Behavioral Intelligence Platform: APPLY
The only application predictive model that integrates machine learning and marketing automation.
Free your staff from the complexity of enrollment predictions with APPLY, one of three predictive modeling products within Capture’s Behavioral Intelligence Platform (BIP). APPLY is managed by a data science team and uses machine learning to predict which students are most likely to apply to your university.
Why APPLY Matters
Minimize uncertainty and reduce spending by using APPLY to tailor and target email, social, digital and direct mail campaigns to likely applicants. The only application predictive model to rank and score suspect an inquiry roles against each other, and based on your data.
An interactive dashboard
featuring student-level applicant rankings grouped by likelihood to apply.
Predictions are updated daily and available for download at any time.
Use all of your search names in conjunction with prior years’ data to identify students who are likely to apply.
Identify students most likely to apply.
APPLY is a data modeling service powered by your search names, in conjunction with your historical data, to predict which of those searched students are mostly likely to apply to your university. Save precious budget dollars on direct mail and other high-cost campaigns by directing your time, resources and marketing dollars to those students who are mostly likely to apply.
APPLY is a managed service. The Capture professionals who will help you get the most out of APPLY include your:
- Date Scientists and Analysts: To run the predictive engine that creates your models, leveraging your institutional and public data sets to help you better apply your time and resources.
- Account Executive: Enrollment experts who serve as the primary contact to create your strategies, assess your performance metrics, and guide the building and implementation of your Partner Success Plan.
- Project Manager: To ensure efficient approval, launch and optimization of the campaigns suggested by your model.