post-click engagement on native ads by predicting the dwell time on the corresponding ad landing pages. To infer relationships between features of the ads and dwell time we resort to the application of survival analysis techniques, which allow us to estimate the distribution of the length of time that the user will spend on the ad. This information is then integrated into the ad ranking function with the goal of promoting the rank of ads that are likely to be clicked and consumed by users (dwell time greater than a given threshold). The online evaluation over live traffic shows that considering post-click engagement has a consistent positive effect on both CTR, decreases the number of bounces and increases the average dwell time, hence leading to a better user post-click experience.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
通过生存分析提高原生广告的点击后用户粘性
在本文中,我们主要通过预测相应广告登陆页面的停留时间来估计原生广告的点击后粘性。为了推断广告特征与停留时间之间的关系,我们采用了生存分析技术,这使我们能够估计用户将在广告上花费的时间长度的分布。然后将这些信息整合到广告排名功能中,目标是提高可能被用户点击和消费的广告的排名(停留时间大于给定阈值)。对实时流量的在线评估表明,考虑点击后粘性对点击率和平均停留时间都有持续的积极影响,减少了反弹次数,增加了平均停留时间,从而带来了更好的用户点击后体验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
MapWatch: Detecting and Monitoring International Border Personalization on Online Maps Automatic Discovery of Attribute Synonyms Using Query Logs and Table Corpora Learning Global Term Weights for Content-based Recommender Systems From Freebase to Wikidata: The Great Migration GoCAD: GPU-Assisted Online Content-Adaptive Display Power Saving for Mobile Devices in Internet Streaming
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1