Getting Healthcare Professionals to Respond

This is Part 1 of a 4-part series on what I learned from surveying 777 dental practices while building CLIN. Part 2 covers the actual data. Part 3 analyzes the patterns. Part 4 shows how these insights led us to pivot to Dentplicity.

My first batch of outreach emails got a 0.3% response rate. Three people out of a thousand. The subject line was "Quick Survey About Your Practice" and it deserved to die in every inbox it landed in.

Healthcare professionals are overwhelmed, protective of their time, and skeptical of yet another software company asking for "five minutes." After ten months building CLIN in stealth, I needed to understand dental practice financial challenges before finalizing our neobank architecture. I could not build sophisticated banking infrastructure, from RTP settlement files to Durbin-exempt partnership structures, without understanding exactly how practices manage money, when they need credit, and what breaks in their current workflows.

Traditional market research felt hollow. I needed real conversations with real practice owners about cash flow timing, check clearing delays, and payment processing costs. The granular financial details that determine whether to build on FedNow rails or stick with ACH settlement timing.

The result: 777 verified responses from dental practices across the U.S. and Canada, with 100+ extended interviews. Here is exactly how I made it work.

My first attempts were disasters. Generic subject lines disappeared into the noise. I needed to scale legitimate outreach, which meant learning entirely new skills.

The tech stack that worked: Instantly.ai for campaign management became my command center. Their YouTube channel is a goldmine for anyone learning cold email. I watched 30+ hours of their content. Most importantly, I learned about domain warming, which was critical. You cannot spin up a new domain and blast emails. You need gradual warm-up sequences to build sender reputation. Python scrapers handled lead generation, pulling publicly available information from Google Maps and practice websites. Did we violate some terms of service? Probably. But we were collecting public information, enriching it, and making it valuable for genuine outreach. LinkedIn Sales Navigator was essential for finding decision-makers and understanding practice structures before reaching out.

Beyond cold email, we tapped into the dental community infrastructure. We reached out to organizations like Glidewell Clinical Education Center in Irvine, a state-of-the-art facility with a 40-seat auditorium that had hosted over 100,000 attendees in their online study club alone. These were not educational programs. They were community hubs where practice owners connected. When you come from a place of wanting to educate rather than sell, and genuinely want to understand the space, people are willing to help. Glidewell's success proved this. They built trust through education first, sales second. We introduced ourselves to the ecosystem first, then asked for insights.

I ran what I called "ABCDEFG campaigns" on Instantly.ai, testing everything from subject lines to calls-to-action. The 5-second rule became crucial: you need to get your message across via subject line, preview text, and first body paragraph within 5 seconds.

The email structure that converted: Line 1, "Hey, I'm building something..." Line 2, "Here's what I'm noticing people doing..." Line 3, "I'd love your thoughts, absolutely not trying to sell you." Personal email signature, not company domain. The more personal and shorter the email, the less explaining I had to do about the product. Making people know this was a real message from a real person got replies and high open rates. List validation was crucial. Clean, segmented lists by specialty and geography. How quickly we replied mattered enormously. We focused on scheduling actual conversations, not collecting survey responses.

I A/B tested 47 different subject lines across 5,000+ emails.

The winners:

"Building for my mom's dental practice - quick question" (8.4% open rate) "Independent practice financial challenges (2-minute survey)" (7.9% open rate) "Helping small practices like yours - quick input needed" (7.1% open rate)

The losers were predictably corporate: "Healthcare Fintech Market Research" (1.2%), "Survey: Practice Management Solutions" (0.8%), "Quick Survey About Your Business" (0.6%).

Personal connection beats professional polish. Healthcare professionals respond to authenticity.

Healthcare schedules create predictable availability windows. After tracking response patterns for two months, the best response times were Tuesday through Thursday, 11 AM to 2 PM EST, with 73% higher response rates. Mondays were administrative catch-up day. Fridays meant early closures and weekend prep. Evenings and weekends were off limits. Regional variations mattered: West Coast practices responded better to 10 AM PST emails (1 PM EST) and East Coast practices preferred 11 AM EST timing.

I used TypeForm with conditional logic, drawing on my urban planning background from the Minnesota Irvine urban planning survey to avoid leading questions. The goal was to let providers talk and listen.

Five minutes maximum. Seven questions total. Every question had to deliver specific, actionable insights.

Question 1, practice basics: "How many dentists work in your practice?" (Solo, 2-3, 4-5, 6+). Question 2, financial pain identification: "What's your biggest monthly operational challenge?" (Multiple choice with write-in option). Question 3, pain quantification: "What percentage of your time do financial management tasks consume?" (Less than 10%, 10-25%, 25-50%, 50%+). Question 4, current tools: "What software do you use for financial management?" (Open text). Question 5, solution interest: "If someone built financial tools specifically for dental practices, what would matter most?" (Ranked priorities). Question 6, willingness to pay: "What do you currently spend monthly on financial/administrative tools?" (Ranges: Under $500, $500-1K, $1K-2.5K, $2.5K-5K, $5K+). Question 7, follow-up permission: "Would you be open to a 15-minute call to discuss these challenges in more detail?"

TypeForm's conditional logic was crucial. Respondents never had to skip irrelevant questions because with Logic they never saw them. This created higher completion rates through a more personal, human experience. For dental practices specifically, I could customize follow-up questions based on practice size, patient type, or satisfaction ratings.

