• The mechanics behind 10x growth after 1st year of public launch

• The Vertical Trap - when niche traction masks a market ceiling

• PLG & Product-led sales strategies in action

• Company culture behind a product people love

• How hard things become a Deferred Lever

Strategic Summary: Attio is the fastest-growing CRM in 2026. The company started as Fundstack, a vertical CRM for venture capital firms, before pivoting in 2019 to attack the $63B CRM market dominated by Salesforce and HubSpot. The defining decision was spending 3+ years building a new data architecture from scratch before going public. This architectural advantage translates directly into distribution: templates install in 30 seconds, onboarding delivers value in under 3 minutes, and migration from competitors takes hours instead of months. Attio reached $1M ARR before public launch, grew from ~100 to 1,000 paying customers in the first year, and scaled to 5,000 paying customers within 2 years by Series B ($116M raised total, led by GV). The go-to-market engine combines product-led growth (75% organic signups) with Product-Led Sales - the product enters bottom-up through builders and operators, then sales converts scattered adoption into company-wide contracts.

The beginning

Within two years of public launch, Attio captured ~4% adoption among CRM users and reached #5 in the category - behind Salesforce, HubSpot, Pipedrive, and Zoho. Confirmed by Ramp’s January 2026 vendor analysis across 3 million data points. Strongest traction is in micro-SMB (6% adoption), tapering to ~1% in mid-market and enterprise. The trajectory - from zero market presence to top five in 24 months - is the result of great software and years of building credibility before going public.

The Vertical Trap

The story starts in 2017 with a company called Fundstack.

Nicolas Sharp and Alexander Christie were building inside the venture capital world when they spotted a fundamental problem. VCs received hundreds of emails, calendar invites, and meeting requests daily. Relationships were getting lost in the noise.

Fundstack solved this by automatically building a user’s network from their email data. Connect your inbox, and the system aggregated, enriched, and organized every contact you’d ever interacted with. For the VC community, it worked. The product generated revenue. It had real traction.

But two years in, the founders hit a ceiling they couldn’t engineer around. The VC and private equity market was too small to sustain what they actually wanted to build.

The Vertical Trap. It says start with a niche and it’s correct. A sharp problem, a clear audience, a defined ICP. But the niche must have room to expand. If the market ceiling is too low, traction becomes a trap: the product works, but the business can’t scale. This is why sizing the total addressable market matters before committing.

Attio’s case mirrors Sword Health. Sword started with limb paralysis patients - a real but extremely narrow group - then expanded to the broader MSK physiotherapy market. Both pivots took roughly two years of building before the founders recognized the ceiling. Both required starting nearly from scratch. The pattern: the original problem was valid, but the original market was a cage.

The Larva Phase

After the pivot, Attio entered the larva phase - direction found, but the company still had a long way to scale. From 2019 to late 2022, full focus on the project for three years in the dark.

They entered the $63B market owned by Salesforce and HubSpot for over 15 years. It was mature, crowded and seemingly settled. But the founders saw what incumbents couldn’t admit - their infrastructure was aging, and no amount of feature layering could fix a rigid foundation. The gap was wide enough for the ‘10x better’ rule to apply.

The bet followed a counterintuitive principle: hard things make everything else easier - this is a deferred lever. It doesn’t activate on day one. Hard projects are a nightmare before they’re a magnet - the shift happens when results start proving the vision. Sword Health, Figma, Gmail followed the same arc. Then difficulty itself becomes the attractor for talent, capital, and customers.

The dark period hit hard. Sharp described it openly: “There were so many times we wanted to give up. Day after day the feeling was, ‘This is a disaster.’ We’ve interviewed 400 engineers and no one wants to work with us.” His survival framework was one question: “If you were to start again, is this a company you would start again?” The answer was always yes. So they kept building - from scratch, for over three years. Similar to how Google spent 4 years developing Gmail before launch, Attio chose to rebuild the foundation on new technology.

4 pillars of great product

The product rested on four pillars:

Flexible Data Model. Traditional CRMs force users into rigid pipelines - fixed fields, fixed stages, fixed logic. Attio lets teams define custom objects that mirror how their business actually works as a basic feature. Sales pipelines, renewal tracking, churn monitoring, revenue expansion - all configurable without developers or consultants. The system adapts to the company, not the other way around.

Automatic Data Enrichment - inherited from Fundstack’s DNA. Attio instantly builds a populated CRM with every person and company you’ve ever interacted with through Gmail and calendar integration. CTO Christie set the onboarding target: time-to-value under 3 minutes.

AI-Native Architecture. They built for AI from the ground up - a three-layer structure: a system of record (custom objects at sub-50ms latency), a system of context (automatic ingestion of emails, calls, documents), and a system of action (AI agents executing GTM tasks that previously required human judgment).

Modern UX. Consistently described as “the first CRM that feels truly modern.” Real-time multiplayer collaboration, command-K launcher, near-zero-latency search - conventions borrowed from Notion and Google Sheets. If you’re comfortable in those tools, Attio feels native.

Product development

Attio built the product the way lean startups are supposed to - but rarely do. The process followed a clear sequence: do it manually, find the pattern, then encode it into software.

In the earliest phase, Sharp and the team onboarded every customer by hand. Manual data migration, custom workspace setups, hours spent watching users click through the product. The goal was pattern recognition. Which steps led to the “aha” moment? Where did users get stuck? What made them invite teammates? What made them leave?

Once the pattern repeated, they coded it. Guided workspace setup, opinionated templates, prompts to connect email and calendar early. The manual playbook became the product. Classic lean startup logic - but applied to the onboarding experience itself, not just the feature set.

The product loop they discovered was simple:

Every element of the onboarding was tuned to push users through this sequence as fast as possible. One critical insight shaped the design: Attio only sticks as a multiplayer tool. A single user gets value. A team gets locked in.

They also use Attio to track their own customers through the adoption journey. Trial expiries, seat spikes, downgrades - all routed through their own CRM to trigger sales or CS interventions. The product was simultaneously the thing they sold and the tool they used to sell it.

Monetization followed the same bottom-up logic. Attio iterated toward a reverse-trial model: new users start with full features, then choose to pay or fall back to free. Individual users enter at zero cost. Teams experience the full power together. Accounts expand naturally as seat count grows - no top-down negotiation required - at least not yet.

Do things that don’t scale - then scale the things that worked. Attio’s PLG engine wasn’t designed in a boardroom. It was discovered through hundreds of manual onboarding sessions where founders did the work themselves. The playbook came from observation, not theory. Once the pattern was clear - which actions led to activation, which led to expansion, which led to churn - they encoded it into software and removed themselves from the loop.

Product as Distribution

In a traditional CRM, the path to revenue looks like this:

HubSpot and Salesforce need entire partner ecosystems just to get customers operational. The product doesn’t sell itself - an army of intermediaries sells it.

Attio’s architecture inverted this. Three mechanics turned the product into its own distribution channel:

Templates as entry points. Attio offers a library of pre-built workflows - fundraising pipelines, sales tracking, talent acquisition. A user installs a complete workflow in 30 seconds. For teams migrating from legacy CRMs, the same flexibility compresses a 3-month implementation into hours.

Land where legacy fails. Most companies use Salesforce for core sales - but processes like partnerships, investments, or customer success end up in Notion or Airtable because Salesforce is too rigid. Attio enters through these gaps. One team builds a workflow for one process, proves the value, then spreads across the organization.

API-first as developer advocacy. For most CRMs, the API is an afterthought. For Attio, it’s a primary distribution channel. Real-time data sync, clean documentation, modern architecture. When a developer needs to connect a CRM to their product’s data, Attio wins by default - it works like modern software. Developers become internal ambassadors who sell Attio to the rest of the company.

