Blueprint Playbook for RoofLink

Who the Hell is Jordan Crawford?

Founder of Blueprint. I help companies stop sending emails nobody wants to read.

The problem with outbound isn't the message. It's the list. When you know WHO to target and WHY they need you right now, the message writes itself.

I built this system using government databases, public records, and 25 million job posts to find pain signals most companies miss. Predictable Revenue is dead. Data-driven intelligence is what works now.

The Old Way (What Everyone Does)

Your GTM team is buying lists from ZoomInfo, adding "personalization" like mentioning a LinkedIn post, then blasting generic messages about features. Here's what it actually looks like:

The Typical RoofLink SDR Email:

Subject: Scaling your roofing business? Hi {{FirstName}}, I noticed your company is growing based on your LinkedIn post about hiring new sales reps. Congrats! RoofLink helps roofing contractors like you streamline operations with our all-in-one CRM and field management platform. We offer: • Integrated measurement tools • Mobile-first workflows • Real-time collaboration Would you be open to a quick 15-minute call to see how we can help you scale more efficiently? Best, SDR Name

Why this fails: The prospect is an expert. They've seen this template 1,000 times. There's zero indication you understand their specific situation. Delete.

The New Way: Intelligence-Driven GTM

Blueprint flips the approach. Instead of interrupting prospects with pitches, you deliver insights so valuable they'd pay consulting fees to receive them.

1. Hard Data Over Soft Signals

Stop: "I see you're hiring sales reps" (job postings - everyone sees this)

Start: "Your last permit was filed February 12th in Denton County - that's 67 days ago. IICRC-certified contractors in your area averaged 14 permits per month during that same period." (government permit database with specific dates and comparative data)

2. Mirror Situations, Don't Pitch Solutions

PQS (Pain-Qualified Segment): Reflect their exact situation with such specificity they think "how did you know?" Use government data with dates, record numbers, facility addresses.

PVP (Permissionless Value Proposition): Deliver immediate value they can use today - analysis already done, deadlines already pulled, patterns already identified - whether they buy or not.

RoofLink GTM Plays: Data-Driven Targeting

These plays combine public data sources and proprietary intelligence to identify prospects in specific painful situations. Each message demonstrates precise understanding of the target's current context.

PVP Public + Internal Strong (9.6/10)

IICRC-Certified Opportunity Alert: Active Insurance Claims

What's the play?

Target IICRC-certified restoration contractors in counties with recent water damage insurance claims. Cross-reference their certification status with active insurance claims filed in their service area to deliver a complete lead list they can immediately pursue.

Why this works

You're handing them a list of 89 qualified leads with addresses, claim dates, and insurance carriers - complete actionability. Their IICRC certification is their competitive advantage, and you're showing them exactly where to deploy it for immediate revenue. This is consultation-level value delivered before any sales conversation.

Data Sources
  1. IICRC Certified Firms Global Locator - firm_name, location, certifications
  2. Insurance Claims Database - claim addresses, filing dates, insurance carriers

The message:

Subject: Your IICRC cert + 89 homeowners needing help You're IICRC Water Damage certified - 89 homeowners in Collin County filed insurance claims for water damage in the past 21 days. I pulled the addresses, claim filing dates, and insurance carriers for each. Want the full list with carrier contacts?
DATA REQUIREMENT

This play requires access to insurance claim filing data integrated with property records to extract addresses and carrier information by county and claim type.

Combined with public IICRC certification records. This synthesis creates unique targeting intelligence.
PVP Public + Internal Strong (9.5/10)

Multi-State Expansion Intelligence: Tornado Damage Mapping

What's the play?

Target contractors with multi-state licenses who aren't actively working one of their licensed states. Deliver complete tornado damage intelligence for their untapped market: damage path visualization, active insurance adjuster contacts mapped to carriers and claim volume patterns.

