Due to scattered data, BOB Autowas was not able to derive valuable insights from the existing database to understand why certain customers cancel their subscriptions. To help the company overcome this barrier, we first integrated all customer data from different platforms into Churned AI engine and created a unified dashboard that has real-time customer insights. Important metrics, such as customer health scores, key churn factors, and churn risk rates were essential to help BOB Autowas understand how churn rates of various customer segments differ from each other. This implementation saved the company from time-consuming and repetitive manual work, such as categorizing customers and searching for specific numbers. Further, by leveraging the machine learning power, BOB Autowas was able to identify the effectiveness of the carry-out marketing campaigns, and how these campaigns affect churn rates in the long run. For example, our solution demonstrated that even though offering a free one-month subscription attracts many new customers, 70% of these customers were lost over the subsequent six months. BOB Autowas needed precise data-driven insights to drive retention actions instead of “intuitions”, and Churned helped them achieve that. These insights not only enabled BOB Autowas to uncover the actual effects of their marketing actions but also predict the customer lifetime value of the newly acquired clients. In addition, we worked with BOB Autowas to set up A/B tests in their active campaigns which target customers in the high-risk segments and optimize their strategy to minimize churn and maximize retention. We were also proud to be able to incorporate our analytical results for BOB Autowas into the Google BigQuery environment and feed Active Campaign, a marketing automation tool with churn predictions.