Case Study: Crisis Text Line achieves a 10% capacity boost and five-minute response times with Periscope Data

Crisis Text Line - Customer Case Study

Crisis Text Line is a nonprofit, 24/7 text-based crisis intervention service that has handled more than 70 million messages and trains over 13,000 volunteer counselors. Facing a high volume of unstructured data, they needed to spot real-time crisis trends, reduce texter wait times, and improve volunteer capacity, so they partnered with Periscope Data and its natural language processing and machine learning tools.

Periscope Data helped Crisis Text Line apply topic modeling, build a stack-ranking queue to prioritize incoming messages by severity, and create a self-service data environment for nontechnical staff. As a result, Crisis Text Line saw a 10% capacity boost during peak periods and was able to meet its five-minute wait-time goal more often, enabling plans to double counselors and quintuple conversations; Periscope Data will next be used to forecast trends and train counselors by analyzing keywords and tags.

Crisis Text Line