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.
Company: Archy
What they do: Archy is an all-in-one cloud-native practice management platform for dental practices. They consolidate 5+ disconnected software systems (scheduling, charting, imaging, billing, communications) into one integrated platform with built-in AI imaging.
Core problem: Dental practices waste 80+ hours monthly managing disconnected legacy systems for scheduling, communications, imaging, and billing. Legacy systems create data silos, increase operational costs (~$8,000/year in subscriptions), and prevent modern cloud-based workflows.
Industries: Dental Healthcare
Company Types: Dental Service Organizations (DSOs), multi-location dental groups (2-10 locations), independent practices converting from legacy systems
Company Size: 5-500 employees, single to multi-location dental practices
Primary Persona: Dental Practice Owner / Office Manager responsible for practice operations, software management, budget, staff coordination, patient scheduling, and insurance billing
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 Archy 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 Texas practices are getting D2740 claims denied at 47% - that's $127K in the last 90 days" (internal data with specific procedure codes and dollar amounts)
PQS (Pain-Qualified Segment): Reflect their exact situation with such specificity they think "how did you know?" Use internal data with procedure codes, location names, and specific dollar amounts.
PVP (Permissionless Value Proposition): Deliver immediate value they can use today - analysis already done, procedure codes already pulled, patterns already identified - whether they buy or not.
These messages demonstrate precise understanding of the prospect's current situation or deliver immediate value. All plays are sorted by quality score (highest first).
Identify DSOs with multiple Texas locations that have crown claims (D2740) sitting in denial/appeal status due to missing the July 2024 Texas Medicaid pre-treatment narrative requirement. Provide the exact template they need to recover the revenue.
$213K is massive and specific to their operation. Calling out the exact regulatory change (July 2024 Texas Medicaid requirement) shows you track compliance shifts they may have missed. Offering the actual template provides immediate actionable value - they can act without a meeting.
This play requires internal claims data ($213K, 11 locations, D2740 procedure code) combined with public knowledge of Texas Medicaid documentation requirements that changed in July 2024.
The combination of internal claims tracking + public regulatory monitoring is what creates defensible insight.Identify specific practice locations within a DSO that have exceptionally high denial rates for resin crown procedures (D2391) in the most recent quarter. Offer procedure-specific and payer-specific breakdown to help them fix the underlying billing workflow issues.
Calling out three specific locations by name proves deep analysis of their practice footprint. 52% denial rate is alarming and actionable. $89K in appeals is money they could collect faster. The procedure code specificity (D2391) shows granular analysis, not generic benchmarks.
This play requires claims data showing denial rates by practice location, procedure code (D2391), and time period (Q4). The $89K figure represents actual claims in appeals status for these three locations.
This is proprietary data only you have - competitors cannot replicate this play.Identify DSOs with Texas practices that have abnormally high crown claim (D2740) denial rates. Show them the dollar impact and contrast with the denial rate achieved by practices using integrated eligibility verification.
47% denial rate is catastrophic and specific to their Texas practices. $127K is real money being lost RIGHT NOW. The 11% comparison (practices using integrated verification) shows there's a concrete, proven solution. The easy yes/no question creates low friction for engagement.
This play assumes Archy has aggregated insurance claim denial data across their customer base, segmented by procedure code (D2740) and state (Texas). The 47% denial rate and $127K figure are specific calculations based on the recipient's practice data vs. benchmark.
Helps the recipient recover lost revenue and serve their patients better by reducing claim denials.Aggregate all claim denial data across a DSO's entire practice portfolio to identify the top 3 procedure codes driving the most revenue loss. Then identify which specific locations lack integrated eligibility verification technology that would catch these denials before the procedure.
$441K aggregated across their entire operation is massive. Identifying the top 3 procedure codes shows data synthesis, not just raw data. Calling out 14 of 18 locations proves you know their exact practice count. The integrated eligibility check is the specific solution, and offering the list of 14 locations helps them prioritize which to fix first.
This play assumes Archy has aggregated claims denial data across all of the recipient's practices (18 total), can identify top denial drivers by procedure code, and knows which 14 locations lack integrated eligibility verification (based on their tech stack).
Helps the recipient prioritize which locations to fix first based on dollar exposure.Identify DSOs with multiple Florida practices that have periodontal scaling (D4341) denial rates significantly above the state average. This pattern suggests documentation or pre-authorization workflow gaps that are costing them revenue.
Specific procedure code (D4341) and state (Florida) shows real research. The 41% vs 19% comparison makes the problem concrete and alarming. Calling out 7 practices shows you know their Florida footprint. The documentation/pre-auth insight is actionable - they can fix this. The routing question is easy to answer.
This play assumes Archy has claims denial data segmented by state (Florida), procedure code (D4341), and can benchmark against state averages. The 7 practices figure comes from knowing the recipient's practice count in Florida.
This is proprietary data only you have - competitors cannot replicate this play.Identify DSOs with California practices where periodontal maintenance (D4910) denial rates have increased significantly from one quarter to the next. This suggests a recent process breakdown in documentation or payer mix changes that needs investigation.
Specific procedure code (D4910) and state (California) again. The 38% vs 22% trend shows deterioration - alarming and urgent. Q3 to Q4 comparison suggests a recent process breakdown they may not have noticed. Calling out 5 practices shows you know their CA footprint. The easy yes/no routing question creates low friction.
This play assumes Archy has time-series claims denial data showing Q3 vs Q4 trends for specific procedure codes (D4910) by state (California) and can identify the 5 California practice locations.
This is proprietary data only you have - competitors cannot replicate this play.Old way: Spray generic messages at job titles. Hope someone replies.
New way: Use internal claims data to find DSOs with specific billing inefficiencies. Then mirror that situation back to them with procedure codes, dollar amounts, and location names.
Why this works: When you lead with "Your Texas practices are getting D2740 claims denied at 47% - that's $127K in 90 days" instead of "I see you're a multi-location practice," you're not another sales email. You're the person who did the analysis they should have done themselves.
The messages above aren't templates. They're examples of what happens when you combine internal claims data with regulatory monitoring. Your team can replicate this by building the data infrastructure described in each play.
Every play traces back to verifiable data. Here are the sources used in this playbook:
| Source | Key Fields | Used For |
|---|---|---|
| Internal Claims Data | procedure_code, denial_rate, state, location, dollar_amount, payer, time_period | All PVP and PQS plays - identifying DSOs with high claim denial rates by procedure type and location |
| Practice Technology Stack Data | integrated_eligibility_verification, practice_location, software_systems_used | Identifying which practices lack integrated eligibility verification technology |
| Texas Medicaid Documentation Requirements | regulation_effective_date, required_documentation_fields, procedure_codes_affected | $213K Texas claims play - regulatory compliance monitoring |
| State Average Denial Rates | state, procedure_code, median_denial_rate | Florida D4341 play - benchmarking against state averages |