A data mining framework for product and service migration analysis |
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Authors: | Siu-Tong Au Rong Duan Wei Jiang |
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Institution: | (1) Rue Crespin 20, 1206 Geneva, Switzerland |
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Abstract: | With new technologies or products invented, customers migrate from a legacy product to a new product from time to time. This
paper discusses a time series data mining framework for product and service migration analysis. In order to identify who migrate,
how migrations look like, and the relationship between the legacy product and the new product, we first discuss certain characteristics
of customer spending data associated with product migration. By exploring interesting patterns and defining a number of features
that capture the associations between the spending time series, we develop a co-integration-based classifier to identify customers
associated with migration and summarize their time series patterns before, during and after the migration. Customers can then
be scored based on the migration index that integrates the statistical significance and business impact of migration customers.
We illustrate the research through a case study of internet protocol (IP) migration in telecommunications and compare it with
likelihood-ratio-based tests for change point detections. |
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Keywords: | |
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