Commission Plan, Cherry-Picking and an Untouched Aged File
Vantage Insurance Services runs a 30-agent inside sales team with about 12,000 leads a month. Inbound web leads are 35% of volume and convert at 14%; aged purchased leads are 65% and convert at 1.8%. Agents earn a $400 base plus $18 per sale, with no differentiation by source. Aged leads sit an average of nine days before first touch, and 62% are never dialed at all. Inbound leads are worked within 11 minutes on average. Overall conversion is 6.1% against an 8% target. Leadership is considering a $10 spiff per aged-lead sale. Two top agents account for 31% of aged-lead sales and both say the spiff is the only reason they would touch the file. The CRM records disposition codes inconsistently, and no-answer and bad-number are often logged as the same code.
1. Decompose the 6.1% conversion figure. Where is the gap to 8% actually coming from, and is the commission plan the cause?
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Start with the mix math. Inbound is 35% of volume at 14% conversion, contributing 4.9 points. Aged is 65% at 1.8%, contributing 1.17 points. Total 6.07%, which matches the reported 6.1%. So the current number is exactly what the mix and current effort predict; nothing mysterious is happening.
Now test the target. Holding the mix fixed, reaching 8% would require aged leads to convert at about 6.1% or inbound at roughly 19.5%. Neither is credible. So the target is not reachable by exhortation or by small plan tweaks.
The real lever is coverage. If 62% of aged leads are never dialed, then the 1.8% is diluted across the whole file. Among the 38% that are dialed, conversion is 1.8 divided by 0.38, about 4.7%. If the undialed 62% performed at that same 4.7% when worked, aged sales would rise by roughly 227 a month, taking total conversion from about 6.1% to about 8.0%. That single lever closes the gap.
So the commission plan is a contributing cause of avoidance, not the root cause. The root causes are first-touch latency of nine days on aged leads, no accountability for coverage, and a disposition taxonomy that hides whether an attempt even happened.
2. Design a replacement incentive plan with numbers. How would you avoid paying for dials that never reach a human?
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Pay for what you actually need: qualified conversations on aged leads, plus sales, with quality gates. Keep the $400 base to protect stability.
Proposed structure:
- Inbound sale: $14, slightly reduced because inbound demand is assigned, not created.
- Aged-lead sale: $38, reflecting the harder work and the lower close rate.
- Qualified aged conversation: $3, defined as a live contact of at least 60 seconds with a decision-maker, logged with a valid disposition. This is the key addition because it pays for the behavior that precedes sales.
- Quality gate: incentive is forfeited on any sale later found to have a false disposition, fabricated attempt, or suppressed-number contact.
Cost check using the coverage scenario: about 227 incremental aged sales at $38 is roughly $8,600 a month, plus conversation pay if agents generate, say, 3,000 qualified aged conversations at $3, which is $9,000. Total around $17,600 against incremental revenue from 227 sales. Run the margin per sale before committing; if it does not clear, lower the conversation rate to $2 and keep the sale rate.
The $10 spiff alone is the wrong instrument: it rewards a sale outcome that depends on contact, so agents will dial the easiest slice of the aged file and ignore the rest. Paying for qualified conversations spreads effort across the file.
3. What CRM and monitoring changes are needed to make the new plan work and to catch gaming?
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The plan fails if the data cannot distinguish a real attempt from a fake one, and right now it cannot because no-answer and bad-number share a code.
Rebuild the disposition taxonomy: no answer, busy, voicemail left, bad number, wrong party, gatekeeper, callback scheduled, not interested, qualified conversation, sale, do not call. Make disposition mandatory at wrap and validate it against dialer result codes so an agent cannot log a connected call as no answer. Bad-number dispositions should trigger a data-quality queue rather than a silent discard.
Monitoring set: first-touch latency by source, percent of aged file dialed within 48 hours, attempts per lead, qualified conversations per paid hour, sale rate per qualified conversation, and disposition distribution by agent. The last one is the gaming detector; an agent with an unusual spike in bad numbers or voicemail is either cherry-picking numbers or rushing.
Audit weekly: 25 randomly sampled records per agent checked against dialer logs and call recordings. Look for short connects logged as conversations, repeated dialing of suppressed numbers, and reassignment of inbound leads to oneself.
Dashboards should be visible to agents so the coverage target is not a secret. Coach on first-touch speed and conversation quality, and review the plan after 60 days against the actual aged-lead lift.