{"title":"The User-journey in Online Search - An Empirical Study of the Generic-to-Branded Spillover Effect based on User-level Data","authors":"Florian Nottorf, Andreas Mastel, Burkhardt Funk","doi":"10.5220/0004052101450154","DOIUrl":null,"url":null,"abstract":"Traditional metrics in online advertising such as the click-through rate often take into account the users’ search activities separately and do not consider any interactions between them. In understanding online search behavior, this fact may favor a certain group of search type and, therefore, may mislead managers in allocating their financial spending efficiently. We analyzed a large query log for the occurrence of user-specific interaction patterns within and across three different industries (clothing, healthcare, hotel) and were able to show that users’ online search behavior is indeed a multi-stage process, whereas e.g. a product search for sneakers typically begins with general, often referred to as generic, keywords which becomes narrowed as it proceeds by including more specific, e.g. brand-related (“sneakers adidas”), keywords. Our method to analyze the development of users’ search process within query logs helps managers to identify the role of specific activities within a respective industry and to allocate their financial spending in paid search advertising accordingly.","PeriodicalId":194465,"journal":{"name":"DCNET/ICE-B/OPTICS","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"DCNET/ICE-B/OPTICS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0004052101450154","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Traditional metrics in online advertising such as the click-through rate often take into account the users’ search activities separately and do not consider any interactions between them. In understanding online search behavior, this fact may favor a certain group of search type and, therefore, may mislead managers in allocating their financial spending efficiently. We analyzed a large query log for the occurrence of user-specific interaction patterns within and across three different industries (clothing, healthcare, hotel) and were able to show that users’ online search behavior is indeed a multi-stage process, whereas e.g. a product search for sneakers typically begins with general, often referred to as generic, keywords which becomes narrowed as it proceeds by including more specific, e.g. brand-related (“sneakers adidas”), keywords. Our method to analyze the development of users’ search process within query logs helps managers to identify the role of specific activities within a respective industry and to allocate their financial spending in paid search advertising accordingly.