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Topological Data Analysis (TDA) is a recent approach to analyze data setsfrom the perspective of their topological structure. Its use for time seriesdata has been limited to the field of financial time series primarily and as amethod for feature generation in machine learning applications. In this work,TDA is presented as a technique to gain additional understanding of thecustomers' loyalty for business-to-business customer relationship management.Increasing loyalty and strengthening relationships with key accounts remain anactive topic of discussion both for researchers and managers. Using two publicand two proprietary data sets of commercial data, this research shows that thetechnique enables analysts to better understand their customer base andidentify prospective opportunities. In addition, the approach can be used as aclustering method to increase the accuracy of a predictive model for loyaltyscoring. This work thus seeks to introduce TDA as a viable tool for dataanalysis to the quantitate marketing practitioner.

Topological Data Analysis of Time Series Data for B2B Customer Relationship Management