Customer Data Clustering using Data Mining Technique

Details Customer Data Clustering using Data Mining Technique Customer Data Clustering using Data Mining Technique

2011-12-09

arxiv.org/abs/1112.2663v1

International Journal of Database Management Systems ( IJDMS ) Vol.3, No.4, November 2011

Computer Science

Databases

11 pages, 2 figures and 1 table

Scientific paper

10.5121/ijdms.2011.3401

Classification and patterns extraction from customer data is very important for business support and decision making. Timely identification of newly emerging trends is very important in business process. Large companies are having huge volume of data but starving for knowledge. To overcome the organization current issue, the new breed of technique is required that has intelligence and capability to solve the knowledge scarcity and the technique is called Data mining. The objectives of this paper are to identify the high-profit, high-value and low-risk customers by one of the data mining technique - customer clustering. In the first phase, cleansing the data and developed the patterns via demographic clustering algorithm using IBM I-Miner. In the second phase, profiling the data, develop the clusters and identify the high-value low-risk customers. This cluster typically represents the 10-20 percent of customers which yields 80% of the revenue.

Affiliated with

Also associated with

No associations

Rating

Customer Data Clustering using Data Mining Technique does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Customer Data Clustering using Data Mining Technique, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Customer Data Clustering using Data Mining Technique will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-381881