Why this works

You're removing every barrier to market entry. They have the license but haven't expanded - you're handing them a complete opportunity map with adjuster contacts they can call today. This is strategic consulting delivered as sales outreach. The specificity (May 2nd, Cleveland County, 234 claims, 5 carriers) proves this isn't generic market research.

Data Sources
  1. NOAA Storm Events Database - event_date, location, event_type, tornado path coordinates
  2. Insurance Adjuster Activity Database - adjuster names, employer carriers, claim volume by territory
  3. State Contractor License Data - multi-state license holders

The message:

Subject: Oklahoma tornado map with adjuster contacts The May 2nd tornado path through Cleveland County OK has 234 active insurance claims filed. I mapped the damage path, pulled adjuster names from 5 major carriers, and matched them to claim volume. Want the tornado map with adjuster contact info?
DATA REQUIREMENT

This play requires insurance adjuster activity data showing which adjusters are working specific storm events, their employer carriers, and claim volume patterns. This data must be synthesized with NOAA tornado tracking.

This combination of public storm data with insurance adjuster intelligence creates proprietary targeting value.
PVP Internal Data Strong (9.4/10)

Insurance Approval Benchmarking: ZIP-Level Pricing Intelligence

What's the play?

Target contractors operating in high-value insurance claim ZIPs where they're systematically underpricing compared to what insurance adjusters consistently approve. Show them the exact approval amounts by carrier so they can price optimally without leaving money on the table.

Why this works

This removes pricing guesswork by showing what insurance companies actually pay in their specific ZIP. The framing is perfect: you're not overcharging customers, you're pricing to what insurance adjusters approve. The carrier breakdown makes this immediately actionable - they can adjust pricing strategy by carrier relationship.

Data Sources
  1. RoofLink Internal Customer Data - aggregated insurance claim approval amounts by ZIP code and carrier across 340+ completed jobs

The message:

Subject: Insurance adjusters approve $11,200 in 75201 We analyzed 340+ insurance claim approvals in Dallas 75201 - adjusters consistently approve $11,200 for standard roof replacements. Your average is $8,400 - you're leaving $2,800 per job on the table that insurance would pay. Want the adjuster approval breakdown by carrier?
DATA REQUIREMENT

This play requires aggregated insurance claim approval data by ZIP code and carrier from your customer base. Must have 340+ completed insurance jobs with final approval amounts, ZIP codes, and carrier information to establish credible benchmarks.

This is proprietary data only you have from servicing roofing contractors - competitors cannot replicate this insight.
PVP Public Data Strong (9.4/10)

Certification Competitive Advantage: Uncertified Permit Analysis

What's the play?

Target IICRC-certified restoration contractors in counties where recent water damage permits were filed by uncertified competitors. Show them the specific jobs where homeowners settled for uncertified work - these are opportunities where their certification could have won the contract.

Why this works

You're showing them 127 specific jobs they could have won using their competitive advantage. The insight cuts deep: they invested in IICRC certification but aren't capitalizing on it while uncertified competitors take their market share. The offer of addresses and filing dates makes this immediately actionable - they can target these same homeowners for future work or referrals.

Data Sources
  1. BuildZoom Building Permit Database - permit_address, permit_type, permit_date, contractor_name, permit_status
  2. IICRC Certified Firms Global Locator - firm_name, location, certifications (WRT/FSRT)

The message:

Subject: 127 water damage permits filed without IICRC certs In the past 30 days, 127 water damage permits were filed in Tarrant County by contractors without IICRC certification. You're certified - these are jobs where homeowners are settling for uncertified work. Want the list of addresses and filing dates?
PVP Internal Data Strong (9.3/10)

Insurance Pricing Benchmarking: ZIP-Level Optimal Rates

What's the play?

Target roofing contractors operating in high-value insurance claim ZIPs where you have substantial pricing data. Lead with the optimal insurance job price backed by 340+ completed jobs, framed around what insurance adjusters approve rather than what competitors charge.

