A note on attribution. Pacific Agency Group is a composite case study drawn from several engagements we’ve run with personal lines P&C agencies in the $2–3M book range. Numbers are representative of typical outcomes, not a single named client. Full NDA-attributed case studies are available on request — email hello@renewalengineai.com.
The agency
Pacific Agency Group is a representative independent P&C agency in the Southwest. At engagement start:
- Book size: $2.5M in personal lines premium (auto, home, umbrella).
- Policy count: ~350 households, concentrated in a three-state footprint.
- Team: 1 agency principal, 2 producers, 2 CSRs. No marketing hire.
- AMS: Applied Epic. Epic had been in place for 6 years; carrier downloads were clean but client contact data was inconsistent (phone type unflagged, mobile vs. landline mixed).
- Lead sources: Local SEO, Google Ads, 3 referral partners, and a legacy aggregator contract.
What was breaking
The principal had noticed retention drifting. Not a collapse — a slow bleed. His own numbers from Epic, pulled in the audit week:
| Metric | Pacific’s baseline | Industry reference |
|---|---|---|
| Renewal retention | 82% | Top-quartile independents: 92%+ |
| Median lead response time | 47 hours | Winning agencies: under 5 minutes |
| Quote-to-bind ratio | 28% | Well-run agencies: 35-50% |
| Clients contacted 60+ days pre-renewal | ~23% | Target: 95%+ |
| After-hours leads answered the next business day | 62% | Target: < 5% |
The pattern was classic reactive workflow. Producers were quoting; they weren’t following up. Renewals were getting pulled out of Epic the week before expiration instead of 60 days ahead. The CSRs were absorbing service load in a way that left no time for retention work.
The principal had asked three vendors for proposals before us. Two were CRMs asking him to do the work himself. The third was a call center. He wanted the outcome without buying another piece of software.
What we built (Weeks 1-3)
The Audit surfaced exactly where the leaks were; the Build & Launch shipped the four systems that closed them.
1. AI renewal engine (Applied Epic integration)
We pulled the nightly renewal list from Epic via the Applied API, enriched each household with 24 months of claim history and engagement signal, and ran the four-touch cadence from the renewal automation playbook against the full book.
- Touch 1 (Day 60): Email acknowledging the upcoming renewal, rate context, and an open question — "Anything changed on your end since last year?"
- Touch 2 (Day 30): Personalized preview with the carrier’s preliminary renewal premium, rate-shock framing where premium was up > 8%.
- Touch 3 (Day 14): Channel switch (text if Touch 1–2 were email). Producer-paged for silent clients.
- Touch 4 (Day 7): Last-chance producer call list, ranked by risk.
Every outbound message was drafted in the agency principal’s voice. The CSRs reviewed the first 100 drafts before we let the queue run autonomously.
2. Instant lead response (under 60 seconds)
Every inbound source — web form, phone, referral email, ad click — flowed into a normalized queue and got a personalized first response in 30–60 seconds. The response referenced every field the lead filled in and offered three specific calendar slots. Details in the instant lead response article.
3. Quote follow-up automation
Every open quote got a 21-day, 7-touch sequence until bind-or-decline. Personalization included carrier, stated premium, and the producer’s voice.
4. Operations dashboard
Weekly retention, response time, and pipeline metrics rendered in a single page the principal could check Monday morning.
90-day results
We ran Managed Ops from Week 4 onwards, tuning classifiers weekly. The numbers at the 90-day mark:
| Metric | Baseline | Day 90 | Change |
|---|---|---|---|
| Renewal retention (rolling 30-day) | 82% | 94% | +12 points |
| Median lead response time | 47 hrs | 38 sec | −99.98% |
| Quote-to-bind ratio | 28% | 41% | +13 points |
| Clients contacted 60+ days pre-renewal | 23% | 98% | +75 points |
| After-hours leads with same-day engagement | 38% | 97% | +59 points |
Revenue impact (first 90 days)
- 47 additional retained policies vs. the projected baseline retention trajectory.
- 13 additional binds from quote follow-up that would have gone cold.
- Estimated incremental premium retained/captured at 90 days: $46,000.
Annualized over the first 12 months, the model projects $187,000 in recovered annual premium — roughly 7× the total first-year engagement cost.
12-month outlook
At the 12-month mark, the composite pattern we see across similar engagements:
- Retention holds in the 93–95% range with tuning.
- Producer time freed up from cold follow-up gets reinvested in cross-sell and referral relationships, adding another 6–10% book growth.
- Managed Ops ongoing cost ($2,500/mo = $30,000/yr) offset roughly 6× by retained + net-new commission.
What the principal would say
From the representative post-engagement conversation with the agency principal:
"The part I didn’t expect was how much time my CSRs got back. We weren’t even looking at lead response time as a problem. It turned out to be the single biggest revenue miss. The renewal lift is great, but the time I got back from my team is what made this actually pay for itself."
Why it worked (and where it could have failed)
Three factors mattered:
- Clean enough AMS data. Pacific’s Epic data wasn’t pristine, but the email and mobile fields were populated on 85%+ of households. Below 60%, the engagement would have started with a data-cleanup sprint instead of a build.
- Principal bought in on tone review. The first 100 messages were reviewed by the principal. This is the step agencies skip and then complain the AI "sounds like AI." Tone review is not optional.
- Managed Ops kept the classifiers honest. Weekly tuning caught two classifier drifts in the first 90 days — one where rate-shock language over-triggered, one where the producer-paging threshold was too loose.
Is this realistic for your agency?
Pacific’s numbers are achievable for agencies in the 200–600 policy range with at least moderately clean AMS data and a principal willing to invest an hour a week in the first month on tone + classifier review.
Agencies below 150 policies typically don’t have enough volume to justify the Build & Launch price tag yet. Agencies above 1000 policies see larger absolute revenue recovery but the same percentage lift.
The free audit is the right first step — 5 days of actual assessment against your real book, ending in a proposal with numbers specific to your agency. Read how it works for the process.
This is a composite case study. Numbers and names are representative of typical engagements, not a single named client. Full NDA-attributed case studies available on request.