How Beyond Maybe actually works
Personalization tools usually hide their math. Ours is simple enough to explain on one page, including what it can't do.
How student evidence is collected
Everything starts from what a student explicitly shares: an adaptive conversation of about seven essential questions (interests, academic picture, home, distance, campus, budget, dealbreakers), plus optional follow-ups that appear only when relevant, athletic questions only after a student mentions competitive college athletics, testing questions only for juniors and seniors. Sensitive topics (identity, household income, circumstances) are optional modules, asked only where they unlock aid, and never inferred from other answers.
Minimum evidence for personalization
Beyond Maybe shows personalized pathways or school categories only when a profile has at least one interest signal, one academic signal, and two preference signals. Below that threshold, students see clearly-labeled examples to react to, not “matches”, and a list of exactly which missing information would sharpen results.
How unknowns are handled
A skipped question stores nothing. No home city means no distance math and residency stays “unknown”; no budget means no affordability claims. Unknown preferences never act as exclusions, and skipping optional questions never lowers a match or a completion score.
Where schools and careers come from
- Careers: the U.S. Department of Labor's O*NET database, tasks, skills, education levels, pay, and outlook, connected to programs of study through the official O*NET-to-CIP crosswalk.
- Schools: a small, hand-verified starter set plus live search of the U.S. Department of Education's College Scorecard covering every accredited US institution. Personalized matching currently draws on the starter set; live search results are labeled as live federal data, not personalized recommendations. We say this plainly because the full national matching system is still being built.
How matching is calculated
Scoring is deterministic, the same answers always produce the same results. Schools are evaluated on separate components (program alignment, academics, cost, location, campus, support), each shown with its own strength dots rather than blended into a single mystery number. Categories (“strong possibility,” “possible,” “reach,” “highly selective”) come from comparing a student's shared record against each school's published admitted ranges.
Why results are not guarantees
Admissions decisions involve essays, recommendations, institutional priorities, and luck, none of which any tool can see. A category compares your record with historical published data; it is not your personal probability, and a general admission rate is not your personal chance.
How financial values are classified
Every cost figure carries a classification: official (published by the school or federal government), average (federal reporting across students), or calculated estimate (our math, with assumptions stated). Published tuition is never mixed with average net price; missing values read “not published” instead of guesses; estimates state that they are estimates and never claim to be offers.
Restricted-eligibility opportunities
Scholarships tied to identity, circumstances, or residency appear only when a student's own optional answers make them relevant, they add money to a list and never affect school matching.
Known limitations
- Personalized matching does not yet evaluate every US institution or program, that national system is in development, and we won't claim it early.
- Program-level data (which schools offer which specific programs) is verified only for the starter set today.
- Cost estimates depend on the most recent federal reporting year, which lags real prices; always confirm with the school.
Corrections
Something wrong or outdated? Email hello@beyondmaybe.org. We review flagged data, correct what fails verification, and note review dates on every content page.
Judge it yourself
The fastest way to evaluate a methodology is to watch it refuse to guess.
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Last reviewed September 8, 2026 by the Beyond Maybe team. Spot an error? Email hello@beyondmaybe.org and we’ll correct it.