Ralf van der Lans, G. V. van Bruggen, J. Eliashberg, B. Wierenga
{"title":"向Harvest Reach发送消息预测和优化电子口碑的传播","authors":"Ralf van der Lans, G. V. van Bruggen, J. Eliashberg, B. Wierenga","doi":"10.2478/GFKMIR-2014-0039","DOIUrl":null,"url":null,"abstract":"Abstract In a viral marketing campaign organizations stimulate customers to forward marketing messages to their contacts. To optimize a viral campaign it is necessary to predict how many customers will be reached, how this reach evolves, and how it depends on promotion activities. a new Viral Branching model can provide these results. It is based on insights from epidemiology and the spread of viruses and was adapted to a marketing context and an electronic environment. The model is applied to an actual viral marketing campaign in which over 200,000 customers participated during a six-week period. The results show that the model quickly predicts the actual reach of the campaign and serves as a valuable tool to support marketing decisions related to online campaigns","PeriodicalId":30678,"journal":{"name":"GfK Marketing Intelligence Review","volume":"21 1","pages":"32 - 41"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Seeding a Message to Harvest Reach. Predicting and Optimizing the Spread of Electronic Word-of-Mouth\",\"authors\":\"Ralf van der Lans, G. V. van Bruggen, J. Eliashberg, B. Wierenga\",\"doi\":\"10.2478/GFKMIR-2014-0039\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract In a viral marketing campaign organizations stimulate customers to forward marketing messages to their contacts. To optimize a viral campaign it is necessary to predict how many customers will be reached, how this reach evolves, and how it depends on promotion activities. a new Viral Branching model can provide these results. It is based on insights from epidemiology and the spread of viruses and was adapted to a marketing context and an electronic environment. The model is applied to an actual viral marketing campaign in which over 200,000 customers participated during a six-week period. The results show that the model quickly predicts the actual reach of the campaign and serves as a valuable tool to support marketing decisions related to online campaigns\",\"PeriodicalId\":30678,\"journal\":{\"name\":\"GfK Marketing Intelligence Review\",\"volume\":\"21 1\",\"pages\":\"32 - 41\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"GfK Marketing Intelligence Review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2478/GFKMIR-2014-0039\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"GfK Marketing Intelligence Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/GFKMIR-2014-0039","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Seeding a Message to Harvest Reach. Predicting and Optimizing the Spread of Electronic Word-of-Mouth
Abstract In a viral marketing campaign organizations stimulate customers to forward marketing messages to their contacts. To optimize a viral campaign it is necessary to predict how many customers will be reached, how this reach evolves, and how it depends on promotion activities. a new Viral Branching model can provide these results. It is based on insights from epidemiology and the spread of viruses and was adapted to a marketing context and an electronic environment. The model is applied to an actual viral marketing campaign in which over 200,000 customers participated during a six-week period. The results show that the model quickly predicts the actual reach of the campaign and serves as a valuable tool to support marketing decisions related to online campaigns