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.
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 Scan.com SDR Email:
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.
Blueprint flips the approach. Instead of interrupting prospects with pitches, you deliver insights so valuable they'd pay consulting fees to receive them.
Stop: "I see you're hiring compliance people" (job postings - everyone sees this)
Start: "Your facility at 1234 Industrial Pkwy received EPA violation #2024-XYZ on March 15th" (government database with record number)
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.
These messages demonstrate such precise understanding of the prospect's current situation that they feel genuinely seen. Every claim traces to a specific government database with verifiable record numbers.
NY WCB Assembled Claims data (carrier_type, wcio_part_of_body_description, wcio_nature_of_injury_description, district_name, medical_fee_region, accident_date, current_claim_status) identifies private workers' comp carriers whose lower-back and knee strain/sprain claims in specific WCB districts remain open 40+ days longer than peer carriers in the same district and fee region. The contrast between imaging-gated MSK injuries (strains/sprains) and non-imaging injuries (fractures, lacerations) isolates the diagnostic-scheduling delay as the root cause, not general claim-handling speed. This carrier's own 2023 Hauppauge district cohort shows 41% open at 18 months versus 24% for same-district peers—a measurable, verifiable gap that points directly to slow imaging access.
Claims managers feel accused when delays are framed as operational failure; this message inverts that by using the carrier's own peer comparison to isolate the MRI gate as the culprit. The fracture-vs-strain contrast is a cut the recipient has not run, making it feel like a gift rather than criticism. The yes/no close ('Does that match what your Hauppauge desk is seeing?') is non-threatening and invites collaboration rather than defensiveness.
DOL Form 5500 research file (FUNDING_GEN_ASSET_IND, TYPE_WELFARE_BNFT_CODE, TOT_PARTCP_BOY_CNT, SPONS_DFE_MAIL_US_ZIP, Schedule C PROVIDER_OTHER_NAME) identifies self-funded health plans headquartered in specific metros. Scan.com's proprietary pre-onboarding routing pattern (hospital-vs-freestanding MRI split observed across 50+ employer customers in that metro) and contracted rate spread reveal market-typical behavior ($1,840 at hospital outpatient vs $590 at freestanding in Atlanta) before a plan makes changes. The message prompts the benefits director to ask whether their TPA (Peachtree) reports their own split—a question they may not have thought to ask and a discovery that positions Scan.com as a source of operational intelligence.
The recipient already knows they self-fund; the value is learning that their peers' routing leans 63% toward expensive hospital outpatient before optimization. This context is useful for preparing a conversation with their TPA without requiring a response. The question ('Does Peachtree report your split?') is a yes/no that opens dialogue without selling.
Metro-level contracted MRI rates by center type (10+ centers in Atlanta) and pre-onboarding hospital-vs-freestanding routing share observed across 50+ employer customers.
Scan.com's pre-onboarding routing analytics are proprietary; aggregated across 50+ employer customers per metro (privacy-safe). The 63% hospital-outpatient share and corresponding rate data come from Scan.com's customer onboarding experience in the Atlanta metro and cannot be replicated by competitors, brokers or consultants without equivalent national integration footprint and claim-level visibility.NY WCB Assembled Claims data tracks median days-to-first-hearing and first-hearing-to-section-32 intervals for specific injury types by carrier and district. A private carrier's shoulder and lower-back sprain claims in Buffalo show a year-over-year increase from 131 days (2022) to 174 days (2023)—a 43-day slip in one year—while peer private carriers in Buffalo held steady at 118 days. This drift appears only on MRI-gated injuries; the same carrier's fracture and laceration claims track at district peer median, proving the lag is not systemic to their adjusting philosophy but specific to imaging-dependent claims.
Year-over-year change in a carrier's own numbers is a credible, internal signal that leadership will investigate. The peer comparison is data-driven, not accusatory. Isolating the gap to MRI-gated injuries only redirects blame from the claims team to the scheduling bottleneck, which is where Scan.com can help.
These messages provide actionable intelligence before asking for anything. The prospect can use this value today whether they respond or not.
NY WCB Assembled Claims data (current_claim_status, wcio_part_of_body_description, county_of_injury, assembly_date) surfaces the count of open lower-back, knee and shoulder claims for each carrier by county. Scan.com's proprietary RIS/EMR-integrated freestanding MRI center network (10+ centers per region, live next-available-slot scheduling, 48-hour median report turnaround) maps those open claims to real, actionable next-appointment slots this specific week. The deliverable is county-level capacity (median days-to-MRI), center names with direct phone numbers, and specific dates when slots exist—data no static imaging directory can provide because it requires live scheduling-system integrations.
An adjuster or nurse case manager receives a list of three centers with phone numbers and availability dates before they even reply. This is a gift: it is immediately useful for routing injured workers who are sitting in their book right now, independent of any sale. The implicit message is 'we know your open claims count and we can move your people faster'—a demonstration of capability wrapped in concrete help.