Infrastructure is distribution. Legacy CRMs are pre-assembled furniture - you get what’s in the box. Attio is Lego. Same bricks, infinite configurations. Every architectural decision - flexible data model, auto-enrichment, modern UX - compresses the distance between “signup” and “paying customer”.

Early-stage marketing

In their first years, go-to-market and product development were the same thing. By December 2022 - before any public launch Attio had crossed $1M ARR.

Three moves, executed during the larva phase:

Building in public. The founders shared code snippets, design decisions, and product thinking on X.com (Twitter) throughout the build period. This attracted a specific audience: builders and operators who tolerated an MVP-level product in exchange for shaping what it became. Sharp described the target: people who would “be a patient and forgiving tester for you.”

Founder-led sales. Sharp personally prospected on Reddit, X, and startup communities, then onboarded each customer by hand. Some setups took days - manual data migration, custom configurations, bespoke workarounds. Painful and unscalable. But every session was a discovery loop: mapping which steps led to the “aha” moment and what a modern CRM actually needed to do day-to-day.

Velvet rope strategy. Pre-2023, Attio ran a private beta with a waitlist of several thousand teams, onboarding selectively. Growth came from inbound interest, word-of-mouth, and VC connections - not outbound.

VC referral loop. Fundstack’s original customer base - venture capitalists - became Attio’s first organic distribution channel. VCs who used the tool recommended it to portfolio companies, creating one of the earliest sources of paying customers.

The founders invested in their own PR and proof-building from the start, treating public credibility as a compounding asset, not a launch-day tactic. By autumn 2020, they started collecting positive mentions appearing on X - including from TechCrunch.

The Velvet Rope. Most startups rush to open the gates. Attio did the opposite - they controlled access, charged premium prices, and used every customer as a research subject. The waitlist wasn’t a growth hack. It was a filter. Only users who matched the builder persona got in, which meant every feedback loop improved the product for the exact ICP they planned to scale with.

The Butterfly Phase

After three years in the dark, Attio launched publicly in March 2023. The decision was triggered by the convergence of signals that told the founders the product was ready.

The launch conditions:

Technical readiness. In the earliest beta, email sync took 3.5 days to complete, by launch, it happened in seconds. CTO Christie treated data freshness as the killer feature: the moment someone connects their email, insights must surface immediately. The infrastructure had to be invisible. If users noticed the technology, the technology wasn’t ready.

Retention signal. The DAU/MAU ratio reached a level the founders considered sufficient for a daily-use product.

Willingness to pay. Attio tested pricing early at a relatively high price point, and people paid. When they cut the price in half - close rates jumped. By the seed round (November 2021), they had 120 paying customers, $1M+ ARR.

Competitive pressure. New CRM competitors were appearing. Real-time data, flexible objects, modern UX - features Attio’s beta users validated daily - were becoming common. The window to establish category leadership was narrowing. Sharp recognized: “You can’t just build the best product, you also need to win the market”.

A hard deadline. The team set a company-wide launch date and committed to it collectively. It helped them avoid improving the tool endlessly.

Most startups launch too early - trying to scale before retention holds - or too late, after the window closes and unique advantages become table stakes. Attio timed it by stacking signals: retention held, users paid, the market was moving. The final accelerator was a hard deadline that aligned the entire company on a single date. Sharp now treats deadlines as a core operating tool: “Deadlines set the tempo and get people energized.”

Marketing tactics

The public launch in March 2023 was paired with a PR wave, a $23.5M Series A announcement covered by TechCrunch, and a #1 Product Hunt campaign - all timed to hit simultaneously, creating immediate momentum. The message was clear: Attio is no longer a private beta. It’s open, funded, and ready to compete.

As a result, 75% of signups came through organic channels. But the foundation of marketing was the product itself - the <3-minute onboarding that auto-syncs email and calendar data, instantly populating a CRM with enriched contacts. VP of Marketing Alex Vale called it the “magic moment.” Everything else was built to drive users toward that first experience.

They scaled marketing in layers - though some started years before launch. Vale described the full sequence: “Word of mouth from VCs, spreading to startups, building in public on social media, paid search, and eventually, organic social and broader word-of-mouth growth.”

Owned audience. Throughout the pre-launch build period, Attio invested in social presence, podcasts, and newsletters - building an audience before having a product to sell. By launch day, this wasn’t a cold start. Thousands of people already followed the journey and waited for access. This compounding exposure was likely one of the key factors behind Attio’s growth from ~100 paying customers at launch to over 1,000 within the first year.

Product Hunt as launchpad. Attio hit #1 on launch day. For a tool targeting builders and operators, Product Hunt delivered the right audience at the right moment - early adopters tracking innovation, ready to try a new CRM on the spot.

Paid channel. CRM is a high-intent category. People searching “CRM for startups” or “Salesforce alternative” are actively buying. Vale confirmed paid search was one of the earliest successful paid channels: “Paid search worked well in the early stages, helping build a pipeline of high-intent, qualified leads.”

Creator partnerships. In February 2025, Attio formally launched a selective Creator Partner Program targeting GTM leaders and B2B content creators - after running it informally with a few creators earlier. Benefits include free Pro workspace, early feature access, ad spend support, and direct access to the product team. The program is invite-only. Attio recently hired a dedicated Creator Partnerships Lead, signaling this is a strategic channel for 2025-2026, not an experiment.

Sales strategy

Attio’s ICP isn’t the VP of Sales. It’s the builder - the operator, the RevOps lead, the technical founder who configures tools themselves and shows the team. This is bottom-up distribution - one person adopts, the team follows.

The product sells first. Free plan, 14-day trial, self-serve signup - small teams adopt Attio without ever talking to sales. The product handles acquisition. This shifted the sales team’s center of gravity: instead of cold outreach, they focus on helping new users design their workspace, configure workflows, and expand usage. The sales team doesn’t generate demand. It converts demand that the product and marketing already created.

To scale this further, they run Product-Led Sales. When someone creates a workspace, connects their API, and invites colleagues - the sales team receives a signal to reach out to the decision makers. They have context to say: “Hey, your ops team is already building on Attio. Let’s help you roll this out globally.”

The product opens the door. Sales walks through it. But this matters most at scale. Attio’s bottom-up approach works - until the CFO asks why five teams pay separately for tools that do the same thing. The sales team needs to convert scattered adoption into one company-wide contract before that question triggers top-down consolidation.

The Trojan Horse. Legacy CRM sales start at the front gate - pitch the CEO, negotiate the contract, deploy consultants. Attio enters through the side door as “a small tool for the RevOps team.” By the time the license renewal comes around, critical workflows, customer data, and institutional knowledge already live inside Attio. The switching cost is no longer price - it’s operational disruption. Salesforce wins deals top-down. Attio wins bottom-up with sales support.

Growth Milestones

Attio crossed $1M ARR in December 2022 with ~100 paying companies - still in private beta. Three months later, the public launch paired with a Series A announcement revealed the full scale: 2,000+ customers across 100+ countries, most on free or trial tiers.

Product Culture & Organizational DNA

Product and marketing matter - but so does the company mindset that turns vision into a working product the market actually needs. Attio’s founders built their organization around a few principles they publicly credit for the product’s shape and success:

Product engineers, not software engineers. Attio doesn’t hire coders who wait for specs. Every engineer is a product engineer - they design, build, test, and validate features end-to-end. This model allowed Attio to operate without a single product manager for nearly 7 years. The first PM was hired around 2024. Sharp and Christie modeled the approach after early GitHub and Stripe. The result: fewer people, faster decisions, and a product built by people who understand both the code and the customer.

