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rapid insight webinars Customer Appreciation Week:
Blitz Sessions

Wednesday, July 14, 2 pm ET | 11 am PT Watch the Webinar

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Tune in for Day 2 of Customer Appreciation Week and get inspired by stories from the Rapid Insight user community!

We’ll shine the spotlight on 3 customers as they highlight data projects they accomplished with Rapid Insight’s software.

These 15-minute blitz sessions will inform your work and inspire you to take on new data challenges.

Read about each blitz session below. Scroll down to register!

  • Southern Adventist University wanted to quantify and attribute revenue to specific departments and majors. SAU had partial information, but not in an easily consumable format. In a collaboration between their Enrollment Management and Student Finance departments, SAU used Construct to develop a net revenue attribution model that provides them with the granularity to track the flow of money down to the individual student and faculty members.

    This model allows SAU to explore the financial interconnectivity between programs and departments, and understand the financial impact of cognate and non-departmental courses. Additionally, SAU can now explore scalability and efficiency issues at all levels.

  • Mount Saint Mary’s University administers course evaluation surveys that involve over 50 different course schedules in 4 survey periods. MSMU initially used Excel for the evaluation data, which necessitated a time-consuming, error-prone manual maintenance process.

    When the office of Institutional Planning and Research took ownership of the course evaluations, they automated the process in Rapid Insight Construct. The IPR department handled outliers and planned survey periods around course start and end dates. Now, the process is almost entirely automated, saving time and avoiding errors.

  • When Michael Chavez joined the staff at the University of Texas Permian Basin, he discovered that UTPB’s analysts had the data they needed, but that the school stored the data in separate silos. Using Construct, Chavez merged all queries into a single data source to get at the necessary information. With the data in one place, his team could analyze the data and develop nudge campaigns to increase enrollment, student success, and graduation rates.

    Chavez’s carefully planned campaigns (modeled after tactics used by Netflix, Amazon, and Uber) used k-means analyses to segment students. The team, along with the Marketing and Communication groups, designed tailored creatives and messaging for text, email, and social media communications. The results and yield rates were even higher than expected.

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