Why this works

The ZIP-specific pricing backed by 340+ jobs removes all pricing guesswork. Framing it around "what insurance adjusters approve" positions this as money they're leaving on the table, not overcharging customers. The low-commitment ask ("want me to show you the breakdown?") makes response easy.

Data Sources
  1. RoofLink Internal Customer Data - aggregated job pricing by ZIP code and job type (insurance claims) across 340+ completed jobs with median and percentile pricing ranges

The message:

Subject: Do you charge $11,200 for insurance jobs in 75201? Our data shows the optimal insurance claim job price in Dallas 75201 is $11,200 based on 340+ completed jobs. At less than $11,200, you're potentially underpricing against what insurance adjusters approve. Want me to show you the ZIP-level pricing breakdown?
DATA REQUIREMENT

This play requires aggregated pricing data from your customer base by ZIP code and job type. Must have 340+ insurance claim jobs with final pricing to establish credible optimal rates by market.

This is proprietary data only you have - competitors cannot replicate this ZIP-specific pricing intelligence.
PVP Public + Internal Strong (9.3/10)

Certification Opportunity Mapping: Active Claims in Service Radius

What's the play?

Target IICRC-certified restoration contractors who filed zero permits despite substantial water damage insurance claims activity in their 15-mile service radius. Deliver the complete claim list with addresses and carrier information so they can immediately pursue these opportunities.

Why this works

You're confronting them with 234 revenue opportunities in their backyard that went to uncertified competitors. Their IICRC certification is wasted if they're not working - this is a painful mirror. The offer of claim addresses and carriers makes this immediately actionable. This is lead generation delivered as sales outreach.

Data Sources
  1. Insurance Claims Database - claim addresses, filing dates, insurance carriers by county and claim type
  2. IICRC Certified Firms Global Locator - firm location, certifications
  3. BuildZoom Permit Database - permit activity by contractor in service radius

The message:

Subject: 234 water damage claims in your 15-mile radius In the past 45 days, 234 water damage insurance claims were filed within 15 miles of your office. You're IICRC-certified but filed zero permits - these jobs went to uncertified contractors. Want the claim addresses and insurance carriers?
DATA REQUIREMENT

This play requires insurance claim filing data with addresses and carrier information, cross-referenced with contractor business location to calculate service radius and permit filing activity.

This synthesis of insurance claims, business location mapping, and permit activity creates proprietary targeting intelligence.
PVP Public + Internal Strong (9.2/10)

Job-Level Pricing Analysis: Margin Leak Diagnosis

What's the play?

Target contractors operating in high-value ZIPs where you can compare their actual completed job pricing against aggregated market rates from your customer base. Diagnose the source of their pricing gap (estimation tools vs adjuster negotiation skills) and offer job-by-job pricing comparison to fix it.

Why this works

You're showing them their exact margin leak ($2,800 per job) and diagnosing the cause. The offer of job-by-job comparison makes this actionable - they can see exactly which jobs they underpriced and why. This is pricing consultation delivered before any sales conversation.

Data Sources
  1. RoofLink Internal Customer Data - individual job pricing by ZIP with aggregated market rate benchmarks
  2. BuildZoom Permit Database - permit_address, permit_cost, contractor_name for the target contractor

The message:

Subject: Your $8,400 average vs market $11,200 in 75201 We mapped your completed jobs in Dallas 75201 - average value $8,400 vs market rate $11,200. That's $2,800 per job you're underpricing, likely due to estimation or adjuster negotiation gaps. Want the job-by-job pricing comparison?
DATA REQUIREMENT

This play requires individual job pricing data from your CRM for existing customers, combined with aggregated market rate data from your broader customer base to establish ZIP-level benchmarks.

This synthesis of individual job records with market benchmarks creates diagnostic pricing intelligence.
PVP Public + Internal Strong (9.1/10)

Storm Response Intelligence: Active Adjuster Contact List

What's the play?

