{"title":"The impact of TV advertising on website traffic","authors":"Lukáš Veverka, Vladimír Holý","doi":"10.1002/asmb.2850","DOIUrl":null,"url":null,"abstract":"We propose a modeling procedure for estimating immediate responses to TV ads and evaluating the factors influencing their size. First, we capture diurnal and seasonal patterns of website visits using the kernel smoothing method. Second, we estimate a gradual increase in website visits after an ad using the maximum likelihood method. Third, we analyze the nonlinear dependence of the estimated increase in website visits on characteristics of the ads using the random forest method. The proposed methodology is applied to a dataset containing minute-by-minute organic website visits and detailed characteristics of TV ads for an e-commerce company in 2019. The results show that people are indeed willing to switch between screens and multitask. Moreover, the time of the day, the TV channel, and the advertising motive play a great role in the impact of the ads.","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"88 1","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Stochastic Models in Business and Industry","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1002/asmb.2850","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
We propose a modeling procedure for estimating immediate responses to TV ads and evaluating the factors influencing their size. First, we capture diurnal and seasonal patterns of website visits using the kernel smoothing method. Second, we estimate a gradual increase in website visits after an ad using the maximum likelihood method. Third, we analyze the nonlinear dependence of the estimated increase in website visits on characteristics of the ads using the random forest method. The proposed methodology is applied to a dataset containing minute-by-minute organic website visits and detailed characteristics of TV ads for an e-commerce company in 2019. The results show that people are indeed willing to switch between screens and multitask. Moreover, the time of the day, the TV channel, and the advertising motive play a great role in the impact of the ads.
期刊介绍：
ASMBI - Applied Stochastic Models in Business and Industry (formerly Applied Stochastic Models and Data Analysis) was first published in 1985, publishing contributions in the interface between stochastic modelling, data analysis and their applications in business, finance, insurance, management and production. In 2007 ASMBI became the official journal of the International Society for Business and Industrial Statistics (www.isbis.org). The main objective is to publish papers, both technical and practical, presenting new results which solve real-life problems or have great potential in doing so. Mathematical rigour, innovative stochastic modelling and sound applications are the key ingredients of papers to be published, after a very selective review process.
The journal is very open to new ideas, like Data Science and Big Data stemming from problems in business and industry or uncertainty quantification in engineering, as well as more traditional ones, like reliability, quality control, design of experiments, managerial processes, supply chains and inventories, insurance, econometrics, financial modelling (provided the papers are related to real problems). The journal is interested also in papers addressing the effects of business and industrial decisions on the environment, healthcare, social life. State-of-the art computational methods are very welcome as well, when combined with sound applications and innovative models.
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