Othot’s cloud-based, student success solution is here to support your retention and persistence programs to ensure students graduate on time with manageable debt and a promising post-graduate future.
Visualize predictions and data to quickly understand enrollment projections and share with key stakeholders.
Othot gives customers a dashboard where they can see “Likely to Persist” scores updated dynamically, from the day they enroll through freshman year and beyond.
Use prescriptive analytics to see which actions will have the greatest impact on an individual student’s likelihood to persist and graduate.
View predictions at the individual student level and see what’s influencing their likelihood to persist.
Othot’s advanced machine learning models build the most accurate predictions for your data set by augmenting academic data with other factors critical to retention.
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An Othot advisor will give you a tour of the product and show you key features in the platform.
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After you sign the contract, our Customer Success Team will get you set up in the platform. This process can be completed in as little as 60 days.
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Our Customer Success team will help you get the most out of Othot’s intuitive platform so you can meet your goals.
One of our customers is using the Othot platform to predict the likelihood for student success and retention. Insights from the platform revealed that for previously enrolled students, basic requirements of academic success in the first year were an indicator for student retention. The finding prompted the institution to begin evaluating applied and admitted students on both their enrollment likelihood and on their expectation for success and retention.
Othot’s platform was created to take the cost and complexity out of predictive analytics. Our models are built from scratch for each customer to identify which students are most likely to persist and which interventions are predicted to increase the probability of graduation. We build and deliver our models quickly, so you’re up and running in weeks, not years.
Typically, we onboard customers in 60 to 120 days. We work with our customers to create a timeline that fits their needs.
No, our models are customized for each institution. The first step in our process is to identify the “High Impact Questions” (HIQs) that matter most for your school, such as, “What is the likelihood that a student will enroll?” Then our team creates a machine learning model built around answering that question. Othot’s predictive engines also combine a school’s historical data with external data and can be customized to create predictions for a school’s unique “What-If” scenarios, such as specific campus visit types or scholarships.
This proprietary approach produces predictive intelligence that offers a more comprehensive solution than other analytic programs.
We recommend that you have two to three years of historical data student data to build a model. In addition, we also source external data to build your models. External data includes demographic, socio-economic, geographic, environmental and behavioral.
We release updates to our software several times a year and schedule the updates to minimize disruptions to our customers. We communicate with our customers often about the new releases and provide detailed instructions and notes on all new features in the platform.