Target roofing contractors in counties where recent hail events triggered immediate insurance adjuster activity. Deliver the complete adjuster contact list with names, employer carriers, and claim volume patterns within 72 hours of the storm event - while the opportunity is still hot.

Why this works

You're handing them a list of 47 active insurance adjusters they can call TODAY to win storm damage jobs. The specificity (April 3rd, Collin County, 47 adjusters, 72 hours) proves this is real-time intelligence, not generic market research. Adjuster contacts are pure gold for insurance-based roofing contractors - this is consultation-level value before any sales conversation.

Data Sources
  1. NOAA Storm Events Database - event_date, county, event_type (hail), property_damage
  2. Insurance Adjuster Activity Database - adjuster names, employer carriers, claim volume patterns by territory

The message:

Subject: 47 insurance adjusters active in Collin County right now NOAA shows hail damage in Collin County on April 3rd - 47 insurance adjusters filed activity reports within 72 hours. I pulled the adjuster names, their employer carriers, and claim volume patterns. Want the adjuster contact list?
DATA REQUIREMENT

This play requires insurance adjuster activity tracking data showing which adjusters are actively working specific storm events, their employer carriers, and historical claim volume patterns by territory.

Combined with NOAA storm tracking, this creates real-time competitive intelligence for storm damage opportunities.
PVP Public + Internal Strong (8.9/10)

Storm Response Acceleration: Predictive Alert System

What's the play?

Target contractors with slow storm response times (7+ days from event to first permit). Offer them real-time NOAA hail alerts for their service area ZIPs, showing them how much faster they could have responded to the last major event with automated tracking.

Why this works

You're quantifying their competitive disadvantage (47 hours lost) and offering the solution. The test offer is low-risk and practical - they can validate the value on the next storm. Storm response speed directly correlates with insurance claim capture rate, so this addresses their highest-value opportunity.

Data Sources
  1. NOAA Storm Events Database - event_date, county, event_type, real-time API access
  2. RoofLink Internal Customer Data - service area ZIP definitions and storm alert preferences
  3. BuildZoom Permit Database - first permit filing timestamp post-storm by contractor

The message:

Subject: Real-time storm alerts for your service area We track NOAA hail reports and send you alerts within 2 hours of damage in your ZIP codes. Last month's March 15 event - you would've known 47 hours before your first permit. Want to test it for the next storm?
DATA REQUIREMENT

This play requires NOAA storm event API integration with automated monitoring of contractor-defined service area ZIPs. Must track permit filing timestamps to calculate response time gaps.

This synthesis of storm tracking with service area mapping and response benchmarking creates proprietary alerting intelligence.
PVP Public Data Strong (8.8/10)

Storm Response Competitive Analysis: Permit Filing Breakdown

What's the play?

Target contractors with documented slow storm response (7+ day delay from event to first permit). Show them exactly how many permits competitors filed before they entered the market, along with competitor names, filing dates, and average job values to illustrate the competitive disadvantage.

Why this works

You're confronting them with 73 specific jobs competitors captured while they were still preparing. The 7-day delay (April 3rd to April 10th) is verifiable and painful. The offer of competitor breakdown helps them understand who's beating them and by how much - this is competitive intelligence they can use to improve strategy.

Data Sources
  1. NOAA Storm Events Database - event_date (April 3rd), county (Collin)
  2. BuildZoom Building Permit Database - permit_date, contractor_name, permit_cost for all storm-related permits post-event

The message:

Subject: Your competitors filed 73 permits before you After the April 3rd hail event in Collin County, 73 permits were filed by competitors before your first permit on April 10th. I pulled the contractor names, filing dates, and average job values for all 73. Want the competitor breakdown?
PVP Public Data Strong (8.7/10)

Cross-State Market Intelligence: Competitor Expansion Patterns

What's the play?

Target Texas contractors with Oklahoma licenses who haven't worked Oklahoma despite major storm opportunities. Show them that 156 Texas competitors are already capturing the Oklahoma tornado market using their Texas infrastructure, and offer the complete permit pattern analysis.

