Custom Outreach Messages: Top 5 Named Accounts

Campaign: Insurance Broker Lead Intake Automation
Use case: First-touch LinkedIn connection/DM for Shepherd, Scott, Starkweather, Houchens, BMB
Last updated: 2026-02-04

These are custom 1:1 messages that reference specific documented pain points from the research report. Do NOT use generic templates for these 5 firms.


1. SHEPHERD INSURANCE (~$74M, Carmel, IN)

Pain Point

Failed LLM/RAG pilot. Publicly documented: “Non-deterministic,” “unreliable,” “hype has not lived up to expectations.” Manual underwriting is “laborious and painful.” 4-day submission-to-proposal lag.

Target Personas

  • Head of Operations / COO
  • Hiring manager for Personal Lines Account Manager roles

Message Option A: Direct LLM Failure Acknowledgement

[CONNECTION REQUEST]

Hi [Name], saw your team at Shepherd tested LLMs for underwriting intake. We built the solution you were looking for — task-specific, cited, no hallucinations. Would love to connect.

[FOLLOW-UP MESSAGE — 5-7 days after connection]

[Name], appreciate the connection.

I saw your team documented the LLM pilot — “non-deterministic outputs,” unreliable table extraction. You rejected it for the right reason. Generic AI trained on everything doesn’t work for precision tasks like insurance.

We built what you needed: task-specific automation trained only on intake workflows. Every extraction is cited (page, section, timestamp). No guessing, no hallucinations.

Your 4-day submission lag × 50 leads/month = 200 hours of manual work. We turn that into 20 hours.

Can I show you the deterministic IDP approach in a 15-minute demo? Would love to walk through how we solve the exact problem your pilot couldn’t.


Message Option B: Hiring Manager Angle

[CONNECTION REQUEST to hiring manager]

Hi [Name], saw you’re hiring Personal Lines Account Managers at Shepherd. We automate the intake workflows that create the bottleneck. Would love to connect.

[FOLLOW-UP MESSAGE]

[Name], thanks for connecting.

I noticed Shepherd is hiring multiple Account Managers — Naples, Sarasota, Bedford — and I understand why. Your intake process requires staff to “gather prospective underwriting information by carrier,” which I’m guessing means logging into multiple portals and re-keying data.

Your team tested LLMs to automate this and hit the reliability wall. We built the cited, task-specific alternative.

Quick question: If you could cut intake from 4 days to 4 hours, would that change your hiring needs?

Happy to show you a 15-minute demo of the workflow.


2. SCOTT INSURANCE (~99M, Lynchburg, VA)

Pain Point

20-hour WIP reports for surety clients (VP quote: “highly manual process”). Manual file shuffling. Hiring Intake Coordinators and Production Underwriting Assistants.

Target Personas

  • VP of Surety / Head of Surety
  • CFO
  • Hiring manager for Intake Coordinator / Production Underwriting Assistant

Message Option A: VP of Surety (20-Hour WIP Hook)

[CONNECTION REQUEST]

Hi [Name], saw your VP mentioned WIP reports take up to 20 hours. We turn that into 20 minutes with automated financial data spreading. Would love to connect.

[FOLLOW-UP MESSAGE]

[Name], thanks for connecting.

Your VP called out the WIP bottleneck: “highly manual process, 20 minutes to 20 hours.” Let’s do the math:

50 contractors × 20 hours each = 1,000 hours/year
At 75,000/year on one task**

That’s half an FTE’s annual capacity spent on report generation — not analysis, not client service, just data entry.

We automate the financial data spreading. Ingest QuickBooks export or Excel WIP → auto-map to surety format → cited output. 20 hours becomes 20 minutes.

Can I show you the workflow with a sample contractor WIP? 15-minute demo.


Message Option B: Hiring Manager (Intake Coordinator)

[CONNECTION REQUEST to hiring manager]

Hi [Name], saw Scott is hiring Intake Coordinators. We automate the manual intake workflows that drive that need. Would love to connect.

[FOLLOW-UP MESSAGE]

[Name], appreciate the connection.

I saw you’re hiring Intake Coordinators — and I understand why. Between the surety WIP bottleneck (20-hour reports) and the benefits file shuffling your team mentioned, the manual workload is overwhelming.

We specialize in automating intake for surety and complex commercial risks. Cited extraction, submission-ready drafts, automated WIP analysis.

