Why do some collectors convert more right-party contacts than others on the same accounts?
Collection is persuasion, and different people persuade different people. Each collector is stronger with some kinds of accounts than others: one with large, fresh balances, another with older consumers on aged accounts. A floor-wide leaderboard averages those strengths away. Split results by type of account and the differences show.
New to BestPair? See what it is and how it works
Every collector has a strong suit
The idea is old. David Ricardo described comparative advantage in 1817: each person should do the work where their advantage is greatest, not only the work they are best at overall. On a collection floor, a collector who looks average on the leaderboard can be the strongest on aged accounts, on one state or on restarting payment plans.
Gary Becker’s work on matching, from 1973, adds the second half. When the result depends on the pair, sorting well beats ranking. The question changes from "who is my best collector?" to "who is best for this account?"
Who is on the call changes the result
People respond to the person asking. In a field experiment at a Chinese consumer lender, 21% fewer borrowers made a verbal promise to repay when the caller was an AI voice bot rather than a person (Choi, Huang, Yang and Zhang, "How Good is AI at Twisting Arms?", NBER working paper w33669, 2025). If the caller matters that much, which person calls matters too.
What it looks like in the data
- Two collectors with the same overall conversion: one converts far better on small, aged balances, the other on recent, larger ones.
- A collector in the middle of the leaderboard who leads the floor on one age band or one state.
- A top collector whose lead is concentrated on a few kinds of accounts, and who is near the floor average on the rest.
In BestPair’s Sample Report, built on synthetic data from a fictional floor, the best collector collects $194 per account contacted and the weakest $92. Those figures are synthetic. Your own spread comes from your own history, and on some floors it is narrow.
How to check your own floor
- Pull call outcomes and payments, linked to the collector who worked each account.
- Split accounts by type: balance band, age of debt, placement age, state, consumer age band.
- Compare collectors within each type on dollars collected per account contacted, not on raw totals.
- Ignore cells with too few accounts to tell skill from luck.
If the order of your collectors changes from one type of account to the next, routing is leaving money on the table. That is the gap predictive pairing is built to close.
Common follow-up questions
Isn’t it simply that some collectors are better than others?
Some are better overall, but the order changes by type of account. Ranking by an overall average sends your strongest collectors accounts anyone competent would close, while the accounts that needed them go to whoever is next.
How many collectors do you need before the differences are real?
Usually 25 or more. With fewer, too few collectors work each kind of account to tell skill from luck.
What it could mean on your floor
Two minutes
Watch the explainer
What your dialer does with the next account, what pairing changes, and what the Floor Assessment measures. With captions.
Watch the videoYour floor
Try the calculator
Four numbers off your dialer and collections reports give an illustrative figure for your floor. It is at best informed guesswork until your own history is measured.
Open the calculatorA live test
Read the case study
170,000 telecom accounts split at random before the first call, and how the result was counted.
Read it
Would it be a bad idea to spend 45 minutes finding out?
If your shop does not qualify, you will hear it on the call, not after you have paid for a report.
Book a 45-minute fit call