着眼长远:这对用户和企业都有好处

Henning Hohnhold, Deirdre O'Brien, Diane Tang
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引用次数: 94

摘要

在过去的10多年里,大大小小的在线公司已经广泛采用了A/B测试作为评估潜在产品改进的稳健的基于数据的方法。在在线实验中,可以直接测量短期效果,即在实验过程中观察到的影响。然而,短期效果并不总是可以预测长期效果,即一旦产品完全推出,用户改变了他们的行为后的最终影响。因此,挑战在于如何确定对用户的长期影响,同时仍然能够及时做出决策。在本文中,我们通过首先开发量化长期用户学习的实验方法来解决这一挑战。然后,我们将这种方法应用于谷歌搜索上显示的广告,更具体地说,确定和量化广告盲目性和视障性的驱动因素,即用户改变其点击广告或与广告互动的固有倾向的现象。我们使用这些结果创建了一个模型,该模型使用短期可测量的指标来预测长期。我们了解到用户满意度是至关重要的:广告盲目性和目标性是由之前浏览或点击的广告质量驱动的,这可以通过广告相关性和登陆页面质量来衡量。正如我们的研究结果所示,关注用户满意度不仅可以确保用户更快乐,而且还具有商业意义。我们描述了我们的研究结果的两个主要应用:对我们的搜索广告拍卖的概念上的改变,进一步提高了广告质量的重要性,以及谷歌移动搜索界面上的广告负荷减少了50%。本文的结果主要有两种推广方法。首先,该方法可用于量化用户学习效果,并评估广告以外情境下的在线实验。其次,广告盲目性/盲目性结果表明,关注用户满意度可以帮助减少互联网上的广告负荷,对商业产生长期中立甚至积极的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Focusing on the Long-term: It's Good for Users and Business
Over the past 10+ years, online companies large and small have adopted widespread A/B testing as a robust data-based method for evaluating potential product improvements. In online experimentation, it is straightforward to measure the short-term effect, i.e., the impact observed during the experiment. However, the short-term effect is not always predictive of the long-term effect, i.e., the final impact once the product has fully launched and users have changed their behavior in response. Thus, the challenge is how to determine the long-term user impact while still being able to make decisions in a timely manner. We tackle that challenge in this paper by first developing experiment methodology for quantifying long-term user learning. We then apply this methodology to ads shown on Google search, more specifically, to determine and quantify the drivers of ads blindness and sightedness, the phenomenon of users changing their inherent propensity to click on or interact with ads. We use these results to create a model that uses metrics measurable in the short-term to predict the long-term. We learn that user satisfaction is paramount: ads blindness and sightedness are driven by the quality of previously viewed or clicked ads, as measured by both ad relevance and landing page quality. Focusing on user satisfaction both ensures happier users but also makes business sense, as our results illustrate. We describe two major applications of our findings: a conceptual change to our search ads auction that further increased the importance of ads quality, and a 50% reduction of the ad load on Google's mobile search interface. The results presented in this paper are generalizable in two major ways. First, the methodology may be used to quantify user learning effects and to evaluate online experiments in contexts other than ads. Second, the ads blindness/sighted-ness results indicate that a focus on user satisfaction could help to reduce the ad load on the internet at large with long-term neutral, or even positive, business impact.
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