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Modeling strategies using predictive analytics: Forecasting future sales and churn management
KTH, School of Information and Communication Technology (ICT).
2015 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Strategier för modelleringmedprediktiv analys (Swedish)
Abstract [en]

This project was carried out for a company named Attollo, a consulting firm specialized in Business

Intelligence and Corporate Performance Management. The project aims to explore a new area for

Attollo, predictive analytics, which is then applied to Klarna, a client of Attollo. Attollo has a

partnership with IBM, which sells services for predictive analytics. The tool that this project is

carried out with, is a software from IBM: SPSS Modeler. Five different examples are given of what

and how the predictive work that was carried out at Klarna consisted of. From these examples, the

different predictive models' functionality are described. The result of this project demonstrates, by

using predictive analytics, how predictive models can be created. The conclusion is that predictive

analytics enables companies to understand their customers better and hence make better decisions.

Abstract [sv]

Detta projekt har utforts tillsammans med ett foretag som heter Attollo, en konsultfirma som ar

specialiserade inom Business Intelligence & Coporate Performance Management. Projektet grundar

sig pa att Attollo ville utforska ett nytt omrade, prediktiv analys, som sedan applicerades pa Klarna,

en kund till Attollo. Attollo har ett partnerskap med IBM, som saljer tjanster for prediktiv analys.

Verktyget som detta projekt utforts med, ar en mjukvara fran IBM: SPSS Modeler. Fem olika

exempel beskriver det prediktiva arbetet som utfordes vid Klarna. Fran dessa exempel beskrivs

ocksa de olika prediktiva modellernas funktionalitet. Resultatet av detta projekt visar hur man

genom prediktiv analys kan skapa prediktiva modeller. Slutsatsen ar att prediktiv analys ger foretag

storre mojlighet att forsta sina kunder och darav kunna gora battre beslut.

Place, publisher, year, edition, pages
2015.
Series
TRITA-ICT-EX, 2015:5
Keyword [en]
Business Intelligence, Predictive Analytics, Data mining, Data warehouse, Predictive Modeling, RFM, Churn
Identifiers
URN: urn:nbn:se:kth:diva-167130OAI: oai:DiVA.org:kth-167130DiVA: diva2:813110
Examiners
Available from: 2015-05-21 Created: 2015-05-21 Last updated: 2015-05-21Bibliographically approved

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