Asking for specific percentages and dollar amounts generated quantifiable data I could compare across practices. Vague questions like "Do you have cash flow challenges?" produced useless yes/no answers. As Rob Fitzpatrick outlines in The Mom Test, the key to customer discovery is asking about specific past behaviors rather than hypothetical future intentions. Asking for current spending amounts worked better than asking if they would pay for new features.

I was building toward specific technical decisions. Should I integrate with RTP for instant settlement? How much would practices pay for same-day clearing? Did their cash flow patterns justify the engineering complexity of FedNow implementation versus traditional ACH timing? These were infrastructure architecture decisions that would determine our entire technical stack.

The follow-up that mattered most: transcript analysis with Google Notebook LM. Out of 777 responses, 108 were interested in Zoom calls, and most of those happened. I took those transcripts and fed them into Google Notebook LM and Google Gemini, creating what became a living body of knowledge on the pains and trials of dental practice owners.

Instead of manually coding hundreds of interview transcripts like traditional qualitative analysis, Notebook LM's AI identified semantic patterns automatically. I could ask "identify all passages discussing cash flow timing" and get relevant excerpts across all interviews in minutes instead of hours. This became my secret weapon. I would listen to these insights podcasts while walking my dog, constantly learning from the actual voice of dental practice owners.

Every completed survey received a personalized thank-you within 24 hours. I provided immediate value back. Respondents received a one-page benchmark report comparing their challenges to similar practices in their region. "Based on 47 practices your size in California, 34% cite cash flow timing as their top challenge vs. 67% citing staff costs..."

This accomplished three things. Immediate value: practices got useful benchmarking data. Credibility building: showed I was analyzing data seriously. Interview conversion: 31% of survey respondents agreed to extended interviews.

The benchmark data revealed specific patterns that informed our technical architecture. Practices with >$50K monthly card volume consistently mentioned 2-3 day settlement delays as cash flow bottlenecks. This validated the business case for RTP integration. Not for all customers, but for high-volume practices where instant settlement would justify the per-transaction cost premium. Small practices cared more about predictable timing than speed. Large practices needed both. This segmentation became foundational to our tiered banking service architecture.

I wanted geographic diversity but concentrated outreach where it would matter most for product development. Target distribution: 30% California (largest dental market, regulatory complexity), 15% Texas (independent practice concentration), 10% Florida (retiree population, unique payment patterns), 8% New York (high operational costs, tech adoption), and 37% other states for national representation. Outreach sources included state dental board public directories, practice websites with contact forms, LinkedIn practice administrator networks, and industry conference attendee lists. Every response required practice verification: website match, phone number confirmation, or LinkedIn profile validation. This eliminated 23% of initial responses as spam or incomplete.

What did not work: Industry partnerships fell through. Three dental industry publications wanted payment or reciprocal marketing arrangements. Bootstrap constraints made this impossible, but direct outreach proved more authentic anyway. Social media promotion generated high response volume but low quality, mostly vendors and students. Referral incentives ($25 Amazon gift cards) attracted participants motivated by rewards rather than genuine interest, and quality dropped significantly. Cold calling failed because receptionists blocked access and interrupting patient care felt disrespectful.

The most valuable responses came from practices willing to share specific challenges. A dentist in Portland wrote three paragraphs about insurance claim delays affecting cash flow. A practice administrator in Nashville detailed exact software integration failures. These detailed responses became product features. When multiple practices mentioned similar pain points, those moved to the top of our development priority list.

The Portland dentist's insurance delay story led directly to our credit facility design. If insurance payments took 45-90 days but practices needed cash flow predictability, we could advance against verified claims, but only with real-time risk monitoring and automated underwriting based on deposit data patterns. The Nashville integration failures informed our API-first architecture. Practices wanted their existing practice management software to work with banking. No separate logins, no manual reconciliation. This meant building robust webhooks, standardized data formats, and fallback systems for when integrations failed.

Survey quantity matters, but survey quality determines product success. One detailed response from a frustrated practice owner teaches more than ten quick checkbox surveys. Each detailed response informed specific technical architecture decisions that would cost hundreds of thousands to implement incorrectly.

After proving the approach worked, I systematized outreach. Weekly targets: 250 new emails, 50 follow-ups, 10 benchmark reports. Five different template variations to avoid spam filters. Detailed spreadsheet tracking open rates, response rates, and geographic distribution. Phone verification for every response claiming $25K+ monthly spend.

777 verified responses over ten months. 15.5% overall response rate after methodology optimization. 100+ extended interviews with practice owners genuinely interested in solutions. Every feature we built had specific customer validation behind it.

These surveys did not inform product features alone. They determined our entire banking architecture. Cash flow timing insights led us to Durbin-exempt bank partnerships for 10x higher interchange rates. Integration pain points drove our API-first, webhook-heavy architecture. Credit needs shaped our real-time underwriting models based on deposit data patterns. When VCs ask about product-market fit, I can point to specific survey responses that justify every major technical decision from FBO account structures to ML fraud detection algorithms.

This methodology transfers beyond dentistry. Healthcare professionals respond to authenticity, respect for their time, and immediate value exchange. Lead with personal connection, not business pitch. Ask specific questions that generate actionable data. Provide value back to respondents. And if you are building in healthcare fintech, these conversations are about technical architecture validation. Understanding whether your customers need same-day settlement, real-time payments, or traditional ACH timing determines your entire infrastructure stack. Getting this wrong costs millions in retrofitting.

The 777 survey responses became our foundation for product development, pricing strategy, go-to-market approach, and most critically, our technical banking architecture.

Data sources: CLIN Customer Discovery Whitepaper (777 verified survey responses, completed March 2025), personal outreach methodology documentation