OutcomesIQ: Your Evidence-Based College List Builder
The goal: Move from "this feels right" to "this is evidence-backed." By the end of an OutcomesIQ session you should have a more balanced list, clearer confidence in each school's role, and fewer decisions made on instinct alone.
Overview: The Three-Phase Review
Think of an OutcomesIQ session as three connected moves:
- Diagnose — See how your current list holds up against real outcomes
- Investigate — Drill into the evidence behind individual schools
- Act — Add, remove, and adjust based on what you find
The sections below walk through each feature in the order you'd naturally use it.
Getting Started: Opening OutcomesIQ
- Navigate to Counselor list and select the OutcomesIQ tab
- Results load automatically when you open the tab
Why this matters: You're switching from list management to list strategy. Everything on the Counselor List tab is your working draft — OutcomesIQ lays an evidence layer on top of it so you can see how that draft holds up against real-world outcomes.
Step 1: Read the List Balance
At the top of OutcomesIQ, your student's schools are grouped into outcome-based categories:
| Category | What it means |
|---|---|
| Net | 70%+ acceptance rate among similar students |
| Fit | 35–69% acceptance rate |
| Reach | 10–34% acceptance rate |
| Lottery | Under 10% acceptance rate |
| Insufficient data | Fewer than 5 similar outcomes — treat as unconfirmed |
- Fit labels are calculated using only students with at least medium similarity (70+ threshold)
- This means you're always comparing your student to a relevant pool, not the full applicant universe
Why this matters: A list can look well-rounded on paper but still be overweighted toward risk. The balance view lets you spot in seconds if a student has too many Reach/Lottery schools and not enough Fit/Net anchors — before it becomes a problem in the spring.
Step 2: Review Disagreement Flags
- When your manually assigned label and OutcomesIQ's data-derived label don't match, the UI flags that school for review
- Flags appear inline on the affected school card
Why this matters: These are your highest-leverage review points. A school you labeled "Target" might be showing Reach-level outcomes for similar students — or a school you've treated as a Reach may be more accessible than you thought. Resolving disagreement flags is where counselor judgment and real data meet.
Step 3: Evaluate a School Not Yet on the List
- Use the "Evaluate another school" search at the top of the OutcomesIQ view to test any college without adding it to the list first
- The school appears in a dedicated Evaluating section until you dismiss it or formally add it
Why this matters: You often want to test a school before committing to it. This gives you a low-friction way to run a trial — see how similar students performed there, review the evidence, then decide. It's the difference between adding a school on instinct and adding it with a reason.
Step 4: Toggle Your Students vs. Network
Use the data source toggle to switch between two outcomes pools:
- Your students — outcomes from students you've personally worked with; more calibrated to your counseling context
- Network — outcomes from all students across the CounselMore platform (100,000+ records); broader sample size
Why this matters: Your own data is more personally relevant; the network gives you depth when your own pool is thin. If you're newer to counseling or working with an unfamiliar student profile, the network gives you the confidence of a much larger data set. If you're experienced with strong historical data for this student type, your own pool may be more precise. Using both lets you cross-check.
Step 5: Expand a School Card
- Click any school card to expand it and see student-level outcome rows
- Each row represents a real similar student who applied to that school, with their outcome (accepted / waitlisted / denied)
Why this matters: The fit label gives you the headline. The expanded rows give you the story. You can see the range of profiles that got in, where denials clustered, and whether your student sits near the top or bottom of that range. That context changes how you present the school to a family.
Step 6: View a Full Student Profile
- Click View profile on any student row to open a side-by-side comparison modal
The modal includes:
- Academic metrics (GPA, SAT/ACT)
- Course rigor by subject area
- AP tests and scores
- Activities, with shared items highlighted
- Self-assessment comparison
- Languages
- That student's outcomes at other colleges
- From the modal, you can also add colleges to your student's list directly
Why this matters: A similarity score tells you two students are alike — the profile modal tells you why. When you can see that a matched student had the same activity profile, similar course rigor, and was admitted to three of your student's target schools, that's the kind of evidence that builds real counselor confidence and helps you explain your reasoning to families.
Step 7: Add or Remove Schools
- Each school card includes Add to list (if not yet on the list) or Remove from list (if already on it)
- Changes take effect immediately on the Counselor List tab
Why this matters: Insight only matters if it changes the plan. These controls let you convert your analysis into real list movement while the evidence is in front of you — not later, when you've lost the thread.
Step 8: Fill In Missing Data
If a student row is missing key fields — GPA, test scores, major, outcome — you'll see Update links on your own students' rows.
Two ways to fill gaps:
- AI Assist — paste or upload existing data and let AI extract and pre-fill fields for your review
- Manual entry — directly enter GPA, SAT/ACT, major, outcome, and other profile fields
- Click Save & refresh results to update OutcomesIQ recommendations immediately
Why this matters: OutcomesIQ is only as good as the data behind it. Missing profile data reduces similarity confidence and can cause schools to appear as "Insufficient data" when they shouldn't. Filling gaps improves recommendations for this student and strengthens the model for future students — your data contributions make the tool better over time.
Setting Your Counselor Label
- After reviewing OutcomesIQ's recommendation, you can set or adjust your own label for each school
- OutcomesIQ recommends; counselor judgment finalizes
Why this matters: Data is an input, not a verdict. You know context the model doesn't — a family's financial situation, a student's personal connection to a school, a coach relationship. OutcomesIQ gives you a rigorous baseline so your overrides are intentional and informed, not accidental.
What a Strong OutcomesIQ Session Looks Like
A successful review ends with:
- Every school having a clear, evidence-backed role on the list
- Disagreement flags resolved or documented with a rationale
- At least a few alternatives tested via "Evaluate another school"
- Student profile data as complete as possible
- A list distribution that matches your risk strategy for that student
How Similarity Is Calculated
OutcomesIQ scores each historical student against your current student across multiple factors:
- Test scores
- Course rigor (years per subject)
- AP tests and scores
- Activities
- Self-assessment profile
- GPA
Scores display as High, Medium, or Low. Only students with at least medium similarity are included in fit-band calculations. If fewer than 5 qualifying matches exist for a school, it shows as Insufficient data — OutcomesIQ won't surface a fit label when the evidence base is too thin to be reliable.