Context over control. Founders handle the 50% that shapes direction - data architecture, platform strategy, AI vision. The other 50% - features driven by customer feedback, UX improvements, workflow fixes - is executed autonomously by the team without heavy top-down approval. If a customer reports friction, the engineer closest to the problem fixes it, tests it, and ships it. This split keeps the product both ambitious and responsive. The 50/50 split isn’t a documented KPI - it’s how they describe their prioritization philosophy.

Company-wide deadlines Sharp discovered during the launch push that hard deadlines work - they set the tempo and get people energized. Attio now uses them as a core operating tool across the company.

Democratized features. Most legacy CRMs gate powerful features behind enterprise pricing. Attio pushes significantly more power into lower plans - strong automation, flexible data model, and API access on self-serve tiers. Full custom objects unlock at Pro, not Enterprise. The heaviest gating - SSO, dedicated CSM, advanced permissions - is reserved for organizational needs, not core functionality. The logic: the more people who use the tool, the stronger the lock-in. Sharp confirmed: CRM’s value “comes from the number of team members using it… you don’t want it to just be used by a few power users.” Monetization follows seat expansion and usage, not feature paywalls.

Funding

Total raised: $116M - each round funded a different phase - but the priority never changed: product first, distribution second.

Seed funded the larva phase. Four years of building with a small team, no “mainstream” marketing or sales. The $7.7M bought time to build Particle and run the private beta.

Series A ($23.5M + growth ~$33M) coincided with a public launch. Attio earmarked funds to expand the Particle data layer for more complex workflows, accelerate product development including AI features and integrations, and grow GTM presence globally - with emphasis on US and Europe. Engineering and product took the larger share. GTM was explicit but secondary.

Series B ($52M) shifted the narrative to “AI-native CRM.” Attio committed to scaling heavy R&D to ship faster, with focus areas including agent collaboration, granular permissions, and predictive intelligence. Product development priorities: native data ingestion, intelligent workflows, and programmable surfaces (APIs, App SDK). The marketing engine scales in parallel - more regions, more support - but the investment thesis remains product-led: deepen the moat, then distribute.

GV as Series B lead likely isn’t accidental. Google Ventures leading a $52M round for a company built on Google Cloud infrastructure signals strategic alignment beyond financial return. Attio’s architecture runs on the same ecosystem GV’s parent company sells. When your lead investor also provides your core infrastructure, the relationship compounds in both directions - credibility for Attio, ecosystem validation for Google Cloud.

Key Takeaways

1. Infrastructure decisions are distribution decisions. Most founders treat technology as a backend choice and distribution as a frontend problem. Attio proved they’re the same decision. Cloud Spanner wasn’t picked just for performance - it was picked as a foundation of product-led growth - the product should be flexible and meet custom user needs immediately. If your tech stack creates friction in adoption, you don’t have a marketing problem - you have an infrastructure problem.

2. Choosing a small market could be your golden cage. Fundstack had revenue, retention, and happy customers. It still wasn’t a business worth building. The Vertical Trap is dangerous precisely because it looks like success - all the metrics are green, but the ceiling is invisible until you hit it. Before committing years to a niche, size the market. Revenue validates the problem. Market size validates the business.

3. Manual before automated. Attio’s PLG engine - the onboarding flow, the activation triggers, the expansion loops - wasn’t designed. It was discovered through hundreds of manual sessions where founders watched users click, struggle, and leave. The pattern came first. The code came second. Most startups automate assumptions. Attio automated observations. The difference is the reason their onboarding is fast and their user experience is strong.

4. Controlled access beats open access in the build phase. The velvet rope strategy - selective beta, premium pricing, curated users - gave Attio something regular customer acquisition never could: a product shaped by its ideal customer and a controlled feedback loop through cohort-based access. Opening the gates early feels like progress, but it often brings noise and early churn.

5. Hard things are a deferred lever - not a default one. Choosing the harder market, the harder technology, the harder problem doesn’t pay off immediately. It’s a nightmare before it’s a magnet. But when results start proving the vision, the difficulty itself attracts talent, capital, and customers. The key word is “deferred.” Most founders quit before this lever activates.

6. Launch timing is signal stacking, not gut feeling. Attio didn’t launch when the product felt ready. They launched when five independent signals converged: technical stability, retention, willingness to pay, competitive pressure, and a hard deadline. Launching on hope kills startups fast. Attio proved the alternative: stack signals, control entry, commit when the data converges.

“If you were to start again, is this a company you would start again?”
Nicolas Sharp, co-founder Attio

Thanks for your time!
Kasper

• The pricing mechanics and sales strategy behind 600% YoY growth.

• Healthcare “traps” that look like product-market fit failures.

• Distribution levers that unlock access to millions of patients.

• How Sword optimized revenue through: distribution and product.

• The AI shift that increased patient-serving capacity by 7-17x per therapist.

• Two strategic moves that could define Sword’s next growth phase.

Strategic Summary: Sword Health built a $4B company by following first principles - not patients, but whoever pays for them. They avoided the B2C trap, bypassed the Provider trap, and sold directly to US employers who pay for employees’ MSK treatment. Capital efficiency (10.5x vs Hinge’s 2.4x) came from forced scarcity, not VC abundance. Phoenix AI delivers 7-17x therapist efficiency. Reverse M&A buys distribution, not technology. 100% client retention comes from pricing model and superior products. They’re now positioned to capture Europe through “Payvider” partnerships and the emerging senior care market.

Why Sword Health?

Sword Health got 50 rejections from European VCs. Four weeks after one cold email to Khosla, they closed $17M. Five years later: $4B valuation, zero client churn, and they just acquired one of their biggest competitors.

1.7B people suffer from musculoskeletal pain. Treatment is expensive, rehabilitation takes time, effort, and money. What makes it worse - many patients could avoid surgery or serious health consequences if they chose prevention earlier.

The CEO, Virgilio Bento, was 10 years old when his brother suffered an accident and spent 12 years recovering from a one-year coma. Virgilio watched his parents struggle to find the best PT (physical therapist) and saw how much money and time they spent. He decided to change the way people like his brother recover.

Sword Health has the potential to become the US and EU industry leader.

💡 Sword raised $490M vs Hinge Health’s $1.23B - yet achieved a higher valuation ($4B vs $2.9B). Capital efficiency ratio: 10.5x vs 2.4x. Sword’s 4-year “larva phase” of forced scarcity built operational discipline that venture-funded competitors never developed. Hinge could afford inefficiency. Sword couldn’t, and that constraint became their advantage.

The beginning

Bento started the company in Portugal, building on his PhD research (2009-2013), alongside co-founder Márcio Colunas. They set out to create digital therapy to help people with limb paralysis at home.

Before significant private capital was available, they relied on a €1 million EU research grant in 2014 to survive the deep R&D phase.

In 2015, they officially launched SWORD (an acronym for “Stroke Wearable Operative Rehabilitation Device”) and entered a four-year period of extended R&D where financing was extremely difficult.

Beyond the grant, they relied on small seed investments of $100,000, $250,000, and $400,000. Barely enough to sustain operations, let alone scale - forcing the company to operate lean while perfecting its sensor technology and AI.

In the early years, Sword attempted to sell to hospitals and rehabilitation centers. This strategy failed because providers viewed the technology as a disruption to their workflows and resisted digital-first models.

💡Portugal was not Silicon Valley - healthcare is very risky for most VCs. A 2014 seed round would have cost 20-30% equity for maybe $1-2M. The EU grant gave them €1M for 0% dilution. That single decision compounded: when Khosla wrote the $17M Series A check in Feb 2020, founders likely still controlled the cap table.

The “Larva” phase

Between 2015 and 2019, Sword remained in extended R&D mode to perfect their technology. Even though competitors grew and money was tight, Sword chose patience over premature scaling.

