Three structured analyses
Engagement. Readiness. Yield.
CeliaConnect answers three questions about every student, every day. Each answer is a
structured JSON payload Celia writes back into a dedicated Slate field your counselors
already know how to filter and report on.
Engagement
Is this student paying attention?
What it measures
- Activity signals (logins, opens, clicks, form interactions)
- Response cadence to counselor outreach
- Last-touch quality (channel, content type, recency)
- Channel mix (email, SMS, portal, in-person)
Output
Score 0–100 plus a ranked list of the signal drivers.
Slate field
ss_celia_engagement
72
What the counselor sees in Slate
The counselor opens the record in Slate and sees a score, a timestamp, and the drivers ordered by weight. Filter a list view on "Engagement < 40" to surface the quietly-disengaged pool in seconds.
Readiness
Is this student actually moving forward?
What it measures
- Application completeness
- Missing documents and checklist items
- Days stalled in stage vs. your institutional baseline
- Stage-transition velocity
Output
Score 0–100 plus an ordered checklist of what is missing.
Slate field
ss_celia_readiness
54
What the counselor sees in Slate
The counselor sees a score and a ranked list of gaps — the specific item blocking progress, how long it has been open, and what the institutional baseline looks like. One click from "missing recommendation letter" to the outreach template.
Yield
Is this student going to enroll?
What it measures
- Cohort and program baseline probability
- Financial-aid package stage and timing
- Historical conversion for similar profiles
- Top contributing factors (positive and negative)
Output
Probability 0.00–1.00 plus the top factors driving the number.
Slate field
ss_celia_yield
0.78
What the counselor sees in Slate
The counselor sees a probability against the cohort baseline, with the three factors nudging it up or down. Aggregate yield across a list view rolls up into a funnel-level forecast the director can show the board.
Alongside the three analyses Celia also writes a
Risk rating
(low / medium / high / critical), the specific
Risk Factors driving it, and a one-line
Recommendation for the counselor's next
action.
Examples
What a Celia run looks like the morning after.
Examples use anonymized data consistent with our no-PII architecture.
Engagement
Alex's Engagement dropped from 72 to 38 this week.
Driver: no email opens in 10 days, after a 6-week streak of same-day replies. Celia flags the drop and recommends a lightweight check-in before the drop becomes a disengagement.
Readiness
Jamie's Readiness is 45.
Gap: missing recommendation letter — 8 days overdue against an institutional baseline of 3. Celia recommends a nudge to the recommender, not to the student.
Yield
Morgan's Yield probability is 0.82.
Cohort baseline is 0.65. Boost factors: attended campus visit, financial-aid package accepted early. Celia recommends a light-touch hold strategy — this student is converting on their own.
Want to see the full output?
One student, end-to-end — input, analysis, counselor view.
See the exact JSON Celia receives from your Slate Query Service, the three analyses it
writes back, the risk tier and recommendation — and the per-student cost.
See a sample analysis