WISER
Web & Institutional Strategy, Evidence, and Research
WISER is an AI-enabled decision support system I built. It integrates governed institutional sources, operational enrollment evidence, behavioral analytics, live website data, and external search and AI discoverability intelligence to diagnose issues, evaluate priorities, and support evidence-based institutional and digital decisions.
WISER works across
- Institutional governance
- Enrollment evidence
- GA4
- Live website & API data
- SEO & AI visibility
- CMS & sitemap intelligence
Project overview
Explore the WISER system
This overview presents the system architecture, evidence model, analytical framework, and decision-support approach developed for WISER.
Questions WISER is designed to help answer
The system combines different evidence types depending on the question rather than treating every problem as a website or analytics issue.
Institutional Strategy + Prioritization
Connect digital evidence, institutional priorities, enrollment and
lifecycle patterns, and strategic opportunities.
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What are the highest-priority opportunities across the available
institutional, enrollment, behavioral, digital, and discoverability evidence? -
Where do institutional priorities, observed user demand, and
current digital experiences appear least aligned? -
Which findings represent isolated issues, and which indicate
broader structural or strategic problems?
Web Experience + Conversion Diagnostics
Evaluate journeys, navigation, routing, page structure, CTAs,
engagement, and progression paths.
-
Where does the website show the strongest evidence of progression
or conversion friction? -
Where does navigation reflect institutional taxonomy more than
observed user intent? -
Which repeated UX or routing issues are strong enough to treat as
template-level problems?
Programs + Enrollment Intelligence
Connect program structure, behavioral evidence, enrollment patterns,
pathway demand, and portfolio context.
-
Which programs or pathways deserve attention when behavioral,
enrollment, and strategic evidence are considered together? - Where is learner demand stronger than public visibility or pathway clarity?
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How well do program experiences communicate audience, eligibility,
modality, requirements, and next steps?
SEO + AI Discoverability
Evaluate organic search, AI visibility, citation ecosystems,
authority signals, structured data, and discoverability gaps.
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Where are the largest gaps between search visibility, user demand,
program relevance, and institutional priorities? -
Where are competitors or third-party sources appearing in
AI-generated answers instead of institutional sources? -
What content and authority improvements could strengthen both
traditional search and AI retrieval visibility?
Governance + Content Intelligence
Validate public presentation against governance sources, live
program information, policy, and institutional taxonomy.
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Where does public website content materially differ from
authoritative institutional sources? -
Which governance-required distinctions should be preserved but
presented more clearly? -
Are there signs of version drift between governed information,
live operational data, and public presentation?
Implementation + Measurement
Inspect CMS structure, APIs, sitemap health, analytics
instrumentation, data quality, and measurement gaps.
-
Which measurement limitations or data-quality issues could affect
confidence in the analysis? -
What important user journeys cannot currently be measured well
enough to support confident decisions? -
What CMS, taxonomy, sitemap, structured-data, or implementation
issues should be prioritized?
Evidence before interpretation
WISER separates direct observations from evidence-grounded interpretations and recommendations. It applies source-purpose rules, identifies material evidence gaps, preserves institutional governance distinctions, and communicates confidence where inference is required.
Diagnosis
Interpretation
Priority
Action