While Sword was on hold, their competitors walked into the B2C trap.

Hinge, Kaia, and Omada - when collaboration with clinics failed - tried to pivot from hospitals to treating patients at home. Their product gained traction because it offered higher comfort and lower cost than in-person visits.

Patients referred to physiotherapy typically need to:

• Travel to the clinic

• Find a parking spot

• Wait in line

• Do exercises

• Go home and repeat several more times

It takes time, effort, and money. The product wasn’t perfect, but it was 10x better than visiting a clinic. Great for patients - but to scale, companies had to drop prices. Patients in the EU weren’t used to paying for healthcare out of pocket. The public system covered most of it. Unit economics suffered, and companies like Omada barely survived before pivoting to B2B.

Why the B2C trap exists:

• Broken Unit Economics (CAC > LTV): Acquisition costs on platforms like Facebook were unsustainably high, often exceeding total revenue a user would generate before quitting.

• Low Willingness to Pay: Consumers have a “third-party payer” mindset - they believe healthcare should be covered by insurance or employers. Out-of-pocket apps feel like an unfair tax.

• The Trust Gap: Patients trust doctors (”White Coats”), not Instagram ads. Without a clinical referral, digital therapies were perceived as low-value “wellness” apps or scams.

• The “Cure Paradox”: In B2C, success kills revenue - if the product works and cures the pain, the customer stops paying. In B2B, outcomes drive contract renewals.

• Public Healthcare Barrier (EU): In markets with universal healthcare, citizens view treatment as a tax-funded right. B2C medical solutions become niche luxury products with no path to mass scale.

💡 First-movers pay the “Pioneer’s Tax” - the cost of educating the market, navigating regulatory unknowns, and validating product-market fit through expensive failures. Hinge, Kaia, and Omada paid that tax between 2015-2019. Sword watched, learned from their mistakes, and entered in 2020 with a proven playbook and zero education costs. Second-mover advantage in healthcare isn’t about speed - it’s about letting others de-risk the market for you.

But “wait and build” is a high-risk bet, not a safe play. It only works if your technology is actually superior when you finally enter.

Sword leveraged this dynamic by delaying commercial entry. They used the time to refine their technology and build a defensive moat of regulatory approvals and IP:

• FDA Class II Medical Device Clearance (2016): Validated Sword as a clinical-grade medical device, not just a wellness app.

• CE Mark (~2015-2017): Ensured compliance with European health, safety, and environmental standards.

Additional certifications followed as the company scaled.

The product was neither bad nor perfect. But clinics became gatekeepers - afraid of being replaced. They refused to adopt the technology.

Key reasons:

• Clinician Pushback: Physical therapists viewed the technology as inferior to their own hands and 20 years of experience. They saw it as a hassle that disrupted their workflow, not a tool that helped them.

• Negative Value: For clinics, the technology meant wasted time and technical frustration. Doctors and therapists refused to use it - and patients, who trust their doctors, never got access to home therapy.

The CEO faced a tough decision: keep developing the product and pivot to B2B - without positive feedback from the professionals who rejected it. Risky and stressful.

The only reasonable path: continue building, collect patient success stories as proof points, and then enter the US market.

💡 By delaying market entry, Sword sidestepped the B2C Trap - but walked into the Provider Trap. Even with FDA Class II clearance in hand, clinicians rejected the technology. Regulatory approval proved the product worked - but couldn’t overcome the politics of threatened professionals protecting their turf.

The real counter-move wasn’t more certifications. It was bypassing the gatekeepers entirely. Sword stopped selling to clinics and started selling around them - directly to employers who cared about outcomes and cost savings, not protecting 20 years of manual therapy experience.

💡 In healthcare, the patient is not the customer - they’re the validation layer. Early users exist to prove clinical efficacy, not to generate revenue. The real money flows from whoever is financially responsible for the patient’s health: employers, insurers, governments. Sword understood this. Their competitors learned it the expensive way.

The “Butterfly” phase

Fundraising

In 2019, Bento spent six months trying to secure a Series A in Europe. He faced nearly 50 rejections - “the kind of no that doesn’t go past the first meeting.”

Reasons for rejection:

• Competitor gap: Hinge Health was 3 years ahead with market leadership and “the same solution.”

• No traction: Zero US clients and no scalable path in EU clinics either

• Geography: A hardware-heavy medical startup based in Portugal.

The critical driver behind US-first strategies for European health-tech founders is the difference in payer incentives.

In the US, healthcare is largely employer-funded (self-insured models). High costs hit the company’s P&L directly, creating urgent demand for cost-containment solutions. Companies have direct financial motivation to adopt efficiency tools.

In Europe, healthcare is publicly funded or state-mandated. The payer is the government or a centralized fund. Sales cycles are bureaucratic and slow. The incentive to optimize is diluted by political and social mandates.

Tech founders followed the money - bypassing Europe’s rigid public systems to attack the US market.

This dynamic also shapes European investors. They either didn’t understand the US employer-payer opportunity, or saw no path through the EU’s public healthcare bureaucracy. Either way - pass.

The turning point: a cold email to Khosla Ventures. Within 4 weeks, the deal was closed - $17M Series A.

The VC choice wasn’t random. Khosla is known for backing high-risk, high-impact bets.

💡 50 European rejections. 4 weeks to close with Khosla. What happened in between matters most. The rejections forced a first principles question: where does the money actually flow in MSK treatment? Not in European clinics, not in B2C patients - but in US employers bleeding $15,000+ per MSK surgery on their own P&L.

The cold email to Khosla wasn’t desperation - it was a calculated pivot to the American VC known for backing high-risk, high-impact bets. Founders finally understood which market their product was actually built for.

💡 Look at the Series E structure: $30M primary capital, $100M secondary. Sword only needed $30M in fresh cash - but investor demand was so high, they facilitated $100M in existing shareholder liquidity.

The signal: the company isn’t burning cash, existing investors wanted to partially exit at $3B, and new investors were fighting to buy in. Textbook pre-IPO positioning - create liquidity for early backers while maintaining growth optionality.

GTM Strategy: Distribution

Omada Health almost died selling MSK treatment directly to patients (B2C) in the US. Kaia Health did better with direct sales in the EU but hit a scaling ceiling. Hinge Health pivoted from B2C to B2B successfully and grew fast, becoming the market leader. Sword copied Hinge’s strategy to enter the US market.

In 2 years, they reached unicorn status (2021).

The model is simple. Sword sells digital MSK programs to companies required to cover employee treatment. Employers are eager to pay because it saves them money. Under US law, employers are responsible for their employees’ medical treatment and rehabilitation.

💡Sword didn’t invent the B2B employer model - Hinge did for the MSK market. Copy the leader’s distribution playbook, win on product. Result: 0 US clients to unicorn status in 24-36 months.

The product was attractive to payers because it wasn’t a nice-to-have wellness perk - it was a cost-reduction tool with measurable medical outcomes, backed by licensed physical therapists, not support staff.

The first principle of this market: companies only buy what saves them money or drives revenue. Sword built everything around this - positioning, pricing, proof. The market got it immediately.

Two pricing mechanics made this work:

• First: claims-based pricing - no PMPM fees. Companies pay when they see measurable results and countable savings. Pay for outcomes, not access.

• Second: the “godfather offer”. Companies paid X based on estimates, but got a money-back guarantee if Sword didn’t deliver savings. To stay credible, they ran calculations through independent ROI auditors.

This pricing strategy gave Sword a 70% win rate in competitive evaluations. Within 4 years: 10,000+ employer clients across three continents.

Product quality reinforced the strategy. By February 2025, Sword reported 100% client retention. No client has ever left the platform.