Why this works

You're showing them a $156M market they're licensed to work but ignoring, while competitors are already there. The insight that other Texas contractors are succeeding removes the "is this even feasible?" question. The offer of permit patterns helps them understand how to replicate competitor success.

Data Sources
  1. BuildZoom Building Permit Database - permits filed in Oklahoma by Texas-based contractors, permit patterns by quarter
  2. State Contractor License Data - multi-state license holders (Texas + Oklahoma)
  3. NOAA Storm Events Database - tornado damage estimates by county

The message:

Subject: 156 permits filed in Oklahoma by Texas contractors In Q1, 156 roofing permits were filed in Oklahoma by Texas-based contractors like you. They're capturing the $156M tornado market while holding Texas licenses. Want the list of who's working OK and their permit patterns?
PQS Public + Internal Strong (8.7/10)

ZIP-Level Pricing Underperformers Post-Storm

What's the play?

Target roofing contractors operating in high-value ZIP codes where their completed permit pricing falls significantly below market averages. Use their actual completed permit data from public records to show them the exact per-job margin gap compared to competitors in the same ZIP.

Why this works

You're showing them their exact numbers ($8,400 average) compared to market reality ($11,200). The $2,800 gap is painful and specific. This isn't generic "you could price better" advice - it's data-driven diagnosis of their pricing strategy problem using their actual completed jobs.

Data Sources
  1. BuildZoom Building Permit Database - permit_address, permit_cost, contractor_name for target contractor's completed jobs
  2. RoofLink Internal Customer Data - aggregated permit pricing by ZIP code from customer base to establish market rate

The message:

Subject: Your average job in 75201 is $8,400 Your completed permits in Dallas 75201 averaged $8,400 per job over the past 6 months. Competitors in the same ZIP averaged $11,200 - that's $2,800 per job you're leaving on the table. Who handles your pricing strategy?
DATA REQUIREMENT

This play requires aggregated permit pricing data from your customer base by ZIP code to establish market rate benchmarks, combined with the target contractor's public permit records.

This synthesis of public permit data with proprietary market benchmarks creates pricing diagnostic intelligence.
PQS Public + Internal Strong (8.6/10)

Insurance Claim Pricing Underperformers by ZIP

What's the play?

Target roofing contractors with completed permits in high-value insurance claim ZIPs where their pricing falls below market rates for insurance work. Frame the gap as money insurance adjusters would approve but they're not capturing.

Why this works

You're showing them their exact pricing ($8,400) vs market rate for insurance work ($11,200). Framing it as "market rate for insurance claim jobs" positions this as approved money they're leaving behind, not overcharging customers. The routing question identifies the pricing decision-maker.

Data Sources
  1. BuildZoom Building Permit Database - completed permits by contractor in specific ZIP with permit costs
  2. RoofLink Internal Customer Data - aggregated insurance claim job pricing by ZIP from customer base

The message:

Subject: Your 75201 jobs are $2,800 below market Your completed permits in Dallas 75201 show an average job value of $8,400. The market rate for insurance claim jobs in that ZIP is $11,200 - you're $2,800 under. Who sets your pricing for insurance work?
DATA REQUIREMENT

This play requires aggregated insurance claim pricing data from your customer base by ZIP code to establish market rates, combined with target contractor's public permit records.

This synthesis of public permit data with proprietary insurance pricing benchmarks creates margin optimization intelligence.
PQS Public Data Strong (8.6/10)

Multi-State License Expiration with Storm Opportunity

What's the play?

Target contractors with licenses in multiple states where one license is approaching expiration while that state experienced major storm damage. Show them the specific license number, expiration date, storm opportunity size, and renewal timeline to create urgency.

Why this works

You're combining administrative urgency (expiring license) with revenue opportunity ($87M in claims). The specific license number (LACB-12345) and timeline pressure (45 days to renew) prove you did the research. The routing question identifies who's responsible without being accusatory.

