2026 entry
Overview
Price is a key driver of student recruitment and therefore understanding the tuition fee market is paramount during these unprecedented times. Drawing on our own experiences of setting tuition fees and conducting portfolio reviews, we have developed our Course and Tuition Fee Database that is the perfect fit for UK universities.
Get in TouchE2026 Database
S Squared Insights Limited are pleased to confirm our E2026 database – retaining all the benefits of our previous databases and a new, adaptive collection method for identifying 'early publishers' to release fee data earlier than previous years. Some of the key features of our database include:
UG Entry Requirements
Including A-Levels, Tariff, BTEC, T Levels and IB
PGT Entry Requirements
Including IELTS and Degree Classification
Database Primary Key
New Course Identifier
CAH3 and HECoS Subject Codes
For more information, get in touch
Detailed
Launching in 2020, our database was the first to introduce new metrics and fields to standardise fee data after listening to sector feedback.
Our Course and Tuition Fee Database is a comprehensive record UK undergraduate and postgraduate taught higher education courses, including both on campus and online distance learning courses.
We cover over 64,000 variants, awards and courses, complete with specialised data marker fields to make our database useful for the sector and easily compatible with Business Intelligence tools.
Our database includes:
Timeframe
Our database is available three months earlier than is traditionally available to UK Universities, with updated releases available monthly from September. Subject to university fee publication date.
September
First database release of early publishers
January
All Russell Group HEIs
April
All HEI providers
July
All TBC fees updated
Our process
In order to deliver the detailed and timely solution that universities require to effectively conduct fee setting and portfolio reviews, our data science team deploy a 3 stage process to ensure data quality, accuracy and completeness.
Data Collection
Our data science led methodology allows is to collate detailed, accurate data.
Data Cleaning
We use a sophisticated data cleaning method to ensure data integrity and deliver consistent, usable datasets.
Data Checking
We introduce a variety of checking methods to identify outliers to continually adjust our collection methodology.
“The inclusion of the primary keys, and also having the historic data sets with primary keys, will be incredibly helpful in our processing of the data.”
University of Glasgow,
2022