My project consisted of determining a machine learning model to help best segment customers of Imperial into groups of similar behavior.  Customer Market Segmentation is a marketing strategy which involves targeting promotions and benefits to specific customers.  With marketing budgets getting bigger and bigger, optimizing the spend is another way to best improve ROI.  So, this method would help enable Imperial to better target their audience to generate the highest returns on their marketing expenses.

After trying 2 different industry-standard processes (DBSCAN and K-Means Clustering) I found that K-Means clustering cleanly segmented customer accounts and provided an effective way of communicating those results to stakeholders.  This model can be deployed for stakeholders and updated/built further upon for future work.