Volume : VII, Issue : VI, June - 2017
On–line Retail Business Mining for Effective Identification of Potential Customers in E–Commerce
D. Sridevi, Dr. A. Pandurangan, Dr. S. Gunaekaran, Dr. A. Kumaravel
Abstract :
We tackle the problem of identifying the potential customer for E–commerce through online retail business. The complexity of prediction becomes challenging especially when the customers are in the remote places, while launching any product in the appropriate market segments, the main issue is to cut cost while customer base is huge which cannot be mentioned easily. Hence in this paper, we recommend a set of data mining algorithms for analysing the pattern of purchases and arriving at optimal model for making recommendations for the possible potential identifiers. Likelihood is measured using Bayes scheme and applied to find the maximum probability attached with each customer’s record. This will support the decision making on budget for customer relationship management.
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DOI : 10.36106/ijar
Cite This Article:
D.Sridevi, Dr.A.Pandurangan, Dr.S.Gunaekaran, Dr.A.Kumaravel, On–line Retail Business Mining for Effective Identification of Potential Customers in E–Commerce, INDIAN JOURNAL OF APPLIED RESEARCH : Volume‾7 | Issue‾6 | June‾2017
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D.Sridevi, Dr.A.Pandurangan, Dr.S.Gunaekaran, Dr.A.Kumaravel, On–line Retail Business Mining for Effective Identification of Potential Customers in E–Commerce, INDIAN JOURNAL OF APPLIED RESEARCH : Volume‾7 | Issue‾6 | June‾2017
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