Healthtech Startup Growth

I've watched 3 "revolutionary" healthcare technologies fail spectacularly. Each time, the technology was perfect. The implementation was disastrous. Google Health (shut down twice). Microsoft HealthVault (lasted 12 years, then folded). IBM Watson for Oncology (massively overpromised). Billions invested. Solid technology. Total failure. Not because the vision was wrong, but because healthcare adoption follows different rules than consumer tech. Here's what I learned building healthcare tech for 15 years: 1/ Healthcare moves at the speed of trust, not innovation ↳ Lives are at stake, so skepticism is protective ↳ Regulatory approval takes years usually for good reason ↳ Doctors need extensive validation before adoption ↳ Patients want proven solutions, not beta testing 2/ Integration trumps innovation every time ↳ The best tool that no one uses is worthless ↳ Workflow integration matters more than features ↳ EMR compatibility determines adoption rates ↳ Training time is always underestimated 3/ The "cool factor" doesn't predict success ↳ Flashy demos rarely translate to daily use ↳ Simple solutions often outperform complex ones ↳ User interface design beats artificial intelligence ↳ Reliability matters more than cutting-edge features 4/ Reimbursement determines everything ↳ No CPT code = no sustainable business model ↳ Insurance coverage drives provider adoption ↳ Value-based care is changing this slowly ↳ Free trials don't create lasting change 5/ Clinical champions make or break technology ↳ One enthusiastic doctor can drive adoption ↳ Early adopters must see immediate benefits ↳ Word-of-mouth beats marketing every time ↳ Resistance from key stakeholders kills innovations The pattern I've seen: companies build technology for the healthcare system they wish existed, not the one that actually exists. They optimize for TechCrunch headlines instead of clinic workflows. They design for Silicon Valley investors instead of 65-year-old physicians. A successful healthcare technology I've implemented? A simple visit summarization app that saved me time and let me focus on the patient. No fancy interface, very lightweight, integrated into my clinical workflow, effortless to use. Just solved an problem that users had. Healthcare doesn't need more revolutionary technology. It needs evolutionary technology that works within existing systems. ⁉️ What's the simplest technology that's made the biggest difference in your healthcare experience? Sometimes basic beats brilliant. ♻️ Repost if you believe implementation beats innovation in healthcare 👉 Follow me (Reza Hosseini Ghomi, MD, MSE) for realistic perspectives on healthcare technology

Every week, I get a 10 new startup pitches that says “We’ll deliver healthcare in 10 minutes.” Quick commerce is now rushing into healthcare. So I thought to do a breakdown on what’s hype and what might actually work in India. What could work? 1)30–60 min medicine delivery can work for chronic refills or acute needs. In metros with dense demand, it's useful. But 10-min isn’t necessary. Even same-day is fine for 90% of use cases. And honestly, your local chemist is already doing that. 2) Rapid diagnostics for home blood collection isn’t about speed but it’s about hygiene and reliability. A 2-hour sample pickup and next-morning results is a solid win. What we need is better logistics and trained phlebotomists, not faster scooters. 3)On-demand nursing or paramedic visits but for use cases like wound care, IV, injections. Could work with proper scheduling. Think “Ola for nurses,” not “Blinkit for bandages.” Needs backend infra for verification, training, EMR integration. What won’t work (At least not now) 1) Ambulance in 10 mins sounds great until you hit Delhi or Bangalore traffic. Speed is useless without triage and location accuracy. What we really need is better coordination between hospitals and ambulance providers, not just faster wheels. 2) On-demand doctors in 10 mins is a bad idea. You don’t need any doctor fast but you need the right one. Discovery & matching are bigger problems than speed. Most video consults struggle with quality, not timing. Clinical care isn’t fast food. Trust takes time. 3) The 10-min everything app for healthcare is lazy ambition dressed up with VC money. Healthcare isn’t a SKU game but it’s complex, regulated, and hard to standardize like groceries. Great for funding buzz, terrible for trust and real outcomes. Few thoughts if you really are passionate to build in healthcare. Trust > velocity. Speed isn’t everything. Infra & people ops > APIs. Reliability > 10-min hacks. Health is longitudinal & not transactional. Good luck if you're building something in Healthcare in India.

