FourthRev
How FourthRev unified enrollment data across programs and ad platforms
100+
CRM fields analyzed
3
Ad platforms unified
1
Unified enrollment view
FourthRev is a UK-based education technology company building career accelerator programs in partnership with top universities — including LSE and King's College London — and leading technology companies. Their programs span data science, data analytics, product management, UX design, and digital marketing, combining project-based learning with industry certifications and career coaching. Founded to address the skills gap of the Fourth Industrial Revolution, FourthRev operates across Australia, the UK, and the US, and is actively expanding its program portfolio.
The Challenge
Fragmented enrollment data across CRMs and ad platforms
FourthRev needed a unified view of marketing performance across programs and university partners to optimize spend, improve enrollment attribution, and identify the highest-converting channels by program. Their data landscape made this nearly impossible.
Enrollment and marketing data were siloed across CRM and three ad platforms (Meta, Google, LinkedIn). Inconsistency in lead identifiers across sources made attribution from first touch to enrollment nearly impossible. Variance in data definitions across programs produced misaligned reporting and hundreds of inconsistent fields in CRM.
The Solution
A unified enrollment view powered by e:cue
e:cue integrated all data sources across CRM, ad platforms, and email performance into a single enrollment view. The transformation involved three critical layers:
Standardized lead identifiers : aligning lead IDs across program data sets so first-touch through enrollment can finally be tracked.
Multi-touch attribution logic : mapping each enrollment back to its channel, program, and cohort.
Unified performance layer : reducing fragmented reporting tables into one clean marketing performance layer.
Cue in Action
Clean data powering instant answers
With unified data flowing into Cue, the FourthRev team could ask natural-language questions and get instant, accurate answers. When marketing asked for the average lag from sales-qualified to application submission by program, Cue returned a per-program breakdown with median, average, and actionable next steps in seconds.
The Results
From fragmented partners to a single source of truth
With unified data and Cue's conversational analytics, FourthRev gained a clear, program-level view of how marketing spend converts into enrollments, and where the funnel breaks down between qualification and application.
Channel optimization
Spend rebalanced toward the highest-converting channels by program and cohort.
Staffing-ratios
Enabled updated enrollment staffing ratios to match real lead volume based on lead quality.
Program-level lag
Bottlenecks between SQL and application surface in seconds, ready for targeted outreach.
Multi-touch attribution
Every enrollment mapped back to its originating channel, program, and cohort.
Company
FourthRev
Industry
EdTech / Workforce Training
Use Case
Marketing Attribution, Lead Prioritization
Data Complexity
High