Results / Follow-Up Engine
Case study · Insurance agent · Life, annuities, long-term careA call list that knows who to call next.
An insurance agent was fast at dialing and losing track of everything around it. We built a call-first CRM that tells him who to call next and why. He reports about 20 hours a week back (client-reported).
~20 hrs/weekof manual work saved (client-reported)
+10%revenue in the first 2 weeks (client-reported)
2 daysfrom kickoff to the first live version
1,541policies and 1,184 members brought into one CRM
The situation
He makes around 100 calls on a heavy day into an inherited book. Dialing was never the problem. Continuity was. He couldn't tell at 9am who was worth calling. He forgot what he'd promised, and when. Every conversation started from zero. He was paying an outside appointment-setting service thousands of dollars a year to cover part of it by hand.
His words: "I need to know if they're called, and I need to know if I've connected with them."
What we built
- Call mode. A priority list, and every name shows why it's there.
- One-tap outcomes. Appointment set, callback by date or season, or do-not-bother. The next name comes up.
- Briefings. A short summary of past notes before each call, every fact linked to its source note.
- One clean book. 1,541 policies and 1,184 members from carrier reports and rosters. Possible duplicates are flagged for him to confirm, never merged on their own.
- Reminders and Google Calendar sync on fixed rules.
- Safety. Do-not-call and calling hours live in tested code, not in AI prompts. Built on de-identified data.
- Since launch. Fixes and small changes come straight from his own notes. Live and still improving.
"I like how those notes are helping me now."
The result
- About 20 hours a week back (client-reported)
- Revenue up 10% in the first 2 weeks (client-reported)
- First live version 2 days after kickoff
- The number we track: share of promised follow-ups completed on time
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