Case Study — Prospect Segmentation & Rep Fit

Their best rep ranked third in their biggest segment

We grouped 2,420meetings from an EdTech sales team into segments by what prospects said on the intake form, then laid each rep's close rate over every segment. The team's highest-volume closer won one segment outright and ranked third in the largest one, where another rep closed 23 points higher. No single rep was best everywhere.

The takeaway: routing every lead to your "best" rep quietly underfills the segments where someone else closes more.

5
Segments found
from intake answers
23pt
Close-rate swing
in the biggest segment
765
Prospects
in the top segment
+55.2%
Revenue lift
modeled, routing + shielding
2,420 meetings analyzed5 segments from intake forms52.9% blended close rateReps anonymized
The setup

Same leads, one routing rule: round-robin

MedLeague books pre-med students into sales calls off a single intake form. With round-robin assignment, every prospect was spread evenly across the team, so each segment landed on strong-fit and poor-fit reps in equal measure. The blended close rate looked healthy at 52.9%. The blend was hiding who actually closed what.

The real data

Close rate by segment, by rep

The same five reps, working five segments off identical inbound demand. Read it down a column and the rep-fit jumps out: nobody is best at everything.

Segment (prospects)Rep ARep BRep CRep DRep E
Pre-Med Research Beginners
765 prospects
45%n=114
68%n=33
49%n=36
36%n=31
24%n=125
Cancer Research Explorers
447 prospects
50%n=61
31%n=20
42%n=35
26%n=17
20%n=72
MCAT-Stage Research Seekers
390 prospects
37%n=66
49%n=18
12%n=15
20%n=22
15%n=71

Close rate by prospect segment, for prospects who completed the intake form. The best-fit rep in each segment is outlined. Rates are empirical-Bayes smoothed; per-cell sample sizes (n) range 15 to 125. Rep A is the team's highest-volume closer.

Why 'route to your best rep' loses money

The same rep wins one segment and trails in another

Biggest segment

Pre-Med Research Beginners

765 prospects, the largest pool and the one that drives the most revenue. Rep B closes it at 68%. Rep A, the team's highest-volume closer, manages 45% here and ranks third. Routing this segment by rep rank instead of rep fit leaves roughly a quarter of its winnable deals on the table.

Then it flips

Cancer Research Explorers

In the next-largest segment, the order reverses. Rep A closes it best at 50%, while Rep B, who dominated the beginners, drops to 31%. There is no single "best rep" to route everything to. Fit is a property of the pairing, not a line on the leaderboard.

This is the pattern segment-aware routing is built to catch: send each segment to the rep who actually closes it, and the same team converts more from the same pipeline. The deeper logic is in our write-up on prospect segmentation and rep fit.

What it's worth

The gap is the opportunity

The segment-by-rep gaps above are measured. Closing the routing and reliability gaps they expose, applied to MedLeague's real numbers, models out to +55.2% in annual revenue, about $150,793, from the same booked demand and the same 28.1% no-show rate they started with. The full revenue model, with the no-show side included, is in the original MedLeague case study.

See your segments with your data

Import your scheduling history and we'll segment your prospects, lay each rep's close rate over every segment, and show you which pairings are quietly costing you, in minutes.

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