Inkrementell responsanalys av Scandnavian Airlines medlemmar : Vilka kunder ska väljas vid riktad marknadsföring?

Scandinavian Airlines has a large database containing their Eurobonus members. In order to analyze which customers they should target with direct marketing, such as emails, uplift models have been used. With a binary response variable that indicates whether the customer has bought or not, and a bina...

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Main Authors: Anderskär, Erika, Thomasson, Frida
Format: Others
Language:Swedish
Published: Linköpings universitet, Statistik och maskininlärning 2017
Subjects:
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-139465
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spelling ndltd-UPSALLA1-oai-DiVA.org-liu-1394652017-08-12T05:29:41ZInkrementell responsanalys av Scandnavian Airlines medlemmar : Vilka kunder ska väljas vid riktad marknadsföring?sweIncremental response analysis of member data from Scandinavian Airlines : Which customers should be selected in direct marketing?Anderskär, ErikaThomasson, FridaLinköpings universitet, Statistik och maskininlärningLinköpings universitet, Statistik och maskininlärning2017uplift modelsincremental response analysisnet lift modelslasso regressionlogistic regressioninkrementell responsanalyslassoregressionlogistisk regressionProbability Theory and StatisticsSannolikhetsteori och statistikScandinavian Airlines has a large database containing their Eurobonus members. In order to analyze which customers they should target with direct marketing, such as emails, uplift models have been used. With a binary response variable that indicates whether the customer has bought or not, and a binary dummy variable that indicates if the customer has received the campaign or not conclusions can be drawn about which customers are persuadable. That means that the customers that buy when they receive a campaign and not if they don't are spotted. Analysis have been done with one campaign for Sweden and Scandinavia. The methods that have been used are logistic regression with Lasso and logistic regression with Penalized Net Information Value. The best method for predicting purchases is Lasso regression when comparing with a confusion matrix. The variable that best describes persuadable customers in logistic regression with PNIV is Flown (customers that have own with SAS within the last six months). In Lassoregression the variable that describes a persuadable customer in Sweden is membership level1 (the rst level of membership) and in Scandinavia customers that receive campaigns with delivery code 13 are persuadable, which is a form of dispatch. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-139465application/pdfinfo:eu-repo/semantics/openAccess
collection NDLTD
language Swedish
format Others
sources NDLTD
topic uplift models
incremental response analysis
net lift models
lasso regression
logistic regression
inkrementell responsanalys
lassoregression
logistisk regression
Probability Theory and Statistics
Sannolikhetsteori och statistik
spellingShingle uplift models
incremental response analysis
net lift models
lasso regression
logistic regression
inkrementell responsanalys
lassoregression
logistisk regression
Probability Theory and Statistics
Sannolikhetsteori och statistik
Anderskär, Erika
Thomasson, Frida
Inkrementell responsanalys av Scandnavian Airlines medlemmar : Vilka kunder ska väljas vid riktad marknadsföring?
description Scandinavian Airlines has a large database containing their Eurobonus members. In order to analyze which customers they should target with direct marketing, such as emails, uplift models have been used. With a binary response variable that indicates whether the customer has bought or not, and a binary dummy variable that indicates if the customer has received the campaign or not conclusions can be drawn about which customers are persuadable. That means that the customers that buy when they receive a campaign and not if they don't are spotted. Analysis have been done with one campaign for Sweden and Scandinavia. The methods that have been used are logistic regression with Lasso and logistic regression with Penalized Net Information Value. The best method for predicting purchases is Lasso regression when comparing with a confusion matrix. The variable that best describes persuadable customers in logistic regression with PNIV is Flown (customers that have own with SAS within the last six months). In Lassoregression the variable that describes a persuadable customer in Sweden is membership level1 (the rst level of membership) and in Scandinavia customers that receive campaigns with delivery code 13 are persuadable, which is a form of dispatch.
author Anderskär, Erika
Thomasson, Frida
author_facet Anderskär, Erika
Thomasson, Frida
author_sort Anderskär, Erika
title Inkrementell responsanalys av Scandnavian Airlines medlemmar : Vilka kunder ska väljas vid riktad marknadsföring?
title_short Inkrementell responsanalys av Scandnavian Airlines medlemmar : Vilka kunder ska väljas vid riktad marknadsföring?
title_full Inkrementell responsanalys av Scandnavian Airlines medlemmar : Vilka kunder ska väljas vid riktad marknadsföring?
title_fullStr Inkrementell responsanalys av Scandnavian Airlines medlemmar : Vilka kunder ska väljas vid riktad marknadsföring?
title_full_unstemmed Inkrementell responsanalys av Scandnavian Airlines medlemmar : Vilka kunder ska väljas vid riktad marknadsföring?
title_sort inkrementell responsanalys av scandnavian airlines medlemmar : vilka kunder ska väljas vid riktad marknadsföring?
publisher Linköpings universitet, Statistik och maskininlärning
publishDate 2017
url http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-139465
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AT anderskarerika incrementalresponseanalysisofmemberdatafromscandinavianairlineswhichcustomersshouldbeselectedindirectmarketing
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