Spread across 30 office locations and with nearly 2,000 employees, this multi-disciplinary civil engineering firm desired an innovative approach to deliver on an enhanced customer experience, retention, and project success. They wanted to know when a customer was at-risk for churn due to dissatisfaction with an engagement. Pulling data from a number of sources (Dynamics ERP for project information, UltiPro HR for staff linkage to projects, Defender Endpoint for internal staff file access telemetry, Exchange Online for communications, etc…) we built a machine learning model that ingested and correlated all these sources, performed sentiment analysis on the communications, and was able to predict at the 30% project milestone whether a project was trending towards success or failure, allowing project managers to step in and better manage expectations and customer experience.
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