I've watched brilliant SaaS founders burn out in HealthTech. Why? Because they never unlearned how different healthcare is. And they thought product-market fit was transferable across industries. It's not. In SaaS, speed wins. In healthcare, speed kills trust. In fintech, users adopt overnight. In healthcare, they ignore you for 18 months-then finally listen if a trusted peer vouches. In AI, "move fast and optimise the model" is a mantra. In healthcare, break one thing and no one trusts you again. Healthcare doesn't care how smart your product is. It cares how safe, proven, and compliant your product is. That's why HealthTech founders must think like operators, not engineers. Your edge is not your codebase. It's your credibility. Your moat isn't your algorithm. It's provider trust. Your traction isn't ARR. It's clinical validation. What's the shift I see in the winners? They stop asking: "How do we scale fast?" They start asking: "How do we earn trust slowly, and never lose it?" They prioritise: Designing around regulation, not fighting it Partnering with clinicians early, not just after launch Building boring, robust systems, not sexy MVPs Measuring real-world impact, not demo delight They build for permanence, not press. If you're in HealthTech and it feels harder than anything you've done before...welcome to the industry. That means you're finally playing the real game. Not tech. Not SaaS. Healthcare.

95% of healthtech startups don’t survive their first real market test. Not because of the product. Not because of funding. But because they misunderstood what the real test even is. Let me explain. Most founders think the test is: Will users try it? Can we grow fast? Does the product work? But in healthtech, the true test is this: Can the market trust you enough to use your product in a clinical workflow, at scale, without hand-holding? That’s where 95% of startups fail. Because healthcare doesn’t reward novelty. It rewards credibility, compatibility, and continuity. Here are 4 brutal truths I’ve learned after 25+ years in this space: 1. Healthcare doesn’t buy tech. It buys trust. Even if your ML model is 95% accurate, it won’t be adopted unless people trust how it works and why it works. If clinicians don’t understand it and decision-makers can’t defend it, they won’t risk patient care or reputations on it. 2. Pilots aren’t validation unless they prove real-world value. A controlled trial is only useful if it demonstrates measurable improvements - like saved clinician time, lower readmission rates, or better outcomes. Without that, it’s just a demo, not validation. 3. Integration beats innovation. If your product forces staff to log into a new system, learn new workflows, or switch between screens - it won’t scale. The best products blend into existing tools and workflows, not break them. 4. Good storytelling doesn’t secure funding. Proof does. You can impress with a flashy deck, but serious investors and clinical buyers want published studies, cost-benefit analyses, and evidence of adoption. Credibility beats charisma - every time. So if your startup fails at the first market test - it probably wasn’t bad tech. It was bad strategy. Too many teams build with optimism instead of realism. If you’re pre-launch or pre-scale, ask yourself: Who exactly will use this every day? Who will approve and pay for it? What will they stop doing once they adopt it? Healthtech isn’t about hacking growth. It’s about building trust - through data, design, and delivery. I’ve seen brilliant teams crash because they built for what should work - Not what actually gets used. You don’t need a better product. You need a better go-to-market reality check. Have you seen healthtech ideas die at the last mile? What caused the failure? #healthtech #founders #startups #innovation

"We tried Cold Email, but didn't see results." Has to be one of the most common challenges I hear. Let me explain. Over the course of 2024, I’ve spoken with many B2B SaaS Founders, Marketing Directors, Sales Directors, and GTM Leaders. They all share one problem in common: They’ve tried Cold Outreach, but they don’t get any results. So naturally, I start asking questions and offer to have a look at what they’re doing. When I review their campaigns, one thing becomes crystal clear: They understand how to build prospect lists, but there's little to no split testing happening. Here’s the reality: If you’re only sending 100-200 emails without testing different angles, you’re gambling on the success of your campaign, and in most cases, that gamble doesn’t pay off. Let’s break this down. There are two types of companies: 1️⃣ The 1% that doesn’t need to split test (they already know their ICP and what works for them). 2️⃣ The 99% that absolutely MUST split test to find what works best. If you’re part of the 99% (and most of us are), here’s how to do it effectively: Step 1: Test Pain Points Start by identifying the key problems your target audience is facing. Let’s say you’re an agency targeting e-commerce brands. You could test angles like: → High customer acquisition costs → Low lifetime value → Low return on ad spend Each email script stays consistent, only the pain point changes. 💡 Example: If you’re targeting a Sales Director, one angle might focus on the challenge of getting unqualified leads filling up their pipeline, while another might highlight how their team spends too much time on lead nurturing rather than closing. Allocate a set number of leads to each angle (e.g., 1,000 leads per angle) and track results. Step 2: Analyze & Scale Winners Once you’ve sent out the emails, review your data. Ask yourself: → Which angle is getting the most positive replies? → Are certain pain points resonating more than others? If one angle shows promise, double down. If another flops, drop it. Step 3: Test Offers After narrowing down the best angles, shift your focus to your offer. Split test variations of your offer to see which drives the most engagement and demo bookings. Forget vanity metrics like open rates (for now). Instead, track the ratio of PRRs. Many B2B companies: ❌ Send a small volume of Cold Emails (100-200) and expect big results. ❌ Focus too much on minor variables like subject lines before testing major factors like pain points or offers. ❌ Don’t analyze campaign performance enough to refine their approach. 💡 Pro tip in the PDF below👇 💬 Drop a comment below, or DM me for a free campaign audit.