Data Sources
  1. Louisiana CSLB Contractor License Data - license_number, expiration_date, license_status
  2. Insurance Claims Database - aggregated claim volume by metro area and quarter

The message:

Subject: Your Louisiana license expires June 30th You're licensed in Texas and Louisiana, but your LA contractor license (LACB-12345) expires June 30th. The New Orleans metro had $87M in hail claims filed in Q1 - renewal takes 45 days. Is someone handling the Louisiana renewal?
PQS Public Data Strong (8.5/10)

IICRC-Certified Firms with Storm Opportunity Gap

What's the play?

Target IICRC-certified restoration contractors who filed no permits for 60+ days despite holding credentials, while their service area experienced $43M in storm damage claims. Use diagnostic questioning to determine if they're capacity-constrained or missing lead opportunities.

Why this works

You're showing them a painful gap: they invested in certification but filed no permits during a major storm opportunity. The diagnostic question (crew capacity vs lead flow) shows you're trying to help, not judge. This identifies contractors with real operational pain - either they're maxed out and need efficiency, or they're struggling with lead generation.

Data Sources
  1. IICRC Certified Firms Global Locator - firm_name, certifications (WRT/FSRT), location
  2. BuildZoom Building Permit Database - last permit_date by contractor
  3. Insurance Claims Database - storm damage claim volume by county and quarter

The message:

Subject: Your IICRC cert but no permits since February You hold IICRC Water Damage Restoration certification, but your last permit was filed February 12th in Denton County. March and April had $43M in storm damage claims filed across your service area. Is your crew fully booked or are leads the issue?
PQS Public Data Strong (8.4/10)

IICRC-Certified Contractors with Extended Permit Gaps

What's the play?

Target IICRC-certified contractors with 60+ day permit filing gaps while peer contractors in their area maintained consistent permit volume. Use comparative data to show them they're falling behind certified peers, then diagnose if lead generation is the bottleneck.

Why this works

You're showing them a stark gap: 67 days since their last permit while peers averaged 14 permits/month. The IICRC peer comparison is fair and specific - these are similar contractors, not mega-companies they can't relate to. The diagnostic question helps identify if they need lead generation solutions.

Data Sources
  1. BuildZoom Building Permit Database - last permit filing date by contractor, permit frequency
  2. IICRC Certified Firms Global Locator - certifications and service area for peer comparison

The message:

Subject: Your last permit was 67 days ago Your last permit filing was February 12th in Denton County - that's 67 days ago. IICRC-certified contractors in your area averaged 14 permits per month during that same period. Is lead generation the bottleneck?
PQS Public Data Strong (8.4/10)

Storm Response Speed Laggards Post-Hail Events

What's the play?

Target roofing contractors who filed permits 7+ days after major hail events in their service area, comparing their response time to competitor averages. Show them the exact dates and quantified opportunity gap to demonstrate how slow response costs them insurance claim opportunities.

Why this works

You're showing them their exact performance (9 days) vs competitors (3-4 days) with specific dates. The 5-day gap translates directly to lost insurance claim opportunities. The routing question identifies who manages storm response without being accusatory. This mirrors a specific operational gap they likely know exists but haven't quantified.

Data Sources
  1. NOAA Storm Events Database - event_date (March 15), county (Tarrant), event_type (hail)
  2. BuildZoom Building Permit Database - first permit filing date post-storm by contractor

The message:

Subject: Your response time in Tarrant County after March 15 hail You filed your first permit 9 days after the March 15 hail event in Tarrant County. Competitors averaged 3-4 days - that's 5 days of insurance claim opportunities lost. Who manages your storm response workflow?
PQS Public + Internal Strong (8.3/10)

Storm Response Delay with Quantified Job Loss

What's the play?

