HSBC and Ayasdi used Topological Data Analysis (TDA) and machine learning (ML) to automatically assemble self-similar groups of customers and customers-of-customers. This exercise was done entirely unsupervised, with Ayasdi's software making the selection of the appropriate algorithms, creating candidate groups and tuning the scenario thresholds within those groups until the optimal ones were identified. In this case, the platform automatically normalized the data columns and combined multi-dimensional scaling and single linkage clustering algorithms to create the topological model. This was then passed through an agglomerative hierarchical clustering algorithm which was optimized to produce balanced segments.