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Due to technology Advancements, relationship marketing has become a reality in recent years. Technologies such as data warehousing, data mining, and campaign management software have made customer relationship management a new area where firms can gain a competitive advantage. Particularly through data mining the extraction of hidden and useful information from a large set databases companies can identify valuable customers, predict future behaviors based on the previous purchase pattern of the customer, and enable companies to make proactive, knowledge-driven decisions.
We propose a system that will help retailers to understand dependencies among goods purchased by the customer , also knowing what good is purchased with the other or if a particular set of goods are purchased so as to maximize profit.
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Abstract should provide a concise summary of the Automated Market Basket Analysis System, including the issue statement, methodology, findings, and conclusion.
Introduction should introduce the Automated Market Basket Analysis System by offering background information, stating the problem, aims, research questions or hypotheses, and the significance of the research.
Literature review should present a review of related literature that supports the current research on the Automated Market Basket Analysis System, systematically identifying documents with relevant analyzed information to help the researcher understand existing knowledge, identify gaps, and outline research strategies, procedures, instruments, and their outcomes.
References section should list out all the sources cited throughout the Automated Market Basket Analysis System, formatted according to a specific citation style.
Others are table of contents, methodology, results, discussion, conclusion, etc…