Target contractors with documented slow storm response (7+ day delay from event to first permit). Quantify exactly how many insurance claims were filed and assigned to adjusters during their delay period, showing them the specific revenue opportunity they missed.

Why this works

You're converting their delay into concrete lost opportunities: 34 specific jobs already assigned to adjusters before they arrived. The dates are verifiable (March 15 to March 24). The accountability question identifies who's responsible for storm monitoring without being confrontational.

Data Sources
  1. NOAA Storm Events Database - event_date (March 15), county (Tarrant)
  2. BuildZoom Building Permit Database - contractor's first permit date (March 24)
  3. Insurance Claims Database - claim filing dates and adjuster assignment timing in service radius

The message:

Subject: 9-day delay cost you 34 potential jobs in March After the March 15 hail event in Tarrant County, you filed your first permit on March 24th. In those 9 days, 34 insurance claims were filed in your service radius - all assigned to adjusters before you arrived. Who's monitoring storm damage alerts?
DATA REQUIREMENT

This play requires insurance claim filing data with timestamps and adjuster assignment dates, cross-referenced with contractor service radius definitions and permit filing activity.

This synthesis of storm events, insurance claim timing, and contractor response patterns creates specific opportunity loss quantification.
PQS Public Data Strong (8.2/10)

Multi-State Licensed with Single-State Activity

What's the play?

Target contractors holding active licenses in multiple states but filing 90%+ of permits in only one state. Show them the massive storm opportunity in their untapped licensed state and ask if geographic expansion is on their strategic radar.

Why this works

You're showing them wasted licensing infrastructure: they paid for multi-state licenses but only work one market. The 94% concentration is stark and verifiable. The $156M Oklahoma opportunity makes this about real revenue, not hypothetical expansion. The open-ended question explores their strategy without being pushy.

Data Sources
  1. State Contractor License Data - active licenses by state (Texas + Oklahoma)
  2. BuildZoom Building Permit Database - permit filing activity by state for target contractor
  3. Insurance Claims Database - storm damage claim volume by state

The message:

Subject: You're licensed in 2 states but only working Texas You hold active contractor licenses in Texas and Oklahoma, but 94% of your permits are filed in Texas. Oklahoma had $156M in tornado damage claims in Q1 - zero permits from you. Is the OK market on your radar?

What Changes

Old way: Spray generic messages at job titles. Hope someone replies.

New way: Use public data to find companies in specific painful situations. Then mirror that situation back to them with evidence.

Why this works: When you lead with "Your last permit was filed February 12th in Denton County - that's 67 days ago. IICRC-certified contractors in your area averaged 14 permits per month" instead of "I see you're growing your business," you're not another sales email. You're the person who did the homework.

The messages above aren't templates. They're examples of what happens when you combine real data sources with specific situations. Your team can replicate this using the data recipes in each play.

Data Sources Reference

Every play traces back to verifiable data. Here are the sources used in this playbook:

Source Key Fields Used For
NOAA Storm Events Database event_date, county, event_type, property_damage, magnitude Storm tracking and hail/tornado event identification for insurance claim opportunities
BuildZoom Building Permit Database permit_address, permit_date, contractor_name, permit_cost, permit_status Contractor permit activity, job volume tracking, pricing data by ZIP
IICRC Certified Firms Global Locator firm_name, location, certifications, certification_type Insurance restoration contractor certification verification
State Contractor License Data (WA/CA/TX/LA/OK) license_number, license_status, county, issue_date, expiration_date Multi-state licensing verification and expiration tracking
Insurance Claims Database claim_filing_date, claim_address, insurance_carrier, claim_type Active insurance claim tracking by county and claim type
Insurance Adjuster Activity Database adjuster_name, employer_carrier, territory, claim_volume Active adjuster contact lists post-storm events
RoofLink Internal Customer Data job_pricing, ZIP_code, job_type, completion_date, service_area_ZIPs Aggregated pricing benchmarks by ZIP and job type, storm alert preferences