Insights
Long-form articles on admissions intelligence, forecasting, and operating models for Higher Education. Written from operational experience.
How AI Should Be Used in Higher Education Admissions
A principled look at where AI genuinely helps admissions teams — and where it creates risk. For HE leaders evaluating AI-native platforms.
The Unified Student Lifecycle Record | Why It Matters
Why the fragmented data model in UK HE creates operational blind spots, and what a unified student record actually looks like in practice.
Applicant Intent | What Universities Miss
Most CRMs track activity. Very few track intent. Here's what admissions data is actually telling you — and how to act on it earlier.
Admissions Operating Model for Modern Higher Education
The operational blueprint for running a high-performance admissions function: pacing, pipeline, decisions and the tools that support each layer.
Why Traditional CRMs Fail Admissions Teams
Salesforce, HubSpot and generic CRMs were built for B2B sales. Admissions is fundamentally different. Here's where the mismatch creates the most pain.
CRM vs SIS in Higher Education | What You Actually Need
CRM and SIS serve different functions but the gap between them creates chaos. Learn where each belongs and why a unified approach wins.
Pacing in Higher Education Admissions | A Practical Guide
What pacing is, why it matters, how to calculate it weekly, and what to do when you're behind target. The operational guide for admissions leaders.
Forecasting in Higher Education Admissions
How to build a reliable enrolment forecast: data sources, confidence intervals and the difference between a pipeline report and an actual forecast.
UCAS Integration | What Universities Need from Their CRM
UCAS deadlines, equal consideration windows and clearing shape the admissions cycle. Most CRMs ignore them. What a CRM actually needs to support UCAS-driven recruitment.
APEL and RPL in Admissions | Why Most Systems Cannot Handle It
APEL and RPL require academic judgement, structured evidence and clear documentation. Most CRMs and SIS platforms handle them badly. Here is where the friction sits and what needs to change.
Clearing Management | What Institutions Need Beyond the Spreadsheet
Clearing compresses decision-making into days. Most institutions manage it through spreadsheets because their CRM cannot separate clearing from the main cycle or support the speed required.
Admissions Show Rates | Predicting Who Will Actually Arrive
Show rate determines whether a university hits its cohort target. Most institutions cannot predict it because intent signals are fragmented and historical averages hide course-level variation.
What Happens After Enrolment | Why Education Teams Lose Visibility
When an applicant becomes a student, engagement history and support context disappear into CRM and SIS silos. Education teams inherit a name, not a complete picture.
Partner University Admissions | Managing Franchise and Validation Pipelines
Franchise and validation arrangements add complexity most systems ignore. Two institutions, different tools, different processes, fragmented visibility.