Forecasting Customer Life Cycle and Value in Retail Industry Using Ensemble of Predictive Models

dc.contributor.guideMalathy, C
dc.coverage.spatial
dc.creator.researcherHarish, A S
dc.date.accessioned2023-07-18T04:51:26Z
dc.date.available2023-07-18T04:51:26Z
dc.date.awarded2023
dc.date.completed2023
dc.date.registered
dc.description.abstractRetail is one industry where the customer s needs and behaviour is newlinediverse and keeps changing with time. The same strategy and action that worked for newlineone may not work for all the others and in fact may not even work for the same newlinecustomer at a different time period. It is also a large scale and highly competitive newlinefield with a complex market presence making it costlier to acquire new customers or newlinereacquire former customers than it is to strategize and invest in engaging the existing newlinecustomers. Therefore, retailers invest a large sum in creating pleasant and engaging newlineshopping experiences that attract customers and keep them coming back. While it is newlinenecessary to devise better retention strategies, it is more critical to target the right newlinebase of customers at the right time to strike a balance in the ratio of cost to revenue newline
dc.description.note
dc.format.accompanyingmaterialDVD
dc.format.dimensions
dc.format.extent
dc.identifier.urihttp://hdl.handle.net/10603/499749
dc.languageEnglish
dc.publisher.institutionDepartment of Computer Science Engineering
dc.publisher.placeKattankulathur
dc.publisher.universitySRM Institute of Science and Technology
dc.relation
dc.rightsuniversity
dc.source.universityUniversity
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Cybernetics
dc.subject.keywordEngineering and Technology
dc.titleForecasting Customer Life Cycle and Value in Retail Industry Using Ensemble of Predictive Models
dc.title.alternative
dc.type.degreePh.D.

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