How Does Prepopulating Search Bars with Keywords Affect Online Consumer Behavior? A Field Experiment

情感(语言学) 反事实思维 产品(数学) 广告 领域(数学) 搜索成本 产品类别 营销 消费者行为 在线搜索 业务 计算机科学 产品类型 情报检索 随机试验 偏移量(计算机科学) 关键字搜索 搜索广告 在线广告 推荐系统 竞争对手分析
作者
Chenshuo Sun
出处
期刊:Marketing Science [Institute for Operations Research and the Management Sciences]
卷期号:44 (6): 1217-1231 被引量:1
标识
DOI:10.1287/mksc.2024.0793
摘要

Search aid technologies, especially prepopulated search bars, are increasingly being adopted by major players in the fast-growing e-commerce industry. Yet, surprisingly little is known about the impact of prepopulating search bars with keywords on online consumer journey. In this study, I design and run a randomized field experiment on a large e-commerce platform involving 72,587 consumers who were randomly exposed to three types of keywords prefilled in the search bar. Individual consumer–level analyses reveal that prepopulating trending category keywords encourages users to discover and buy items from the suggested category without reducing queries using self-entered keywords, ultimately leading to a 10.4% (8.8%) increase in purchase incidence (spending) compared with the counterfactual outcomes when the search bar is empty. Prepopulating personalized keywords brings about more focused product searching within the category recently browsed by users, resulting in a 21% (17%) increase in purchase incidence (spending), although this is offset by the negative effect of a reduction in queries using self-entered keywords. Exposure to niche category keywords is found to have little impact. This study also finds that a prepopulated search bar does not cannibalize the other navigation tool, making it a beneficial addition to the focal e-commerce platform’s business outcomes. These findings, contributing to the literature on consumer search and product recommendation strategies for digital platforms, carry timely implications for e-commerce managers. History: Catherine Tucker served as the senior editor. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mksc.2024.0793 .
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