Find Your Fit: MBA School Selection Session
Most applicants pick MBA programs by ranking, then reverse-engineer a "fit" story for each one. That's how you end up applying to 8 programs you can't actually distinguish in a 200-word essay. Instead, let's work together to figure out what you actually want (e.g., options for your career path, geographical preferences, community, network), then let the school list emerge from that. The MBA Scorecard is a tool I built for this, and something we'll leverage here too. It's a weighted spreadsheet across five dimensions, pre-populated with 50+ programs, scored 1–10 with weights 1–5. You fill it in once and it ranks every program live by composite Fit Score. This package this resource to practical use (and we can it without using the Scorecard too). After our session, you'll leave with direction, and a much more clear-eyed view of where you fit. • FIND YOUR FIT — $469 · 1 hour. The core 60-minute session. You can complete the MBA Scorecard as pre-work if you prefer (~30 min on your end). We meet live, walk through it, pressure-test your top 7, and walk through some material I'll have prepared for you on how to think through differentiating the feel of these top programs. This version gets you from thinking "I'm looking at M7 in general plus a couple safety schools" to a more targeted school list you'll feel more excited to apply to over the next few months. • FIND & LOCK — $938 · 2 hours. Find Your Fit + a 60-minute follow-up session ~1 week later. Between sessions you finish out or refine your Scorecard, do targeted school research (visits, alumni outreach, club deep-dives), and come back with sharper inputs. The second hour locks the final list and identifies the strategic angle for each school. Most applicants want this if they haven't talked to alumni yet. Best for: applicants in pre-application stage who haven't locked their school list — or have a tentative list they don't fully believe; people who got the rankings memorized but can't articulate why GSB vs. Wharton vs. Booth for THEM specifically; career switchers, especially function-pivoters, who need to weight programs by real placement, not just brand. Not a fit if: you already have a locked school list and want help on essays / interviews instead (book those packages directly); you're 18+ months out from applying (too early to do this productively); you only want me to confirm your existing list — I'll push back if it doesn't make sense, and you should want that.
What's included
I send the MBA Scorecard (Excel) and a short framework brief the day you book. You spend ~30 minutes filling it in before our call — weighting categories, setting geographic preferences, scoring your top programs. The live hour is camera-on, screens shared. We open your Scorecard and interrogate it together — where your weights are off, which programs you've under- or over-scored, what the rankings get wrong for your specific career path. By 0:55 you have a directional list of stretches, targets, and fits, with explicit rationale for each. If you're on Find & Lock or Full Strategy, we book the follow-on sessions as part of intake. Between sessions, async questions via message are fine. Live calls outside the booked package are billed at my standard hourly rate. The Scorecard belongs to you afterward — keep iterating on it as you learn more about each program. The whole point is that it stays accurate as your understanding gets sharper.
- A completed MBA Scorecard — weights, geographic preferences, fit scores across 50+ programs, live composite ranking, all customized to you
- A directional school list with stretches, targets, and fits — pressure-tested live and ready to defend in interviews
- A clear-eyed view of where you actually fit, plus next steps: what to research, where to visit, who to talk to before R1
Meet your expert
Ben L.
4x Top MBA Coach | 400+ M7 Admits | xSpeechwriter | GSB '21
• Stanford GSB Alum, Class of 2021 -- see relevant background & experience below: • Coaching | Advised 400+ admits into Stanford GSB, HBS, Wharton, Kellogg, MIT Sloan, INSEAD, Haas, and more (230+ Leland reviews), while teaching multiple courses through Leland • What I'm Doing Now | Based in NYC, building a publication 'Staying Human', working on a stealth, marketplace startup, coaching and playing chess profssionally, and advising a slate of Seed to Series C startups through Elevate LLC • Public Policy | Prior to Stanford, worked on the Policy Team for the Chicago Mayor's Office under Mayor Rahm Emanuel, focusing on 5G infrastructure policy, criminal justice policy, and citywide corporate/economic development deals • McKinsey | Before policy, worked at McKinsey & Co , with casework focused on job training for the formerly incarcerated and workforce development for at-risk youth • PE / VC / Startup Advising | After Stanford, worked in Bain's Private Equity Group on various due diliegences, managed deals with several venture capital firms, and advised multiple startups on growth and go-to-market strategy • Professional Writing | Speechwriting in public policy & political environments, Lead Editor for Nondisclosure (Stanford GSB's magazine) and Managing Editor for the Stanford International Policy Review • Additional Writing | Crafting op-eds, ghostwriting for major publications, developing a fictional short story collection, policy deep dives, a book on chess applications to life, and application essays of all sorts • GMAT / Test-Taking | Scored in the highest percentile of GMAT test-takers, but more importantly I've honed my ability to help others extrapolate top test-testing strategies in the areas they're weakest • Additional Coaching Details | 5+ years experience working with >750 individuals on essay writing and resume professionalization for top consulting firms, MBA programs, execs, and the broader job market • Interview Training | I was interview-trained with McKinsey, helping me give high-quality mock interviews for MBBs and any MBA program; I've also held 10+ events through Leland on interview prep for McKinsey's PEI and GSB's interview process in particular
