Use Cases · For Student Success

For Student Success Leaders

Focus teams on the right students at the right time. Infinize helps advisors and student success teams identify risk earlier, coordinate support, and scale proactive outreach across the student journey, so interventions happen faster and retention improves.

AI-Powered Risk Identification flags at-risk students early

Unified Student View across academic, engagement, and support signals

Actionable Success Insights with next-best actions by cohort

Advisor Workflow Automation to scale caseloads

Retention Intelligence to monitor trends and measure impact

FERPA-compliant with student consent management

What you'll care about

Late identification of at-risk students

Critical warning signs are often discovered after academic performance has already declined. Risk cohorts auto-update daily so you see risk sooner, before it's too late.

Unsustainable caseloads

Advisors struggle to deliver meaningful one-to-one support at scale. Automation handles routine responses and follow-ups so teams support more students with the same FTEs.

Fragmented student data

Student information is spread across multiple systems, limiting visibility and action. A unified student view brings academic, engagement, and support signals into one profile.

Reactive support models

Teams spend time responding to issues instead of preventing them. Next-best actions and playbooks help you prioritize proactive outreach across the student journey.

Impact Metrics

Outcomes you can measure

Earlier risk detection

Identify students who need support sooner, with pilot cohorts surfacing risk in time for timely intervention.

Reduced advisor preparation time

Spend less time gathering information and more time helping students, returning 15–25% of advisor time for complex cases.

Higher student engagement

Strengthen meaningful connections between students and support teams through timely, relevant outreach.

Improved retention

Increase persistence and student success outcomes, with +1–2 percentage point gains in pilot cohorts.

Mini-ROI (illustrative)

Earlier risk detection: identify students who need support sooner

15–25% advisor prep time back from workflow automation

+1–2 pp retention in pilot cohorts within 1–2 terms

Workflow

How it works for your team

From insight to action in three steps

01

Identify

Risk models flag students who missed registration, have DFW risk, or low credit velocity. Cohorts update daily with owner assignments.

02

Act

AI recommends playbooks and drafts outreach (email, SMS, appointment invite). Advisors review, edit, and send in one click.

03

Measure

Track engagement rates, case resolution time, and cohort outcomes. Adjust playbooks based on what moves retention and completion.

Dashboards

Success dashboards

Start each day with a briefing on cohorts needing attention, emerging equity gaps, and which playbooks are working

Strategic view

High-level insights for leadership and planning.

Risk cohorts with action coverage and SLA countdowns

DFW hotspots and tutoring impact by gateway course

Credit velocity and progression bands by cohort or modality

Operational view

Move from insight to execution, see outstanding nudges, appointments, and plan adjustments along with accountable owners.

Action effectiveness and conversion by playbook

Advisor caseload balance and automation lift

Next-best actions surfaced by impact and student consent status

Trust & Equity

Human-centered, secure, and equitable

AI that augments your team without replacing judgment or ignoring fairness

Human-in-the-loop

Advisors stay in control, AI drafts and recommends

Explainable rationale and linked sources for actions

Playbooks reviewed and approved by your team

Privacy & equity

FERPA/GDPR aligned; PII minimization by role

Bias checks on models and interventions

Audit logs for prompts, retrievals, and actions

FAQs

Frequently asked questions

Ready to focus your team on the students who need help now, and prove what's working?

See how Infinize helps Student Success teams improve retention and scale impact