Predicting your yield on acceptances can be a daunting task, especially for someone new to the admissions office. The yield on acceptances is determined by the number of students who enroll after being accepted, divided by the total number of offers or acceptances sent out during the admissions cycle. For example, if you sent out 100 acceptances and 70 students matriculated, the yield on acceptances would be 70%—70 divided by 100 equals 0.70, which, when converted to a percentage, equals 70%.
To navigate the complexities of yield prediction and enhance your strategy, consider the following key factors, each examined over multiple years—preferably four or five. Fewer years may be considered if recent events, such as the COVID-19 pandemic, have significantly impacted the admissions process.
1. Overall Number
Start by calculating your overall yield percentage: total number of enrolled students divided by the total number of acceptances. This provides a baseline from which other variables can be analyzed.
2. Gender Breakdown
It is common to have a varying yield based on gender. For example, one gender may consistently have a higher yield rate than the other, leading to different outcomes each year. Understanding these trends can help in predicting and balancing future admissions.
3. By Each Division
If your institution has multiple divisions—such as preschool, elementary, middle, or high school—it’s crucial to analyze yield data separately for each division. Different divisions may exhibit unique trends and require distinct strategies to optimize yield.
4. By Grade Level
When dealing with limited spaces, particularly in lower grades, predicting yield by grade level becomes vital. Over-enrolling by even a few students in grades like kindergarten could negatively impact the class dynamics or, in the case of preschool, trigger legal requirements such as hiring additional teachers.
5. By Rating
If you use consistent matrices to evaluate students, rating can be one of the most significant predictors of yield. Students who rate higher on your evaluation criteria may have a lower likelihood of enrolling, particularly, when the acquisition of students is highly competitive for your school.
6. Aided vs. Non-Aided Students
More often than not, students receiving financial aid yield at a higher rate than full-pay students. It’s important to separate these two segments to better understand their impact on overall yield and to tailor your strategies accordingly.
7. Other Special Segments
Beyond gender, there are other segments worth tracking, such as students of color, athletes by gender, geographic areas, legacies, international candidates, siblings, religious affiliation or top picks. These segments can offer deeper insights into yield trends and help in refining your approach.
8. Special Programs or Interests
Students with specific interests—such as basketball players, debaters, or vocalists—may yield higher based on the strength of your programs in those areas. Tracking these groups can help identify opportunities to bolster enrollment or understand weaknesses within your program.
9. School Affiliation
Strong affiliations with particular feeder schools can also influence yield. Tracking students from these schools provides data on your brand’s strength or weakness within those institutions and may inform your outreach and engagement strategies.
10. Offer Timing
The timing of your offers can significantly impact yield, especially if you are competing with schools that have a stronger brand or larger reach. The availability of spaces at the top branded schools gets filled, which may move your school up the pecking order.
Conclusion
By systematically analyzing these factors, you can improve your ability to predict yield and develop more effective admission strategies. Each of these elements contributes to a deeper understanding of the variables that impact yield, enabling you to make data-driven decisions that align with your school’s enrollment goals.