Cold outreach can feel like a guessing game, but after sending 1000s of cold emails, I’ve learned 1 thing: Cold email success is in the details. Look at these data↓ - 16.9% of emails never reach the recipient's inbox - Deliverability on Google: 95.54% (57.8% inbox, 37.74% promotions tab) (source: Emailtooltester) Here’s my strategy to improve deliverability and boost replies in 2025: 1. Build a “Spam-Proof” Foundation Your emails are only as good as the infrastructure supporting them. Here’s what works: Authenticate Everything ↳ Use SPF, DKIM, and DMARC to gain inbox trust. Smart Infrastructure ↳ Rely on Smartlead'𝘀 SmartServers for a dedicated setup that avoids shared-IP pitfalls. Start Small, Then Scale ↳ Gradually warm up accounts to 50–100 emails/day. Domain Strategy ↳ Rotate campaigns across multiple domains or subdomains to stay clean. 2. Make Them Want to Open Your Email Subject lines and first impressions matter. Here’s how to make them count: Short Subject Lines ↳ Keep them under 5 words—clear beats clever every time. Personalization ↳ Mention their recent work, role, or company name in the opening line. Text-Only Wins ↳ Fancy designs get flagged; stick to plain-text emails. Curiosity-Driven CTAs ↳ Use phrases like, “Would this solve X for you?” 3. Solve Real Problems, Not Generic Ones Your offer needs to hit home—here’s how to make it stick: - Focus on one pain point that resonates with your audience. - Use data-backed proof: “Cut costs by 20%” or “Save 5 hours weekly.” - Keep your pitch straightforward: No jargon, no fluff. - Add social proof—testimonials and case studies work wonders. 4. Test and Refine Before Sending The best campaigns come from constant iteration. Run Spam Tests ↳ Catch issues before they damage your sender score. Test Placement ↳ Ensure your emails land in the inbox across Gmail, Outlook, and others. Iterate Weekly ↳ A/B test subject lines and CTAs to find what works. A Smarter Way to Scale The formula is simple: Robust setup + Irresistible offers + Strategic scaling = Cold email success. Tools like Smartlead SmartServers handle the technical side, leaving you to focus on what matters: building meaningful connections. What’s been your toughest cold email challenge?

After analyzing $200M+ in sales data across 2,500+ campaigns. I'm sharing my proven framework for scaling outbound success. Current Sales Challenges In 2025: - 79% of sales emails never reach primary inbox - 91% struggle with prospect overload - Only 2% of cold calls result in appointments - Average response rates declining 23% yearly - 51% of quota-hitting reps use social selling My Battle-Tested Scaling Framework: 1. Strategic Targeting - ICP development and refinement - Multi-channel prospect identification - Data-driven lead scoring - Behavioral trigger mapping - Custom audience segmentation 2. Personalization at Scale - AI-powered content generation - Industry-specific messaging - Dynamic template creation - Response pattern analysis - Engagement optimization 3. Multi-Channel Orchestration - Cross-platform integration - Sequential touchpoint mapping - Channel performance tracking - Automated follow-up sequences - Social selling integration My Verified Results Of Q4 2024: - Response rates improved 312% - Sales cycle reduced 47% - Lead quality up 189% - Conversion rates increased 156% - Cost per acquisition down 67% My Enterprise Case Study Of a B2B Tech Company. Before Implementation: - 18 calls per connection - 2.1% response rate - 15 hours weekly on research - $245 cost per qualified lead After Implementation: - 6 calls per connection - 8.9% response rate - 5 hours weekly on research - $76 cost per qualified lead Success isn't about more outreach - it's about smarter, data-driven engagement that resonates with your prospects. Start with personalization and a multi-channel approach. This combination alone improved our clients' response rates by 40%. What's your biggest challenge in scaling outbound sales? #SalesStrategy #OutboundSales #B2BSales #SalesOptimization

