The Tippie Analytics Cooperative works with national and international brands to creatively solve some of the most challenging problems facing business today. Our clients come from nearly every industry vertical and represent organizations of all sizes. Review some of our past projects to learn how an engagement with the Tippie Analytics Cooperative can help.

Kum & Go logo

Loyalty card insights – Kum & Go

A team of Tippie business analytics students translated over 20 million rows of transactional data into behavior-driven shopper segments. Their insights revealed opportunities to grow revenue through targeted offers and promotions that increase basket size and the frequency of shopper visits.

  • Tools: R, Tableau
  • Technique: Cluster Analysis

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BMO Transportation Finance

Roll off prediction - BMO Harris Transportation Finance

Tippie’s data analysts worked with over twelve million cells of data in order to build a month-by-month predictive model for “roll off.”  (Roll off is an industry term for business that will “roll off” the books in the future.) Paired with new business projections, accurate roll off projections provide BMO Harris Transportation Finance with critical insights used for operational planning across the organization.

  • Tools: R, RStudio, Rattle
  • Techniques: Decision Tree, Survival Analysis

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College Raptor

Predictive models for college match and admissions - College Raptor

Tippie analysts evaluated hundreds of thousands of data cells and built predictive models that work around noisy data and predict probability of application and enrollment.  The results were ranked and showed 90% of the positive results were found in the top three deciles of the prediction. The resulting models help admissions teams identify the best candidates on which to focus their recruiting dollars.  

  • Tools: R, RStudio, Rattle, Tableau
  • Techniques: Decision Tree, SVM, Logistic Regression, Lift Charts

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Paperless Transactions

Credit card fraud detection - Paperless Transactions

The Tippie Analytics Cooperative worked with millions of data records provided by Paperless Transactions in order to reveal important behavioral indicators of fraudulent activity in online donations and giving. The insights revealed by this engagement provide Paperless Transactions with the validation and insights they need to begin developing the next generation of fraud detection for their products. 

  • Tools: R, RStudio, Rattle
  • Techniques: CRISP-DM, Decision Tree

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Ruffalo Noel Levitz

Higher education fundraising optimization - Ruffalo Noel Levitz

The Tippie Analytics Cooperative analyzed hundreds of thousands of rows of data to develop predictive models for call pickup and donor giving, two components of an analytics-heavy product innovation strategy for Ruffalo Noel Levitz’ next generation phone-a-thon product. The insights revealed in this engagement will allow Ruffalo Noel Levitz to offer their clients a significantly better ROI on their campaigns than the scaled calling approaches of the competition.

  • Tools: R, RStudio, Rattle
  • Techniques: Decision Tree, Random Forest, SVM
University of Iowa Hospitals and Clinics

Patient no-show prediction - University of Iowa Hospitals and Clinics

Analysts from the Tippie Analytics Cooperative worked with historical appointment data to build models that accurately predict patients who are unlikely to show up for their scheduled appointments. By understanding the no-show probability of a patient, the organization can optimize physician utilization, avoid slack time and provide scheduling managers the information they need to optimize physician and clinic schedules.

  • Tools: R, RStudio, Rattle
  • Techniques: Decision Tree, SVM, Random Forest, Profit Curves
University of Iowa Hospitals and Clinics

Patient flow and optimization - University of Iowa Hospitals and Clinics

Students from the Tippie Analytics Cooperative massive amounts of patient encounter data to reveal bottlenecks and opportunities as patients arrive and flow through the multiple engagements that constitute an appointment. These insights will help UIHC improve the patient experience by driving operational efficiencies, optimize staffing and streamline patient visits. 

  • Tools: R, RStudio, ExtendSim
  • Techniques: Value Stream Mapping, Simulation Models

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