Understanding Mobile Searcher Attention with Rich Ad Formats

Dmitry Lagun, Donal McMahon, Vidhya Navalpakkam
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引用次数: 20

Abstract

Mobile Search experiences have evolved significantly from a few blue links that require users to click. Recent search and ad units surface instant information to the user in a variety of visually rich formats that include images, horizontal swipes, and vertical scrolls. These innovative experiences call for new metrics and models to better understand searcher behavior on mobile phones. In this paper, we study how the presence of ads and their formats impacts searcher's gaze and satisfaction. We systematically vary presentation format of the sponsored result, while controlling for other factors, such as position and quality of organic results. We experiment with several configurations of text ad and rich ad formats. Our findings indicate that showing rich ad formats improve search experience, by drawing more attention to the information-rich ad and allowing users to interact to view more offers, which increases user satisfaction with search. In addition, we extend prior work by comparing the performance of various models to infer user's gaze from viewport data. Our models improve accuracy of existing viewport-based gaze inference methods by 30% in Pearson's correlation. Together, our findings show that viewport data can be used for fast, accurate and scalable measurement of user attention on a per-element basis, for both ads as well as organic search results.
利用丰富的广告格式了解移动搜索者的注意力
移动搜索体验已经从几个需要用户点击的蓝色链接发展到现在。最近的搜索和广告单元以各种视觉丰富的格式向用户展示即时信息,包括图像、水平滑动和垂直滚动。这些创新的体验需要新的指标和模型来更好地理解手机搜索者的行为。在本文中,我们研究了广告的存在及其格式如何影响搜索者的目光和满意度。我们系统地改变赞助结果的呈现格式,同时控制其他因素,如有机结果的位置和质量。我们尝试了几种文本广告和富广告格式的配置。我们的研究结果表明,展示丰富的广告格式可以改善搜索体验,通过吸引更多的注意力到信息丰富的广告上,并允许用户互动以查看更多的优惠,从而提高用户对搜索的满意度。此外,我们通过比较各种模型的性能来从视口数据推断用户的凝视,从而扩展了先前的工作。我们的模型将现有的基于视口的凝视推断方法的准确率提高了30%。综上所述,我们的研究结果表明,视口数据可以用于快速、准确和可扩展的基于每个元素的用户注意力测量,无论是广告还是自然搜索结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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