Selling to employers was rational. One contract unlocked access to thousands of eligible patients - without selling to each one individually.

💡 Employers already pay claims when employees get sick. Sword didn’t ask them to learn new buying behavior - just redirected that existing budget. They implemented a pay-per-success model with a money-back guarantee (”godfather offer”) and independent ROI audits, removing the last objection. Result: 70% win rate against competitors, 100% retention, 10,000+ clients in 4 years.

Sword recognized early that large enterprise clients (Fortune 500 companies) rarely make healthcare purchasing decisions without guidance from major benefit consulting firms. So they built relationships with brokers and consultants. It’s a grassroots play - local offices, where individual consultants are the real voice behind recommendations.

Unlike competitors, Sword didn’t organize fancy events. They focused on providing brokers with rigorous clinical data and independent ROI audits. They targeted global consulting firms - Mercer, Aon, Willis Towers Watson - which curate vendor lists for HR directors, but built direct relationships with individual consultants.

This strategy reduced “reputation risk” for brokers, making it safe to recommend Sword based on documented evidence.

Sword also partnered directly with Health Plans. This way, Sword becomes an embedded benefit available to the plan’s entire member network. Massive scalability: a single payer contract unlocks access to millions of potential patients without selling to each employer individually.

Selling to employers means winning one battle at a time. Partnering with Health Plans wins the war - embedding Sword into healthcare infrastructure itself.

💡 Two-front distribution attack. Bottom-up: arm brokers with clinical evidence to neutralize their reputational risk - make recommending Sword the safest choice in the room. Top-down: partner with Health Plans to embed Sword into healthcare infrastructure. Selling to employers wins battles one at a time. Health Plan partnerships win the war - one contract unlocks millions of covered lives.

💡 Timing matters. Sword closed Khosla’s $17M in Feb 2020 - the exact month telehealth usage spiked 78x compared to pre-pandemic levels. Lockdowns forced patients to prefer home-based care. Telehealth visits jumped from 14M (2019) to 62M (2020). Physician adoption: from 15% to 86%. Sword didn’t create this wave - but they caught it perfectly. The product was ready when the market suddenly needed it.

Clinical Validation and Outcomes

Sword invested heavily in clinical evidence, publishing 43 peer-reviewed papers as of 2025. Key findings from randomized controlled trials:

• Efficacy: Digital PT delivers outcomes equivalent to or better than high-intensity in-person physical therapy for chronic low back pain and chronic shoulder pain.

• Engagement: 81% completion rate vs. 40-50% for typical in-person PT.

• Pain Reduction: 62% reduction in pain scores; 67% of members with moderate-to-severe pain report being pain-free by program end.

• Surgery Avoidance: 60-70% reduction in surgery intent; 64% of members become low-risk for surgery.

• Productivity: 68% productivity increase worth $2,916 per member per year in recovered workforce value.

• Cost Savings: $3,177 saved per engaged member annually on MSK care.

• ROI: Independently validated 3.2x1 return on investment; up to 4.4x1 when Predict identifies high-risk members early.

Distribution Channel

In healthcare, distribution is everything - connections, partnerships, sales relationships. Sword didn’t have any of that. So they had to compete with a superior product, “godfather offers,” and innovation.

To maximize distribution, Sword deployed a “Reverse M&A” strategy. They don’t acquire for technology - they believe theirs is already the best. They acquire to “buy the channel”: companies with existing relationships where Sword can inject their product into established contracts.

Acquisitions to date:

In January 2025, Sword acquired Surgery Hero and secured partnerships with 18 NHS trusts in the United Kingdom, serving approximately 10 million patients.

In January 2026, Sword acquired Kaia Health to secure dominance in reimbursed digital MSK care in Europe. Kaia’s exclusive DiGA regulatory approval granted immediate access to 70+ million publicly insured lives in Germany. The deal also absorbed a major competitor with 60+ million covered lives globally and superior computer vision technology requiring no physical hardware. By “buying the channel,” Sword bypassed complex regulatory barriers and established a defensible moat in Europe while consolidating US market dominance.

💡 Most M&A is about technology or talent. Sword’s “Reverse M&A” is about neither - they buy companies for one asset only: distribution relationships.

Kaia acquisition logic: one transaction eliminated a major competitor, absorbed 70M+ covered lives, and bypassed years of German regulatory approval (DiGA). Three strategic wins, one check. This is M&A as market engineering, not empire building.

GTM Strategy: Product Expansion

Sword aggressively expanded into multiple products: Thrive (MSK treatment), Move (injury prevention), Bloom (women’s pelvic health), Predict (AI risk forecasting), and Mind (mental health), Academy (pain education). The goal: shift from “point solution” to comprehensive “platform.”

This strategy was driven by payer expectations, economic efficiency, and the need to maximize ROI.

Large enterprise customers are moving away from point solutions - one vendor for back pain, another for mental health. They prefer platforms that cover multiple conditions. One contract, one provider, everything included.

By offering Thrive, Bloom, and Mind, Sword becomes a one-stop-shop. This increases customer lifetime value, reduces churn risk, and creates barriers for competitors who offer less.

Predict allows Sword to integrate deeply with client medical claims data, making them an essential component of the care continuum - not just an add-on app.

Unit economics improve significantly. Treating multiple conditions per member - back pain and comorbid depression, for example - multiplies value per patient.

The endgame: become the end-to-end operating system for MSK. Own the entire patient journey vertically - from prediction to prevention, through treatment and recovery.

💡 Evolving into a platform was a unit economics optimization move. Initial CAC - hardware shipping and patient onboarding - is a one-time sunk cost. Upselling additional verticals like Bloom incurs near-zero marginal expense. This multiplies Lifetime Value by keeping patients active across the ecosystem, while giving Sword pricing flexibility to structure bundled deals that point-solution competitors mathematically cannot match.

Phoenix

Phoenix launched in June 2024 as the “AI Care Specialist” - a shift from “AI-assisted digital therapy” to “AI-first care.” Unlike Sword’s previous technology, which primarily provided feedback on movement, Phoenix is a conversational interface capable of natural, spoken dialogue. It acts as an always-available therapeutic agent combining real-time monitoring with empathetic interaction.

This fundamentally altered Sword’s unit economics by unlocking massive scalability:

• Clinician Efficiency: Therapists can now manage ~700 patients simultaneously - a massive increase from traditional limits.

• Staffing Reductions: The shift to AI led to laying off ~17% of therapists in 2024, proving fewer humans can serve more patients.

• Structural Cost Advantage: This clinician-to-patient ratio creates a scalable cost structure that labor-intensive models cannot match.

Phoenix also deepened user experience: natural conversation, real-time guidance, full personalization. As a support tool for PTs, it reduces operational costs and drives scalability - especially where clinical supply is a bottleneck.

💡 Phoenix is a revenue engine designed to convert user experience directly into cash flow. By replacing static interfaces with natural conversation, it increases patient engagement - the single most critical metric in a business model where revenue depends on active usage and outcomes.

The efficiency math: traditional PT manages 40-100 active patients. Sword with Phoenix: ~700 per therapist. That’s a 7-17x structural cost advantage. The 17% therapist layoffs in 2024 weren’t downsizing - they were proof the model works.

Nuances and Key Takeaways

A few patterns that built a $4B company:

1. Constraint as advantage EU grant instead of VC. $1M budgets with 12-month kill deadlines. Scarcity forced innovation that well-funded competitors never developed.

2. Follow the money, not the patient First principles question: who actually pays? Not patients, not clinics - employers responsible for employees’ MSK treatment. Every strategic decision flowed from this insight.