Every year at MDisrupt I meet with around 400 health tech companies. Over time, you start to see a clear phenotype of the ones that scale and the ones that fail. The companies that scale: 𝗕𝗿𝗶𝗻𝗴 𝗶𝗻 𝗵𝗲𝗮𝗹𝘁𝗵 𝗲𝘅𝗽𝗲𝗿𝘁𝘀 𝗲𝗮𝗿𝗹𝘆. They don’t wait until launch to talk to clinicians. They understand workflows and pain points from the start and they hire regulatory, product, and commercialization experts who know how to navigate the complexity of healthcare. 𝗧𝗿𝗲𝗮𝘁 𝗲𝘃𝗶𝗱𝗲𝗻𝗰𝗲 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 𝗮𝘀 𝗮 𝗴𝗿𝗼𝘄𝘁𝗵 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆. It’s not a checkbox. It is the foundation for building trust with regulators, clinicians, and payers who need to see ROI before they reimburse. 𝗧𝗵𝗲𝘆 𝗳𝗼𝗹𝗹𝗼𝘄 𝘁𝗵𝗲 𝗺𝗼𝗻𝗲𝘆. They validate that they are solving a real clinical problem and they quantify the ROI, whether that is cost savings or revenue compared to the current standard of care. 𝗧𝗵𝗲𝘆 𝗴𝗼 𝘀𝗹𝗼𝘄 𝘁𝗼 𝗴𝗼 𝗳𝗮𝘀𝘁. Instead of pouring early money into flashy marketing, PR or large sales teams, they focus on regulatory, evidence, and engaging clinical opinion leaders. When the foundation is strong, commercialization scales quickly later. We all know that healthcare moves at the speed of trust. And in this industry, trust cannot be rushed. It has to be built, step by step, with evidence and expertise.

I fired a 6-figure client earlier this year. Here's why..... Healthcare growth doesn't come from speed—it comes from trust compounded over time. This founder was burning $1M/month (family money) trying to sprint through 18-month sales cycles. More SDRs, more tech stacks, more campaigns. I've seen this movie before. But then he shared his vision: "We plan to connect patients with our AI enabled platform, removing the clinician from the visit altogether. They can just review the note after and sign off on medication. Physicians are happier and the patients get what they want without having to deal with a painful in office visit" It was a full stop, contract termination without question at that point. Not only did he expose his arrogance but also ignorance of the healthcare market and the amazing people that are providing care to patients every single day. But he was only focused on profit and cutting out there very people that are the backbone of this industry. Every startup wants to "move fast and break things." But in healthcare, broken things kill people. And I won't be anywhere near a business model that prioritizes speed over patient safety. My stance on AI in healthcare is clear: it should augment workflows, not replace human judgment. Keep humans in the loop. Create MORE patient-facing opportunities, not fewer. The goal? Less paperwork, higher quality, better outcomes, less burnout. Not shortcuts that put patients at risk. The founders I choose to work with build trust systematically: → Clinical evidence before marketing claims → Pilot programs before platform rollouts → Beta clients before mass outreach → Human oversight in every AI decision Trust is the only currency that scales in this market. You can't hack it, you can't automate it, and you definitely can't rush it. Sometimes the most important business decision is knowing when to say no. Speed kills deals. Trust closes them.

Many people reached out to me after I shared how we helped a company send 8M cold emails in 1 month. They’re asking, “Can I scale like that?” My answer is yes, but there are high risks. You need to pay close attention to: Precision ↳ Segmentation and Personalization Deliverability ↳ Infrastructure Efficiency ↳ Costs Here’s how you should do it: 1️⃣ Optimize for cost efficiency early Map out your cost-per-email and ROI targets before scaling. If your margins don’t hold up when you increase volume, you’ll burn through your budget fast. Scaling high-volume cold email means controlling costs without compromising quality. Before even thinking about millions, you need to establish a cost model that works for your business. 2️⃣ Personalization and quality come first Yes, we sent 8 million emails, but volume without personalization is useless. High-quality, personalized emails will always generate better results. That’s why investing in Clay is better than investing in more domains. If you get 1 positive reply for every 100 cold emails sent, you have a strong campaign in your hands. 3️⃣ Scale with a strategic infrastructure When scaling to millions, your infrastructure is everything. Diversify your sending—you don’t stand a chance relying on just one provider. We distributed the sending like this: 50% Google 30% SMTP w/dedicated IP (i.e., Mission Inbox - Email Deliverability Management Hub) 20% Outlook This spread minimized risk and ensured deliverability across platforms. 4️⃣ Continuous monitoring We constantly monitored IP health, reply rates, and complaints. High-volume sending can lead to deliverability drops if not managed properly. You want to avoid getting blacklisted and damaging your reputation at all costs. We rotated domains regularly to prevent any single domain from being overused or blacklisted. But, when sending this much volume, domains will get burned—that’s non-negotiable. We had a backup of domains, already warmed up, to replace the burned ones quickly and keep the campaign running without interruption. Scaling to 8M emails a month without crushing your reputation is possible—but it requires personalization, efficiency, and a strong infrastructure. Want to scale responsibly? Let’s talk. 🔗 DM me “SCALE” and I’ll show you how it’s done.