What If Your Metrics Only Make Sense When It’s Too Late? Why traditional success metrics arrive too late to guide enrollment decisions. March 2, 2026 Most enrollment teams are not failing because they lack effort, expertise, or budget. They are struggling because the way success is measured no longer aligns with when enrollment decisions actually […]

Visibility That Drives Confidence: Inside the New Standard for Enrollment Marketing Decisions Jan 7, 2026 The pressure starts even before the enrollment cycle begins. Budgets have to be approved, campaigns have to be planned, and presidents and boards want answers before results arrive.   In recent years, enrollment marketing has quietly shifted from a volume game to a visibility game. […]

Cygnus Marketing Communications Earns SOC2 Type 2 Certification, Affirming Commitment to Data Security in Higher Ed Enrollment Marketing Feb 9, 2025 Originally Published in GlobeNewswire, HigherEdDive, and MarketingDive. Certification validates that Cygnus’ controls are not only in place—they are working effectively to protect sensitive student and institutional data. Cygnus Marketing Communications, Inc. (“Cygnus”), a leader […]

Why Enrollment Systems Fail Without an Operational Blueprint Aug 19, 2025 By Marcelo Parravicini Originally Published in MarTechView Colleges struggle with enrollment due to siloed systems and lack of integration. Success needs a clear operational plan that unifies teams, data, and processes. Picture a house built one room at a time by separate teams. The […]

Why Data Security Is Vital in Higher Ed Marketing May 29, 2025 By Daniel T. Rehn Originally Published in NextTech Today Higher ed marketing runs on data – but without strong security, trust, and compliance, enrollment efforts can collapse. Here’s why it’s time to rethink your stack. Higher education marketing today is a high-stakes ecosystem. […]

Garbage In, Garbage Out: The Importance of Data Management in Higher Education Originally Published in EdTech Magazine Universities must tighten the quality of the data entered into AI models to improve the output generated by tools such as chatbots. Universities have been cautious adopters of artificial intelligence. As they address data-management challenges while shoring up […]