CollegeAPPs utilizes proprietary predictive analytics algorithms to create a dynamic adult learner database, enabling educational institutions to identify and target potential students effectively. This approach enhances recruitment and enrollment strategies for community colleges, universities, and workforce development teams by providing actionable insights into the adult population.
Funding
Funding not disclosed
Founders
Product
Problem
Educational institutions face challenges in identifying and reaching adult learners who are likely to enroll in their programs. Traditional marketing methods often rely on broad demographic data, leading to inefficient recruitment efforts and wasted resources. It is difficult to pinpoint individuals with a genuine interest in continuing education and align them with specific institutional offerings.
Solution
CollegeAPP provides a data-driven solution that enables educational institutions to identify and target adult learners with a high probability of enrolling. By conducting large-sample surveys and applying machine learning predictive analytics, CollegeAPP creates a dynamic database of adult prospects with demonstrated educational intent and program preferences. This allows institutions to move beyond generic demographic targeting and engage with individuals who are genuinely interested in their specific programs. The platform aggregates person-level data, enabling institutions to create efficient and equity-focused outreach campaigns through various channels, including digital marketing and direct mail.
Target Audience
The primary target audience includes community colleges, technical colleges, four-year universities, and career colleges seeking to enhance their adult learner recruitment and enrollment strategies.
Features
- Predictive modeling of adult learner intent based on large-sample surveys and machine learning
- Individual-level data on over 249 million US adults, including demographics, educational attainment, and program preferences
- Segmentation capabilities to target prospects based on factors such as age, gender, ethnicity, and income
- Program-level interest models to align prospects with specific institutional offerings
- Interactive dashboard for campaign management and performance tracking
- Integration with digital marketing platforms and direct mail services
- "Last Move" parameter to identify and target adults who are new to a community