SkillsSkill 2 of 5
Qualify on what closes, not what replies
Follow every segment from meetings to won revenue per meeting, and qualify on what closes, not on who replies.
Worked example
Should outbound follow the segment that books the most meetings?
The busiest segment isn’t always the best one. Follow each segment from meetings to won revenue before you point the team at it.
The question
Ledgerwick, a fictional accounts-payable automation platform, scores leads with an AI model trained on who replies and books meetings. It ranks companies with 50–200 employees highest. The head of sales development wants to aim next quarter’s AI outbound there.
| Meetings | Opportunities | Won | Average won ACV ($k) | Median sales cycle (days) | |
|---|---|---|---|---|---|
| 50–200 employees | 300 | 120 | 12 | 14 | 45 |
| 200–1,000 employees | 100 | 60 | 15 | 38 | 75 |
| 1,000+ employees | 40 | 20 | 2 | 95 | 210 |
Invented data. 440 meetings, 200 opportunities and 29 wins in all. Won ARR is wins × average won ACV: $168k, $570k and $190k, $928k in total.
- Head of sales developmentThe small companies reply to everything. The AI SDR books three meetings a day there.
- AEIn the 200–1,000 deals there’s a controller who owns AP and feels every month-end close.
“The AI lead score favors 50–200 employee companies because they book the most meetings. Where would you point next quarter’s outbound, and how would you change qualification?”
Your turn
Say your answer out loud, or jot notes below. Both work. Or skip to the worked answer.
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A strong answer, step by step
Open each step in turn. This is one strong answer, not the only one.
Step 1: Follow the meetings to revenue
What would you do here? Open the move you’d make.
Follow the lead score: 50–200 books 300 of 440 meetings, so that’s where outbound goes.
Tempting, but it misses something. Meetings aren’t revenue. That segment won $168k of $928k, 18%, despite 68% of the meetings.
Go where the deals are biggest: 1,000+ at a $95k average.
Tempting, but it misses something. Size alone ignores win rate and speed: that segment won $190k from two deals with a 210-day cycle.
Trace each segment to won ARR: 50–200 books 68% of meetings but wins 18% of revenue; 200–1,000 wins 61%.
The strong move. Following meetings to revenue shows that activity and value point different ways.
See how a strong candidate says it
“The 50–200 segment books 300 of 440 meetings, 68%, but wins only $168k of $928k, 18%. The 200–1,000 segment books 100 meetings and wins $570k, 61%.”
Why it works: Activity and revenue point different ways, and revenue decides.
Step 2: Compare segments on one unit
What would you do here? Open the move you’d make.
Compare total won ARR: 200–1,000 won $570k, so it wins.
Tempting, but it misses something. Totals depend on how many meetings each segment got. Divide by meetings: about $5,700 for 200–1,000 against $4,750 for 1,000+, much closer.
Divide won ARR by meetings: about $560, $5,700 and $4,750 per meeting, with win rates of 10%, 25% and 10%.
The strong move. A per-meeting unit makes segments of different size comparable.
Compare reply rates, since the AI score already measures those.
Tempting, but it misses something. The score was trained on replies, which is what went wrong. Replies don’t tell you that 50–200 wins about $560 per meeting.
See how a strong candidate says it
“Per meeting, won ARR is about $560 for 50–200, $5,700 for 200–1,000 and $4,750 for 1,000+. Opportunities turn into wins at 10%, 25% and 10%.”
Why it works: Dividing by meetings makes segments of different size comparable.
Step 3: Weigh deal size against sample and speed
What would you do here? Open the move you’d make.
Don’t plan on enterprise yet: two wins is too few, and a 210-day cycle means about seven months to close.
The strong move. It resists the biggest-deal answer while leaving room for more evidence.
Move the team up-market: $95k deals beat everything else.
Tempting, but it misses something. Two wins from 20 opportunities, 10%, is a thin base, and next quarter’s meetings wouldn’t close for about seven months.
Ignore enterprise entirely; it’s too slow.
Tempting, but it misses something. It still wins about $4,750 per meeting, close to the 200–1,000 segment. A small, deliberate effort keeps learning without betting the quarter.
See how a strong candidate says it
“Enterprise has the biggest deals, but two wins is too few to plan on, and a 210-day cycle means next quarter’s meetings wouldn’t close for about seven months.”
Why it works: It resists the second tempting answer: chasing the largest ACV.
Step 4: Change who gets worked, and why
What would you do here? Open the move you’d make.
Keep the score and add SDR capacity for 200–1,000 by hand.
Tempting, but it misses something. The score still ranks 50–200 first, so the AI keeps booking the meetings that won 18% of revenue.
Split outbound evenly across the three segments.
Tempting, but it misses something. An even split ignores that a 200–1,000 meeting wins about ten times what a 50–200 meeting does.
Aim most outbound at 200–1,000 companies with a named AP owner, keep a small enterprise effort, and retrain the score on won revenue.
The strong move. It fixes the cause, a score trained on replies, not only next quarter’s list.
See how a strong candidate says it
“I’d aim most AI outbound at 200–1,000 employee companies with a named AP owner, keep a small enterprise effort, and retrain the score on won revenue, not replies. I’d review it after a quarter of opportunities.”
Why it works: It reaches a scoped decision and fixes the score that caused the problem.
The answer, in short
- Decision
- Aim most outbound at 200–1,000 employee companies, keep a small enterprise effort, and retrain the lead score on won revenue rather than replies.
- Because
- That segment turns a meeting into about ten times the won ARR of the 50–200 segment, with a 25% win rate and a 75-day cycle.
- What would change it
- A cheaper self-serve path that makes small deals pay, or more enterprise wins showing the 1,000+ segment converts reliably.
Common traps
- Optimizing for meetings booked.
- Letting a reply-trained score define the ICP.
- Chasing the biggest ACV on two wins.
- Ignoring sales-cycle length.
Check your answer
- Did I follow each segment from meetings to won revenue?
- Did I compare segments on the same unit?
- Did I treat small samples with caution?
- Did I change how leads are qualified, not just where they come from?
Want feedback on how you’d answer? Practice “Qualify on what closes, not what replies” with an AI interviewer on Socratify.
Last reviewed Nov 9, 2026