If we could cut your intake volume by 50%, would that change your hiring plans?

Happy to show you a quick demo of the workflow.


3. STARKWEATHER & SHEPLEY (~91M, East Providence, RI)

Pain Point

SVP quote: “If I could change one thing, it would be not having to deal with all these spreadsheets and PDFs.” Hiring armies of Assistants. Hiring an Enterprise Architect.

Target Personas

  • SVP Operations (the person who gave the quote)
  • Enterprise Architect
  • Hiring manager for Commercial Underwriting Assistant / Personal Lines Assistant

Message Option A: SVP Operations (Spreadsheet Fatigue)

[CONNECTION REQUEST]

Hi [Name], saw your quote about spreadsheets and PDFs. We turn those into the structured data your Enterprise Architect needs. Would love to connect.

[FOLLOW-UP MESSAGE]

[Name], thanks for connecting.

I came across your comment: “If I could change one thing, it would be not having to deal with all these spreadsheets and PDFs.”

Here’s the problem: You’re hiring an Enterprise Architect to build a modern data foundation. At the same time, you’re hiring Underwriting Assistants to manually process Excel and PDFs. The Architect needs structured inputs; the assistants can’t structure them fast enough.

We sit upstream. Ingest the spreadsheets/PDFs → structure them into your data warehouse → cited, auditable. Your Architect gets the inputs they need. Your assistants focus on exceptions, not data entry.

Can I show you how we turn a messy schedule of locations (Excel) into structured risk data? 15-minute demo.


Message Option B: Enterprise Architect (Data Foundation)

[CONNECTION REQUEST]

Hi [Name], saw S&S hired you to build a data foundation. We automate the ingestion layer — turn spreadsheets into structured inputs. Would love to connect.

[FOLLOW-UP MESSAGE]

[Name], thanks for connecting.

You’re building the data architecture, but your team is buried in spreadsheets and PDFs. Classic “garbage in, garbage out” problem — you can’t build a warehouse without structured inputs.

We automate the ingestion layer. Extract structured risk data from Excel schedules, PDFs, emails → cited outputs with explicit source tracing → feeds into your data transformation.

You design the warehouse; we make sure the inputs are clean before they hit your pipeline.

Can I show you the ingestion workflow in 15 minutes? Would love your technical feedback.


4. HOUCHENS INSURANCE GROUP (~$72M, Bowling Green, KY)

Pain Point

Failed direct bill automation (“complexity of direct bill statements”). Hiring COBRA Processors. 12 offices in 5 states.

Target Personas

  • Head of Operations / COO
  • Sarah Walden, Senior Application Technician
  • Hiring manager for COBRA Processor / Personal Lines Client Associate

Message Option A: Head of Operations (Failed Automation)

[CONNECTION REQUEST]

Hi [Name], saw your direct bill automation fell short due to statement complexity. We specialize in parsing complex carrier docs. Would love to connect.

[FOLLOW-UP MESSAGE]

[Name], thanks for connecting.

I saw HIG’s first automation attempt (direct bill reconciliation) failed because of “complexity of direct bill statements.” That’s a common problem — carriers send statements in 100 different formats, and generic OCR/automation can’t handle the variance.

We specialize in parsing complex, non-standard documents. AI-powered commission reconciliation with cited outputs. We handle the messy statements your last vendor couldn’t.

Plus I noticed you’re hiring COBRA Processors. COBRA is rules-based — perfect for automation. We can handle that too.

Can I show you how we parse a messy carrier statement in 15 minutes?


Message Option B: Sarah Walden (Application Technician)

[CONNECTION REQUEST]

Hi Sarah, saw you manage software across HIG’s 12 offices. We automate intake and reconciliation workflows — reduce the tool sprawl. Would love to connect.

[FOLLOW-UP MESSAGE]

Sarah, appreciate the connection.

Managing software across 12 offices in 5 states is a nightmare when every office has its own manual workflow. You’ve got email, PDFs, local drives, and 5 different carrier portals.

We centralize intake automation upstream of your AMS. One workflow for document ingestion, extraction, and submission-ready drafts. Reduces the “tool per office” sprawl and gives you a single point of management.

Can I show you the centralized workflow in 15 minutes? Would love your technical input.