Live next-available-slot timestamps and median days-to-appointment for RIS/EMR-integrated freestanding MRI/CT centers, aggregated by county across 10+ centers; per-center report turnaround tracking (98% within 48 hours).
Scan.com's live two-way RIS/EMR scheduling integrations and report-turnaround tracking are the product's stated differentiators. Sharing aggregated county-level capacity and center lists (10+ centers per region, no customer-specific data) drives referrals to partner centers and is a genuine gift independent of contract. This proprietary data is not available from static imaging networks (One Call, US Imaging Network, Green Imaging, OneImaging) because they lack live scheduling integrations.NY WCB Assembled Claims data (current_claim_status, wcio_part_of_body_description, county_of_injury, assembly_date) identifies open knee and lower-back claims for each carrier by county. For a carrier with 96 open MSK claims in Erie and Monroe counties, Scan.com's proprietary RIS/EMR-integrated freestanding network provides real-time next-available-slot data (2.4 days median this week) and specific dates when appointments exist (e.g., Tuesday Nov 4, Thursday Nov 6) with 48-hour reads. The message provides center names, addresses and phone numbers so case managers can act immediately.
Nurse case managers own the day-to-day work of moving injured workers through imaging. Giving them specific dates and phone numbers they can call before COB removes friction and proves the system works. The 48-hour read turnaround is the KPI they actually track, so citing it demonstrates understanding of their pain.
Live next-available-slot timestamps and median days-to-appointment for RIS/EMR-integrated freestanding MRI/CT centers, aggregated by county across 10+ centers; per-center report turnaround tracking (98% within 48 hours).
Scan.com's live two-way RIS/EMR scheduling integrations provide real-time slot availability and turnaround tracking. Aggregated county-level capacity and center lists (10+ centers per region) are privacy-safe and drive referrals to partner centers. Competitors cannot provide this data because they operate static directories.DOL Form 5500 research file (FUNDING_GEN_ASSET_IND, TYPE_WELFARE_BNFT_CODE, TOT_PARTCP_BOY_CNT, SPONS_DFE_MAIL_US_ZIP, Schedule C PROVIDER_OTHER_NAME) identifies self-funded health plans with 2,000+ participants headquartered in specific metros. Scan.com's proprietary contracted MRI/CT rates by center type in that metro (10+ centers per metro, aggregated across 50+ employer customers) and observed imaging utilization per 1,000 lives reveal a metro-specific price spread and dollar-value model. For Dallas-Fort Worth, freestanding centers charge $640 for lumbar MRI versus $1,980 at hospital outpatient—a $1,340 spread per scan—enabling a benefits director to calculate that a 10-point shift in volume toward freestanding sites yields ~$97,000 annual savings at that plan's size.
A benefits director can take this number straight into their TPA renewal conversation without ever replying. It is independently useful and positions Scan.com as a source of market intelligence, not just a vendor. Metro-specific contracted rates (not generic industry benchmarks) prove insider knowledge and competitive intelligence.
Metro-level contracted MRI/CT rates by center type (10+ centers per metro) and observed MRI utilization per 1,000 lives from 50+ employer customers.
Scan.com's contracted rates and utilization data are proprietary; aggregated across 10+ centers per metro and 50+ employer customers (privacy-safe). No competitor, broker or consultant can produce metro-specific contracted rates for freestanding networks because they lack the national integration footprint and claim-level visibility into utilization patterns.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 Dallas facility has 3 open OSHA violations from March" instead of "I see you're hiring for safety roles," 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.
Every play traces back to verifiable public data. Here are the sources used in this playbook:
| Source | Key Fields | Used For |
|---|---|---|
| NY Workers' Compensation Board Assembled Claims Data | carrier_name, carrier_type, wcio_part_of_body_description, wcio_nature_of_injury_description, wcio_body_system_description, district_name, medical_fee_region, accident_date, current_claim_status, closed_count, first_hearing_date, section_32_date, hearing_count, ime_count, county_of_injury, assembly_date | Identifying private workers' compensation carriers with MRI-gated claim delays in specific WCB districts; calculating open-claim counts by county and carrier; detecting year-over-year duration trends and peer-relative performance gaps. |
| DOL Form 5500 Group Health Plans Research File | FUNDING_GEN_ASSET_IND, FUNDING_TRUST_IND, FUNDING_INSURANCE_IND, TYPE_WELFARE_BNFT_CODE, TOT_PARTCP_BOY_CNT, SPONS_DFE_MAIL_US_ZIP, PROVIDER_OTHER_NAME (Schedule C), SERVICE_CODE | Identifying self-funded health plans with 2,000+ participants; determining funding type (general assets, trust-funded); mapping plan sponsors to metros via ZIP-to-CBSA crosswalk; extracting current TPA/claims administrator name for outreach targeting. |