The RaiseMe Likelihood to Apply (LTA) Score calculates the likelihood a student on RaiseMe will apply to any college/university. This article will walk you through how the LTA is calculated, the different models that your institution can use to improve the scores and will provide information on how to utilize the LTA scores.
The LTA Score
The Likelihood to Apply Score combines the score from CampusLogic’s likelihood model with student-reported statuses from the RaiseMe site to calculate a final LTA score. The individual student LTA scores are updated daily (M-F) to reflect ongoing student activity.
There are two likelihood models: the generic model and the custom model.
Both models use a combination of the following data sources:
- data from RaiseMe website on students’ achievements, demographics, college interactions, as well as their viewing and following behavior
- college properties
- US census data
- data from colleges/universities on enrollment outcomes
If your institution has not submitted data to CampusLogic from the previous admissions cycle, the LTA score uses the generic model.
If your institution submits data from the previous admissions cycle, the LTA score will use the custom model using the school-specific data, which improves the accuracy of the score.
You can find instructions for uploading data through the College Portal here:
Student-reported statuses are translated into numerical scores that are based on an analysis of actual results provided by our college partners. Student-reported statuses include:
Final LTA Score = Proprietary algorithm combining score from likelihood model + student status score
Using LTA Score to Inform Enrollment Strategy
When should I use the LTA score in RaiseMe?
Use the RaiseMe LTA score to qualify students you plan to download and pull into your CRM for further engagement.
Why should I use the LTA score?
While your institution has likely adopted RaiseMe as an innovative way to engage with prospective students early, it can be tricky to incorporate RaiseMe follower data into your existing workflows since the term “follower” might not fit neatly into your existing model. Use the LTA score to distinguish between followers that fit into your model as prospect/suspect, inquiry, highly interested, etc., without diluting your inquiry pool.
How can I use the LTA score?
The following ranges are recommendations for categorizing and downloading followers based on LTA score:
- LTA Score < .1 = prospect/suspect
- LTA Score ≥ .1 = inquiry
- LTA Score ≥ .7 = highly interested
The RaiseMe dashboard highlights ‘highly interested’ students with LTA scores of .7 and above. Follow up with these students is recommended:
- Filter and download the highest scoring students to focus campus and budget resources
- Consider encouraging these students to apply as part of a call/text campaign or app gen campaign