3. Speed as moat 15-day client onboarding. 24-month path to unicorn. CTO moved to Chief Strategy Officer because at scale, strategic velocity matters more than technical execution - especially when product-market fit is proven and the market is growing.

4. Institutionalized scarcity They didn’t just talk about cost discipline - they built a system for it. The innovation formula:

• Find a General Manager (domain expert)

• Give them $1M budget

• Set a hard deadline: 12 months

• If MVP validates (like Bloom did) → invest more

• If it fails to prove itself → kill immediately

This is how you innovate without burning cash on endless R&D.

5. “We’ve just done 5%” mindset Bento repeats this in interviews: mentally, they operate as if they’re still at the beginning. Same philosophy as Bezos’s “Day 1” - the moment you feel established, you start dying. This mental frame keeps a $4B company acting like a hungry startup.

6. Product-centric obsession - the foundation, not the wrapper Most companies are “assemblers” - they combine existing tools, platforms, and skill sets into a service. Deep-tech is different. You can’t build a medical AI from off-the-shelf components. The technology is the business.

In digital health specifically: if clinical efficacy fails, nothing else matters. Sword stayed close to domain experts and treated product development as survival, not iteration.

7. The Evidence Wall Sword systematically converts technological innovation into hard, verifiable assets - legal and scientific. 43 peer-reviewed papers. 37 patents. FDA Class II clearance. CE Mark. DiGA approval.

The power isn’t in any single credential. It’s in the critical mass: an ecosystem of credibility that can’t be challenged in a sales meeting or due diligence process.

Capital can be raised fast. Building this library of clinical and legal proof takes years. Sword used time as an asset, creating a moat that new entrants can’t leapfrog with money alone.

What next?

The “Payvider” Injection Strategy

Sword needs an aggressive move toward European subscription healthcare giants - Bupa (owner of LuxMed), AXA, DKV. Instead of building distribution or doing another acquisition, inject Sword’s technology into the bloodstream of these players.

Current subscription packages from these giants are leaky. Physiotherapy and mental health are treated as afterthoughts - often limited or excluded entirely. This is the perfect gap. Sword doesn’t enter as competition but as a “Plug-and-Play Premium Module” that patches this hole. Bupa alone operates in 190 countries.

The European market is screaming for efficiency. In the UK, private medical insurance (PMI) costs rose 12.6% in 2024. Operators like Bupa and Vitality are desperately seeking technology that reduces treatment costs - not just raises premiums. Sword is the answer.

The fear that Europe is less profitable than the US (where employers pay) is a cognitive bias. The solution: a Hybrid Model that distributes cost burden while protecting unit economics.

1. The Base (Volume): Employer/insurer pays. European markets offer consolidated entry points that the fragmented US market lacks - one partnership with Bupa or DKV unlocks millions, versus selling employer-by-employer in the US.

2. The Savings: Operator pays (e.g., LuxMed/Medicover), giving up margin in exchange for Sword clearing queues from their physical clinics.

3. The Premium (Co-pay): Patient pays. In Europe (especially the Netherlands, where 55% of healthcare spend is private insurance), consumers are conditioned to pay extra for a premium of faster access.

Partnerships with Bupa Group allow Sword to scale while maintaining margins. This isn’t a fight for retail customers. It’s a fight to become the default operating system for European “Payviders”.

The “B2C Silver” Strategy

By 2050, 34% of Europe’s population will be over 60, consuming 70%+ of healthcare spending - mostly on chronic diseases concentrated in seniors. Projected clinician shortage: 1.8 million. The math doesn’t work.

B2C Silver is not the B2C trap. Seniors aren’t working-age patients expecting employers to pay - they’re no longer “productive assets.” Corporations have zero incentive to fund retiree care. The State becomes Payer of Last Resort - and it’s failing.

The Incentive Conflict Public hospitals are a dead end. They get paid when beds are full - preventative technology that keeps seniors home hurts their revenue. States pay for cures (post-fall rehab), not prevention (mobility training).

The Poland Case Poland shows the opening in real-time. NFZ faces a 4.6B PLN budget gap in 2026. 55% of healthcare spending goes to the 60+ population (26% of citizens, projected 40% by 2060). In December 2025, NFZ cut home physiotherapy reimbursements - making human-delivered home rehab economically unviable.

The State admitted it can’t afford human visits in patients’ homes. Sword has no travel time constraints, no staffing limits. When public systems retreat, AI-first care is the only scalable alternative.

The Strategic Maneuver: “Sword Senior”

1. Sell “System Survival,” Not Therapy - The pitch to Government is Capacity Management, not wellness. Hip fracture costs the State up to €2.5k. Sword prevents it for a fraction. Pure arbitrage on public spending.

2. The “Privatized” Wedge - Wealthy seniors (or their children) pay out-of-pocket to escape public system dysfunction (NPS -27%). They’re buying independence from a broken system, not a wellness subscription.r

Public systems are retreating. Demographics guarantee it gets worse. The question isn’t if this market opens - it’s who captures it first.

“We’ve just done 5%.”
Virgílio Bento, CEO Sword Health

Thanks for your time!
Kasper

I’m Kasper and this is a white audit of “Klinika Holi”. An external, signal-based analysis of a real business - built from public data, observable behavior, and pattern recognition. No access to internal dashboards.

In this article, you’ll learn:

• Why Klinika Holi is worth analyzing right now.

• How its growth system actually works.

• What drives growth and where the leaks are hiding.

• Actionable levers that will drive scalable growth in 2026.

Strategic Summary:
Holi is scaling in the medical obesity market by building a hybrid moat (AI + Medical Ops). However, their growth engine is currently leaking at the pricing stage. Meanwhile, their content strategy is stuck in a "Hamster Wheel" of high-frequency, low-compounding output. Fixing these points and activating a few hidden levers could drastically boost their conversion efficiency.

1. Why This Company Matters Now

While the market is flooded with AI startups that are heavily focused on building pure-play SaaS, Klinika Holi is tackling a far more complex category: Obesity Treatment. This sits at the intersection of medicine, behavioral change, and long-term engagement.

Most AI products lack defense; the technology is commoditized. Holi is different. Their hybrid model (AI + Physical Operations) creates a genuine moat. You cannot simply “copy-paste” a clinic that requires doctors, trust, and medication.

Look also at the execution. They built the platform, staffed the medical team, launched the marketing and achieved net profitability.

The Year 1 Traction:

• Funding: ~€710k (Pre-seed, late 2023)

• Scale: 1,000+ active patients

• Performance: €190k Revenue → €24k Net Profit

The Signal: Most startups burn cash to fake growth. Klinika Holi posted a net profit in its first full operating year. That is worth dissecting.

By late 2025, Holi closed a €3M Seed round and reached 2,500 active patients. According to the CEO, the roadmap for 2026 is clear: expansion into Spain and Italy.

Three elements make this trajectory worth analyzing:

1. Early Viability: The business is not bleeding cash. This proves pricing discipline and healthy unit economics.

2. Consistent Traction: Growth from 1,000 to 2,500 patients is steady, not explosive. In MedTech, predictability is more valuable than volatility.

3. Capital Escalation: The €3M round will accelerate growth.

Now, the question is not whether the company is growing - but how.

2. Product & Market:

Klinika Holi is not for people who want to “drop 5 kilos before summer.” The company explicitly frames obesity as a medical condition requiring intervention, not an aesthetic goal requiring motivation.

The target customer deals with obesity or metabolic disorders - insulin resistance, Type 2 diabetes, or cardiovascular risk. The positioning is strictly preventive and medical, not aspirational.

Market size and structural opportunity

Obesity is a structural crisis. In Europe alone, more than 200 million people struggle with obesity, creating a market valued at over €43 billion. It is a long-term, demand-heavy category driven by demographics, lifestyle, and systemic healthcare inefficiencies.

