Education group predicts enrollments from Facebook with 97% accuracy
StrataTech Education Group focuses on the education, growth, and development of specialized career education schools, particularly skilled-trade programs designed to address the nation’s growing infrastructure needs.
StrataTech wanted to better understand the relationship between its Facebook marketing spend and student enrollments the social media channel generated.
The education group challenged us to produce a reliable return on investment (ROI) student enrollment model for its Facebook marketing.
Using enrollment and social media marketing spend data, uncover patterns to understand how closely they can be correlated.
Our team analyzed both month-to-month enrollment data compared to marketing spend and year-over-year enrollment data compared to marketing to spend.
The data was plotted to uncover an enrollment to marketing spend pattern for each campus (see charts).
Data Collection & Analysis
Because student enrollments lag behind marketing efforts, finding a direct correlation between Facebook marketing spend in any given month to enrollments in any given month can be difficult.
Month-to-month Facebook marketing spend to enrollment predictability is 47%.
Dots represent enrollments. The closer the dots to the coefficient line, the closer an enrollment to marketing spend attribution can be made.
Year-over-year Facebook marketing spend to enrollment predictability becomes 97%.
As an example, the model below can predict expected enrollment lift from increasing the annual Facebook budget from $100,000 to $120,000.
Dots represent total enrollment. The closer the dots to the coefficient line, the closer an enrollment to marketing spend attribution can be made.
Cost Per Lead
Cost Per Enrollment
Higher Facebook lead volume
Consistent Facebook lead volume
Fully tracked leads into CRM
StrataTech Education Group now has a model for predicting expected enrollment based on Facebook lead generation budget changes with 97% accuracy. The education group uses this model to predict enrollments by campus and for scouting new campuses locations.