Built per student from unstructured phone, email, and text conversations
Outcomes forecast from personas plus behavioral signals
Raw communications turned into data-driven engagement strategies
An education re-enrollment company helping students return to and complete higher education was sitting on a rich but underused asset: phone, email, and text conversations with prospective and current students. The signals about who each student was, what they needed, and how best to coach them were embedded in those conversations, but the data was unstructured, fragmented, and not modeled in any form a system could act on.
The company wanted to turn those interactions into a coaching strategy informed by real understanding of each student, rather than coarse segmentation or static rules.
OneSix designed and built a custom data warehouse and analytics platform that ingests and transcribes phone, email, and text conversations across higher-ed institutions nationwide, alongside student enrollment data from each partner school.
Natural language analysis surfaces the substance of each conversation, including a student's relationships with family, work, school, and finances. From those signals, the platform extracts relationship valence and builds a four-dimensional persona for every user, the foundation for understanding what a student actually needs from their coaching relationship.
A prediction layer then combines personas with behavioral signals to forecast student enrollment outcomes, giving coaches and program leaders a data-driven view of who is likely to persist and where coaching can be most effective. Raw communication data is now an asset the company can act on at scale, accelerating the company's product roadmap and replacing intuition with evidence in engagement strategy.
More to explore
OneSix enabled the client to launch a scalable, self-service BI platform within six months, doubling ARR and empowering customers with advanced, on-demand analytics capabilities.
OneSix developed an AI-powered computer vision system for Sunsweet Growers, automating prune inspection with real-time defect detection while preserving high product quality standards.
OneSix developed a machine learning platform for a food distributor, enabling restaurants to optimize ingredient ordering, reduce waste, and enhance profitability through data-driven inventory management.