Unit economics signal

Holi operates on an expected customer lifetime (LTV) of 6 to 12 months. This implies recurring engagement and behavioral change supported by medical oversight—not a one-off transaction.

From a business model perspective, this LTV window suggests:

• Higher CAC Tolerance: They can afford to pay significantly more to acquire a user than mass-market fitness apps.

• Trust as the Primary Gate: Conversion relies on upfront credibility, not impulse.

3. The Audit: How Demand Enters

Holi operates in a “medical environment.” In a regulated, trust-heavy category, the right strategy is Demand Capture, not Demand Creation. You don’t “hype” medical treatment; you build exposition and credibility.

3.1 Social Media

LinkedIn: Correctly Deprioritized

LinkedIn is used in a low-frequency, corporate mode: company milestones, funding, key announcements. This is the right call. LinkedIn is not a primary demand channel for obesity treatment, and forcing volume here would add noise without ROI. I can’t see red flags.

Facebook & Instagram: the “Hamster Wheel” trap

Activity on Facebook and Instagram reveals quantity over quality. The system is optimized for output, not outcome. The company has published ~800 Reels in three years. The volume is massive, but engagement and account growth are disproportionately low. The content is visible, but it doesn’t stick.

Compare this to market leaders like Michał Wrzosek or Artur Karapetyan. They win because they teach dynamically. They build authority through explanation before they attempt to sell. Their content is an asset that compounds; Holi’s content “disappears quickly”.

Holi has the ultimate asset - real doctors and medical expertise - but the current format doesn’t exploit it.

⚠️ The Leak: High production volume with low asset value,
💡 The Lever: Shift from “Brand Content” to “Dynamic Expert-Led Education.”

3.2 Paid Acquisition

Meta Ads:

Paid ads operate under strict medical regulations: no direct pricing claims, no “before/after” promises. Within these limits, the company actively tests diverse themes, especially for Meta Ads:

• Transformation Narratives (Focus on the journey).

• Modern Methods (GLP-1/Medical approach).

• The Struggle (Validating the difficulty of weight loss).

• Motivation (Psychological support).

While the themes are correct, an external review of the Ad Library does not reveal a visible system based on a structured Communication Matrix or Persona Awareness Levels.

For a medical product, the communication needs to distinguish between:

• Level 1 (Problem Aware): Focused on the pain (“Why can’t I lose weight?”).

• Level 2-4 (Solution/Product Aware): Focused on the choice (“What’s on the market, what to choose?”).

To scale efficiency, the strategic fix is to implement a Modular Creative Grid (Slogan + Visual). This allows for rapid testing of specific angles against value propositions and awareness levels. This approach is successfully used by leading Polish brands like ForMeds or Health Labs, which rely on simple, convincing narration.

⚠️ The Leak: Mismatched messaging: ignoring the user’s Awareness Level and stage at Customer Journey.
💡 The Lever: Implement a Modular Grid to target specific user mindsets.

Google Ads: High Intent & The Hidden Asset

Google Ads is a strong strategic choice because it captures high-intent traffic. Unlike social media (scrolling), search traffic consists of users actively looking for a solution.

Apart from standard search campaigns, the most interesting element is how they utilize a specific Lead Magnet. They promote a valuable free course, but with a twist: it is accessible only via ad clicks. It is invisible on the main site unless you find the specific landing page via Google.

The Diagnosis: Great Asset, Limited Leverage

• The Logic: Using the course as a “curiosity trigger” and a soft filter for paid traffic.

• The Flaw: Education is the most powerful trust-builder. Hiding your best educational asset from organic visitors restricts your ability to build an owned audience.

The right move is to integrate the course into the main “Knowledge Base” and ungate it in exchange for an email. Why? To build a First-Party Data asset (Newsletter). In a High-LTV model, you need to own the contact channel to educate and nurture the user until they are ready to buy - rather than paying Google for every single interaction.

⚠️ The Leak: Restricted distribution: High-value asset limited to paid traffic only.
💡 The Lever: Convert the hidden course into a public Lead Magnet for a Nurture Newsletter.

3.3 Organic & SEO

SEO Content: Built for Algorithms, Not for Authority

Content production in 2024 appeared intentional and correct, successfully building early topical coverage. By the beginning of 2025, the domain reached hundreds of TOP10 keywords in Google Search.

In 2025 there is a visible mass refresh of article dates. This tactic correlates with distinct ranking volatility, as data suggests a decline in TOP3 and TOP10 visibility around Q2 2025. Two scenarios are likely here:

1. Self-Inflicted: Large-scale mechanical refreshes disrupted established authority signals.

2. Reactive Failure: The refresh was a desperate reaction to a Google Core Update hit—which ultimately failed to reverse the downward trend.

Regardless of the cause, uniformly updated dates signal content optimized for SEO mechanics, not for readers.

Crucially, the content lacks human anchors: case studies, practitioner-led essays, and named experts sharing real clinical experience. This exposes a major weakness: while generic content may still rank in traditional Search (SERP), it fails in LLM optimization.

LLMs increasingly surface content from Reddit or LinkedIn because they reward unique, first-person perspectives over rewritten definitions. Therefore, shifting focus to Answer Engine Optimization (AEO) grounded in E-E-A-T principles is no longer optional - it is critical.

Right now, Holi’s content is searchable - but likely not yet widely quotable.

⚠️ The Leak: Algorithm-first updates and “thin” authority.
💡 The Lever: Shift to Experience-Based Content (unique knowledge) to win both Google and LLMs.

3.4 Diagnostic Tools: The BMI Calculator

The decision to build a BMI calculator was a highly effective strategic move, tapping into a massive, recurring demand pool. Market analysis reveals a rare great opportunity:

• Volume: ~135,000 monthly BMI-related searches in Poland.

• Intent: Purely diagnostic, not just inspirational - aligning perfectly with Holi’s medical positioning.

• Competition: Very low.

• Cost: CPC at ~PLN 0.03. (~EUR 0.01)

This indicates strong intent with almost no serious advertiser pressure. Importantly, BMI searches are self-diagnostic: users are likely identifying as underweight or overweight, which is precisely the segment Klinika Holi targets.

The Execution Gap (UX) However, the current execution creates unnecessary friction.

• Scrolling Requirement: Results are not immediately visible without user action.

• Visual Clutter: The layout is distracted by decorative images that add no functional value.

• Friction: It lacks a seamless “one-click share” or “save result” feature.

The tool must imply instant utility: input → result. No clutter. Just a seamless top-of-funnel qualifier that fits virtually on a single mobile screen.

To illustrate this, let me show you a retirement calculator our team built for ZUS (the Polish Social Security Institution). This project was awarded at HackYeah! - one of Europe’s biggest hackathons. Why? Because we turned a complex problem into a simple UI. We created a frictionless UX focusing only on key features, all on one screen, without any distractions.

Consider the missed paid opportunity. With a CPC as low as ~PLN 0.03, BMI queries should not be treated solely as SEO traffic. There is a strong business case for running dedicated Google Ads here to own the entire “diagnostic moment.” This strategy builds top-of-funnel volume cheaply, introducing the Holi brand before users even start looking for specific treatments. It turns a simple utility into a brand awareness engine.

⚠️ The Leak: UX friction and passive reliance on SEO; ignoring the low-cost paid opportunity.
💡 The Lever: Use Paid Ads to dominate the Diagnostic Moment and optimize UX for instant gratification.

4. Conversion & Trust: Where Interest Turns Into Commitment

4.1 Onboarding: build momentum

Klinika Holi positions itself around a clear message: “Discover obesity treatment that works with you.” The communication is process-led, not aspirational.

