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dc.contributor.advisor Premaratne SC
dc.contributor.author Wickramasekara VSW
dc.date.accessioned 2021
dc.date.available 2021
dc.date.issued 2021
dc.identifier.citation Wickramasekara, V.S.W. (2021). e-Learning product sales prediction using SMS activation data [Master's theses, University of Moratuwa]. Institutional Repository University of Moratuwa. http://dl.lib.uom.lk/handle/123/20430
dc.identifier.uri http://dl.lib.uom.lk/handle/123/20430
dc.description.abstract Most companies nowadays using data mining techniques and algorithms for the decision-making process and to make profitable adjustments in operation and production. This helpful to identifying possibilities of a customer buying products after buying a particular product, identifying a group of customers who’s in the difficulty in the activation process/ identifying customers who are going to drop from the company/ how it effects for the company, identifying connection between customer purchasing methods, find the group of customers to promote particular product/s and forecasting the product sales process (required quantity of each product for special annual events like exhibitions). Understanding of consumers helps companies to sell more. Customers are a valuable source of information, collection of data that organizations identify different customers and observe how they behave. The more knowledge about consumers and their different needs, it is easier to identify market opportunities to sell and invent new products and target consumers with appropriate offers. Use of company past data, production and operations can predict using data mining techniques and algorithms. en_US
dc.language.iso en en_US
dc.subject E-LEARNING PRODUCT SALES en_US
dc.subject CONSUMER BEHAVIOR en_US
dc.subject CUSTOMER PURCHASING METHODS I en_US
dc.subject NFORMATION TECHNOLOGY- Dissertation en_US
dc.subject COMPUTER SCIENCE - Dissertation en_US
dc.title e-Learning product sales prediction using SMS activation data en_US
dc.type Thesis-Abstract en_US
dc.identifier.faculty IT en_US
dc.identifier.degree Msc. in Information Technology en_US
dc.identifier.department Department of Information Technology en_US
dc.date.accept 2021
dc.identifier.accno TH4556 en_US


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