5. BOWEN, MICLETTE & BRITT (~86M, Houston, TX)

Pain Point

Manual “assembly line”: Processor opens email → Placement Specialist types into carrier websites → forwards for review. Hiring Placement Specialists.

Target Personas

  • Head of Operations / COO
  • Hiring manager for Commercial Insurance Placement Specialist

Message Option A: Head of Operations (Assembly Line Inefficiency)

[CONNECTION REQUEST]

Hi [Name], saw BMB’s placement workflow has two manual handoffs before a quote is generated. We eliminate the typing step. Would love to connect.

[FOLLOW-UP MESSAGE]

[Name], thanks for connecting.

I noticed your placement workflow: Processor distributes lead → Placement Specialist manually types data into carrier websites (“generate quotes online”) → forwards for review.

That’s two manual handoffs and double the labor cost before you even have a quote. And your Specialists (who should be negotiating) are doing data entry.

We automate the submission step. API-first platform: data from intake → pushed to multiple carriers simultaneously. Your Specialists focus on placement strategy, not typing.

Can I show you the API workflow in 15 minutes? One click to push a construction risk to 5 carriers.


Message Option B: Hiring Manager (Placement Specialist)

[CONNECTION REQUEST to hiring manager]

Hi [Name], saw you’re hiring Placement Specialists. We automate the manual quote generation step so your Specialists can focus on strategy. Would love to connect.

[FOLLOW-UP MESSAGE]

[Name], appreciate the connection.

I saw you’re hiring Placement Specialists — and I understand why. Your workflow requires them to manually “generate quotes online” by typing into carrier portals. That’s a $75K/year human doing a bot’s job.

We automate the submission step. Your Processor hands off the lead → system pushes to carriers via API → Specialist reviews quotes and negotiates. No more manual typing.

If we could cut manual quote generation by 80%, how many more accounts could your current team handle?

Happy to show you a 15-minute demo of the workflow.


Multi-Threading Strategy

For each of the Top 5 firms, reach out to BOTH:

  1. Decision-maker (Head of Ops, COO, VP of Surety, etc.) — budget authority
  2. Hiring manager (whoever is posting the Assistant/Coordinator/Specialist roles) — confirms the pain

Why this works:

  • Hiring manager validates the operational bottleneck (“Yes, we’re drowning”)
  • Decision-maker has authority to sign the deal
  • If one doesn’t respond, the other might
  • If both respond, you have internal champions at two levels

Coordination:

  • Space outreach by 2-3 days (decision-maker first, then hiring manager)
  • Reference the hiring in the decision-maker message (“Saw you’re hiring Coordinators — I understand why”)
  • Don’t mention each other in initial outreach (avoid appearing overly aggressive)

Timing & Follow-Up

Week 1 (Days 1-2)

  • Send connection requests to all Top 5 decision-makers
  • Log in HubSpot

Week 1 (Days 3-5)

  • Send connection requests to all Top 5 hiring managers
  • Log in HubSpot

Week 2 (Days 8-12)

  • Send follow-up messages to connected decision-makers
  • Send follow-up messages to connected hiring managers

Week 2-3 (Days 10-15)

  • Respond to replies
  • Offer demo
  • Log outcomes (interested / not interested / no response) in HubSpot

Response Handling

If they say “We already tried automation and it failed”

Response:

“Exactly — that’s why I reached out. The automation you tried (LLMs, generic OCR) fails on precision tasks because it’s trained on everything. We’re task-specific, trained only on your workflow. Every extraction is cited. No hallucinations. Can I show you the difference in 15 minutes?”

If they say “We don’t have budget right now”

Response:

“Totally understand. Quick question: if you’re hiring [Assistants/Coordinators] at 70K each, and we could eliminate 1-2 of those roles, would that free up budget? Our pilot pricing for early customers is designed to be ROI-positive from day one.”

If they say “Send me more info”

Response:

“Happy to. I’ll send over a one-pager. But honestly, the best way to understand it is a 15-minute demo with your actual data (a sample lead or WIP). Does [Day/Time] work for a quick call?”

If they say “Who else are you working with?”

Response:

“We’re in pilot with [X commercial brokerages / surety firms] right now — can’t share names yet, but happy to connect you with a reference once we’re further along. We’re offering pilot pricing to the first 3 firms who help us build this out. Interested in being a design partner?”