Recommendation Model
Cross Selling & Up Selling
The right program for each student. Higher engagement, and lower dropout rates.
Our Cross Selling & Up Selling Model allows you to:
Obtain recommendations on programs, atomized by student
Get more students to enroll in the most appropriate career
Improve engagement and improve the level of stickiness on platform
Help more students graduate, reducing attrition rates
Obtain recommendations on programs, atomized by student
Help more students graduate, reducing attrition rates
Get more students to enroll in the most appropriate career
Improve engagement and improve the level of stickiness on platform
Atomized probabilities per entrant and targeted actions recommendation
Better retention rates during the first semester and greater learning experiences
Growth and profitability for the institution
Improve engagement and retention throughout the student life cycle
Anticipate the most frequent causes of dropout and offer the right solution for each student. Identify the most appropriate postgraduate for each person.
Improve engagement and retention throughout the student life cycle
Anticipate the most frequent causes of dropout and offer the right solution for each student. Identify the most appropriate postgraduate for each person.
secured retention points
months implementation
average assertiveness
How do we do it?
We analyze data sources
We elaborate predictions
We recommend actions
Find out how our solution impacts your institution
The machine learning algorithm can significantly improve the personalization of your academic offer
Thanks to data-driven recommendations, your students will get the right offers at the right time, and your institution will increase enrollment and retention rates.
Da el primer paso hacia una transformación digital integral
Product
Ed Machina
