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Data-Driven Pivots: How Thoughtful AI Found Its Healthcare Sweet Spot

Most founders dream of product-market fit. Few have the discipline to discover it through rigorous data analysis. In a recent episode of Category Visionaries, Alex from Thoughtful AI shared how mining customer data revealed their true market opportunity – and how being an industry outsider helped them seize it.

The journey began with a classic startup scenario: a promising solution searching for its perfect problem. “When we first started the model we created, were a notorious amazing solution, but didn’t really have a problem set that was compelling for it,” Alex recalls. Like many early-stage companies, they cast a wide net, selling automation solutions across multiple industries.

By 2022, they had accumulated a diverse portfolio of 85 robots deployed across 35 customers in various sectors. Instead of continuing to spread thin, they took a critical pause to analyze their data. “We looked at all of our robots…trying to figure out where is product market fit, like, which one of our robot segments are the highest ROI,” Alex explains.

The numbers told a clear story. Their healthcare implementations were delivering staggering results: “We looked under the hood and all of our mid market healthcare companies, the robots were 1000% ROIs. They were spending 200% net revenue retention.” This discovery prompted a decisive pivot to focus exclusively on healthcare providers.

But the real insight wasn’t just about which market to serve – it was about how to serve it. Coming from an aerospace and defense background, Alex approached healthcare with fresh eyes: “I love it because I have no preconceived notions in healthcare of how it’s supposed to be done. So I come with a beginner’s mindset every day. First principles of what’s the core problem here, and how are we solving it best for the customer experience?”

This outsider perspective helped them reimagine how automation technology could be sold and implemented. Rather than following the traditional enterprise software playbook of separate licenses, implementation partners, and internal teams, they consolidated everything into a single offering. “We are your internal team, we are your implementer, and we are your technology,” Alex explains. “And that means the price is one price. So when you buy us, it’s very easy to model ROI.”

They’ve also taken a bold stance on aligning incentives. “We actually have clauses state that you don’t have to pay us until we achieve those outcomes,” Alex notes. This approach has resonated strongly with healthcare executives focused on concrete metrics like cash flow and collections.

The company’s commitment to quality over quantity extends to their growth strategy. “That’s why we’re only selling one customer a month. That’s our capacity right now,” Alex shares. “And we tell our customers we’re committed to quality and excellence, not just pushing seats, pushing pools.”

This disciplined approach is backed by ambitious but focused goals: “We believe getting to 100 million ARR, 100 customers, we can achieve that by 2026.” To maintain their high-touch service model while scaling, they’re investing heavily in internal AI tooling. “We actually believe we have a strategy. The company is 100 million ARR, 100 customers, 100 employees.”

The story of Thoughtful AI offers valuable lessons for founders navigating their own path to product-market fit. First, let data guide your focus – even if it means pivoting away from existing customers. Second, being an industry outsider can be an advantage if you approach it with genuine curiosity and first principles thinking. Finally, don’t be afraid to challenge conventional business models if you can deliver better outcomes for customers.

As Alex puts it: “We realize that innovation is happening at a much faster rate…so we need to stay ahead of the curve.” By remaining focused on their healthcare niche while continually investing in R&D, they’re positioning themselves for sustainable long-term growth rather than just chasing short-term expansion.

Actionable
Takeaways

Embrace Beginner's Mind to Reimagine Legacy Industries:

As an outsider to healthcare, Alex approached the notoriously complex and change-resistant industry with fresh eyes. By focusing relentlessly on customer needs and existing processes, Thoughtful AI built a solution that slots in seamlessly to drive immediate results. Founders should lean into their beginner's mind and challenge legacy assumptions when tackling entrenched sectors.

Invest in R&D to Systematize Bespoke Services:

Thoughtful AI's white-glove, custom-built approach has been key to landing and expanding enterprise accounts. But Alex recognizes this high-touch model must be tempered with robust internal systems to reach scale. By using AI to augment everything from customer onboarding to ongoing support, Thoughtful AI aims to maintain its personal touch while accelerating growth. Founders should balance artisanal experiences with automated engines.

Tie Pricing to Measurable Business Outcomes:

To build trust with enterprise buyers, Thoughtful AI directly links its fees to the ROI it generates for customers. By putting skin in the game and getting paid on results, the company creates aligned incentives and mitigates perceived risk. Founders should explore performance-based pricing models that demonstrate real value creation for clients and boost their confidence to buy.

Sequence Your Expansion From Beachhead to Bowling Alley:

While Thoughtful AI's automation platform has horizontal applicability, Alex is laser-focused on dominating the healthcare market before pursuing other sectors. By establishing a reference customer base and playbook in a trillion-dollar market, the company will have the traction and credibility to attack adjacent industries. Founders should sequence their expansion plans to balance focus and optionality.

Plan Proactively for Technological Disruption:

Even as Thoughtful AI rides the first wave of AI-powered automation, Alex and his team are already preparing for the next phase of innovation. By collecting rich process metadata, they are primed to harness emerging large language models and other AI capabilities to extend their platform. Founders must peer beyond the horizon to anticipate how their solutions may be enhanced or disrupted and plan accordingly.

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