Overview of Vertical SaaS: $0 to $10M ARR With Flat Pricing for Everyone
Episode summary of Omer Khan’s SaaS Podcast interview with Hewitt Tomlin, co‑founder of TeamBuildr. Hewitt explains how TeamBuildr — a vertical SaaS product for strength & conditioning coaches — grew from campus side project to a $10M ARR, 45‑person, 100% bootstrapped company. Key themes: product→customer pivot, deliberate go‑to‑market (early outbound → reputation-driven inbound), a flat pricing philosophy (same price for high schools and NFL teams), and a pragmatic, augment‑not‑replace approach to AI.
Guest & company snapshot
- Guest: Hewitt Tomlin, co‑founder of TeamBuildr (teambuildr.com).
- Business: SaaS for strength & conditioning coaches (program delivery, workflow management).
- Traction: ~$10M ARR, 45 employees, bootstrapped (no outside funding).
- Timeline: Started building ~2011; first paying customer in summer 2012; ~5 years to reach first $1M ARR.
- Founders: Hewitt and James still operate under their original 2012 operating agreement.
What TeamBuildr does and product evolution
- Initial idea: mobile/social app to replace paper workout packets for college athletes.
- Pivot: conversation with a university strength coach revealed the real need was improving coaches’ professional workflows → became B2B web portal for coaches.
- Product focus: job‑function centric (strength & conditioning), not a broad vertical; designed to serve the same core job across high school, college, pro, and international markets.
Go‑to‑market & growth playbook
- Early phase: founder-led cold calling and demos; intense relationship building with early adopters (not passive free users).
- Free beta approach: product + founder time/consultation to secure real feedback; early users treated as partners.
- Product‑market fit indicator: inbound demand—prospects filling demo/quote forms and requesting calls (rather than founder chasing).
- Channel mix over time: outbound → customer service deliverables → reputation-driven inbound. TeamBuildr is primarily an inbound success story.
- Timeline & effort: 0→100k (multi‑year while moonlighting), quit job → accelerated growth to $1M, continued scaling to $10M ARR.
Pricing & customer strategy (flat pricing)
- Unique choice: charge the same price to small high schools as to NFL teams.
- Rationale:
- Product solves the same job across tiers; technical differentiation between buyer segments is limited.
- Flat pricing reduces product complexity and sales friction.
- Big logos (colleges/NFL teams) were used as social proof to accelerate adoption in the high school market.
- As a bootstrapped business, avoiding multi‑product complexity made execution simpler and reputation stronger.
- Practical result: volume focus (high school market makes growth viable) while maintaining credibility with large customers who get a “deal.”
AI stance and competitive dynamics
- Competitor: some vendors (e.g., Vault) push AI‑generated workouts, implying reduced need for human coaches.
- Hewitt’s view:
- Be pragmatic: listen to customers first; don’t adopt AI for novelty’s sake.
- AI as augmentation, not replacement. Use AI internally to improve employee productivity and quality; use it for synthesizing data to inform coach decisions rather than replacing coaching judgment.
- Encourage selected, measured adoption (table stakes internally; customer features only when aligned to real outcomes).
- Reputation and stewardship of the profession matter — TeamBuildr positions itself to enhance the coaching role, not make it obsolete.
Key lessons, tactics and repeatable advice
- Talk to real users early; pivot if a customer’s workflow points to a different problem than your original idea.
- Give free product access as a relational exchange (time, coaching, partnership), not a passive license.
- Product-market fit: look for inbound demand and customers who proactively request demos/quotes.
- Build around a job function to enable horizontal adoption across multiple verticals with minimal product fragmentation.
- Keep pricing simple and understandable to all stakeholders involved in purchasing decisions.
- Use large customers as social proof rather than purely as high‑margin targets when bootstrapped.
- Be selective and intentional about AI: incorporate where it improves outcomes and employee performance.
Notable quotes
- “The first users are so much more valuable than cash in the bank.”
- “If people are coming to your website and filling out a form asking for a call… that’s when product‑market fit is being achieved.”
- “I’m not slapping an AI chatbot… AI should enhance the profession. I am not interested at all in understanding how AI can take away from the profession or replace it.”
- “My business is me, my employees and my customers. That’s it.” (on not having investors)
Lightning round highlights
- Advice he disagrees with: “Start with the end in mind” (when that means designing solely for an exit).
- Recommended book: Do More Faster (Brad Feld).
- Skill improved most: listening.
- Productivity habit: breathing and grounding; energy hygiene via an executive coach.
- Passion outside work: family (three children) and collecting cacti.
Actionable checklist for founders (what to apply)
- Validate early by listening to user workflows; be prepared to pivot.
- When offering a free beta: pair product access with founder time and structured feedback sessions.
- Measure product‑market fit via inbound demand, not just marketing activity.
- If you’re verticalizing, consider designing around a job function to scale across sub‑verticals.
- Keep pricing packaging simple so multiple stakeholders can understand it quickly.
- Use marquee customers as proof to accelerate adoption in your primary volume market.
- Adopt AI internally first to boost quality + speed; add customer‑facing AI only when it directly improves the outcomes coaches care about.
If you want to learn more: visit teambuildr.com (no “e”) or reach out to Hewitt on LinkedIn — he remains active there.