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dc.contributor.authorQismat, Temor
dc.contributor.authorFeng, Yan
dc.date.accessioned2020-11-19T11:44:47Z
dc.date.available2020-11-19T11:44:47Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/11250/2688689
dc.descriptionMasteroppgave(MSc) in Master of Science in Business Analytics - Handelshøyskolen BI, 2020en_US
dc.description.abstractThis study analyzes the difference between classical RFM models and Machine Leaning (ML) models when calculating CLV with transactional data. In this paper we run different programs to analyze the CLV value by using both methods. Based on the results, the researchers found out that Pareto/NBD model have better predictive power of performing CLV predictions than ML models. Lastly, the findings proved the effectiveness of the Pareto/NBD method of calculating CLV.en_US
dc.language.isoengen_US
dc.publisherHandelshøyskolen BIen_US
dc.subjectbusiness analyticsen_US
dc.titleComparison of classical RFM models and Machine learning models in CLV predictionen_US
dc.typeMaster thesisen_US


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