The onboarding process builds credibility through strict qualification and intentional exclusion. The journey starts with a medical questionnaire built in Typeform. It is light, fast, and non-intimidating, yet creates a sense of personalization and medical seriousness. Follow-up communication adapts well to declared motivations.

Crucially, not every user is accepted. The possibility of disqualification introduces an element of credibility and medical integrity. In a category often driven by overpromising, exclusion acts as a strong trust signal.

Observation: Based on repeated test completions, this stage builds momentum rather than friction. I can assume no major conversion leaks here.

4.2 Trust Signals: Institutional Over Emotional

Holi prioritizes institutional authority over emotional engagement, clearly optimizing its early positioning for credibility rather than speed or hype. This strategic choice is evident in several publicly observable signals:

• Social proof through scale: Prominently communicating 2,500+ patients served. This acts as a reassurance mechanism: “others have already trusted us.”

• External validation: Ratings on kliniki.pl and a medically grounded narrative.

• Expert-forward positioning: The entire team (doctors, dietitians) is visible. This is not standard for many digital services. Here, the people are the product.”

There is a notable disparity between the company’s operational scale and its visible social proof. Despite serving over 2,500 users, the volume of visible success stories is limited (only 4). This stands in sharp contrast to competitors like Centrum Respo or Sylwetka Hollywood, which aggressively leverage before/after stories and social proof as their primary conversion engine.

Note: This discrepancy is not a judgment yet - but a signal worth examining.

Early Interpretation: At this stage, Klinika Holi favors institutional trust (credentials, structure) over emotional proof (transformations). While this likely increases credibility among cautious, medically-oriented users, it may cap conversion velocity compared to more aggressive models.

It is crucial to emphasize that unlike “invisible” chronic conditions, obesity is visible. Successful treatment results in a physical transformation that patients are often proud to share - much like in orthodontics.

A prime example is Invisalign, which has mastered this dynamic. By turning patient pride into viral social proof, they scaled to 21M patients and over 4.1M Instagram posts (September 2025). For Holi, this currently represents a significant, untapped asset.

4.3 Pricing & Purchase Experience

A significant bottleneck emerges at the pricing stage, where the interface creates friction through cognitive overload. Too much information competes for attention, making it difficult for users to answer three fundamental questions within seconds:

• What exactly do I get?

• How much does it cost?

• What is not included but I have to pay for?

Compared to classic SaaS or premium service benchmarks, clarity here suffers significantly.

For context, consider this example from the sports-medicine sector: Artur Karapetyan’s platform. It illustrates a high-contrast approach - a simplified layout that immediately directs the user to the core value proposition, reducing cognitive load.

Critical Flaws in Holi’s Pricing Model:

1. The hidden cost trap: there is no clear indication that medication costs are excluded from the program fee. Users may realize too late that the offer is just “consultations plus extras”, not “comprehensive treatment”.

2. Weak USP (Unique Selling Proposition) & the “why pay?” objection: The USP is currently insufficient to counter the “DIY” mindset. A rational objection emerges: “Why not just do blood tests privately and consult a doctor ad hoc?”

Additionally the current USP fails to address the competitive landscape. Holi is positioned between two strong alternatives:

• Public Healthcare (NFZ): For price-sensitive users.

• Corporate Subscriptions (LuxMed, Medicover, Signal Iduna etc.): For users who already have access to private care.

The message does not sharply articulate why a user should pay extra for Holi when they already have access to these systems. The value of specialization and speed is lost.

A clear strength of the pricing strategy is its payment flexibility.

Monthly plans, discounted 6-month prepayments, and Klarna integration are smart choices. They effectively lower entry friction for a high-ticket service and support LTV realization.

This mirrors the successful strategy of Tutlo (online English courses), proving that flexible financing is key to mass-market adoption of premium services.

In parallel, the pricing strategy creates a structural ‘conversion cliff’ due to the absence of an intermediate step between interest and high-ticket commitment. To reduce this friction, Holi should adopt a mechanism used by the beauty sector: the ‘small payment before high commitment’ model.

The ‘High-Ticket’ Logic: Consider services like hair transplants or laser treatments >250€. Selling such services digitally without human-to-human interaction is notoriously difficult.

The standard, effective model in private clinics is to offer a paid diagnosis or consultation first. This creates a necessary “soft landing”. It allows the user to make a micro-commitment and build trust before facing the decision to purchase the full medical program.

A potential ‘Bridge’ offer could be structured as follows:

1. Initial consultation with an obesitologist for ~250 PLN. Includes full diagnosis and next-step recommendations.

2. If the user continues, this fee is credited toward the program price. If not, the 250 PLN covers the CAC.

This mechanism lowers psychological barriers, builds trust through diagnosis, and moves the user into “skin in the game” mode

⚠️ The Leak: A direct jump from a questionnaire to high-ticket pricing (Commitment Shock).
💡 The Lever: Use a personalized medical consultation as a paid entry product (The Bridge).

5. External Validation: Why the ‘Holi Method’ Matters

A critical external signal reinforcing Holi’s positioning comes from recent reporting by the Financial Times regarding GLP-1 drugs (e.g., Ozempic).

Data from the US indicates that patients who discontinue obesity medication often begin to regain weight. While pharmacology is highly effective during use, outcomes weaken significantly once support is removed. This proves a vital point: obesity is a chronic condition, not a short-term hurdle.

Without fundamental behavioral changes, drugs alone cannot sustain long-term results. This external validation strengthens Holi’s core thesis. By focusing on the ‘system’ (doctor + dietitian + tech) rather than just the ‘prescription,’ Holi is positioned on the right side of the clinical evidence.

8. Final results: Levers, Leaks, and Strategic Moves

💡 TOP 3 Growth Levers

1. BMI Calculator as Awareness Engine
   135,000 monthly searches at PLN 0.03 CPC. Fix the UX and scale paid campaigns to own the “diagnostic moment” before users even search for treatment.

2. Paid Medical Entry Offer
   A paid consultation that lowers the entry barrier. It builds trust through a small first step, which then credits toward the full program price.

3. Systematic Opinion Collection
   With 2,500 users, there is massive untapped social proof. Build a repeatable system to capture and distribute patient transformation stories at scale.

⚠️ TOP 3 Growth Leaks

1. Pricing Page Overload
   High cognitive load, unclear medication exclusion, and no low-entry option. This is the primary point of conversion drop-off.

2. Avg. Quality Content Volume
   800+ Reels and algorithm-first SEO, but low engagement and thin differentiation. This is activity without compounding brand awareness.

3. The Gated Content Gap
   There is significant unused potential in building a newsletter database through free, gated video lessons (The “Hidden Online Course” model)

💎 Strategic Ideas

1. Partnerships with LuxMed, Medicover etc.
   Placement in clinics (posters near diabetologists/dietitians’ offices). Builds trust through institutional association and physical presence.

2. Community-Led Engagement Model
   Obesity can be isolating. Organize local meetups (movement, education) led by dietetics or sports science students. This reinforces the “ecosystem, not just a clinic” positioning, similar to the “run clubs” that have been gaining popularity in recent months.

3. Influencer Diversification
   Increase collaboration with influencers. Target nutrition and fitness creators who can authentically integrate the “Holi Method” into their lifestyle content.

4. Expert-Led Evergreen Content
   Shift from high-frequency video to practitioner-led, evergreen education. This builds the authority needed for high-intent social search and LLM discovery.

Ready to improve your growth engine?

I use The Lever Map method to turn your internal data into a clear roadmap, calibrated to your specific goals and challenges. You get a tactical action plan for the next 30–90 days to move the needle where it matters most.

📩 Let's talk: hello@kasperdudek.com or [Book a 15-min intro call here]