6 BORING Businesses that Always Make Millionaires (90% success rate)

Business models for “boring” wealth (cash-flow focus)

David (CEO of Filterbuy) argues that making large money comes from finding “boring” businesses with dependable demand, then executing with disciplined operations.

Two main cash-flow categories

• Property-oriented businesses
  • Often perceived as “passive,” but still require ongoing maintenance, location strategy, and operational upkeep.
• Service-based businesses
  • Typically more capital-light and can scale faster if you build the right knowledge + systems.

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Playbooks / frameworks mentioned (action-oriented)

1) Property business fundamentals (what makes them work)

ATM businesses

Core requirements:

• Location (where the machine is placed)
• Availability/maintenance (machines must be functional)
• Cashflow readiness (you must keep money in the machines)
• Negotiation + infrastructure to keep machines in the best spots

Laundromats

Success depends on:

• Location + convenience
• Consistent cleanliness/safety
• Machine maintenance
• The reality that “set and forget” is usually false

Scaling note:

• Laundromats can require more capital than expected.

Equipment rental (lesson from an operations failure)

If you can keep equipment in stock and working, customers pay a daily premium.

Emphasis:

• Maintenance
• Logistics (getting equipment to customers reliably and quickly)
• Start small and learn before expanding

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2) “Cash flow checklist” (operational priority over income)

• A highlighted step: “The first step… has absolutely nothing to do with how much you make, but how much you spend.”
• Example used to illustrate how operating discipline and margins compound (window cleaning).

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3) Service business scaling playbook

• Start locally

  • Become the best in one small community first
  • Build systems around that community
  • Expand gradually after repeatability is proven

• Use modern local acquisition

  • Social media + reaching local communities at scale
  • Critique: older marketing methods (billboards, radio) are less effective for local service categories

• Stand out challenge

  • Service businesses are easy to start, but hard to differentiate—so execution and marketing systems matter.

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4) Risk-reduction via validation (lean market testing)

• Validate demand before scaling capex
  • Example: Filterbuy used drop shipping early to prove repeatable customer acquisition
  • Only after validating a repeatable system did they invest in manufacturing

Suggested tactics (for services/products):

• Build a landing page
• Run Google ads
• Measure conversion intent (clicks leading to purchases)
• If needed, outsource delivery initially while validating the sales system

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5) Hyperlocal focus before geographic expansion

Domino’s analogy:

• Perfect the delivery/customer model in one college town
• Learn local preferences first
• Expand only when the model is repeatable

Warning:

• Expanding too quickly spreads resources thin and increases failure risk.

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Concrete examples / case studies

• ATM Together (ATM business)

  • Founder: Paul Alex (retired San Francisco police officer)
  • Started (2018):
    • Bought first ATM for ~$2,100
    • Installed at a nail salon
    • Earned about $500 profit/month initially
  • Scaling:
    • Grew gradually: 1 → 2 → 4 → 30+ ATMs
  • By 2021:
    • $10,000+/month profit
    • Retired from police job
  • Present claim:
    • Company earns $8M+/year
  • What mattered (as described):
    • Location selection
    • Maintenance
    • Cash loading/inventory of cash
    • Negotiating/retaining good placements

• Laundromat “success rate” example

  • Claim: 95% success rate in laundromats vs ~50% for most businesses
  • Counterbalance: maintenance, convenience, and location still drive results.

• Filterby’s operations interruption → equipment rental insight

  • Situation:
    • Opening a Salt Lake City plant; air compressor broke
    • New unit delayed 3 weeks
  • Workaround:
    • Rented a diesel air compressor
    • Cost: $500/day
    • Back up and running within a couple hours
  • Resulting insight:
    • Equipment rental opportunity: companies will pay a premium for ready-to-use inventory

• Trade-school / HVAC service business direction

  • David’s service-based playbook:
    • Partnered with a friend (Goldman Sachs connection)
    • Started Filterby HVAC Solutions (service in HVAC)
  • Key scaling ingredient:
    • Knowledge + systems more than heavy capital

• Emergency tow truck example (Talladega, Alabama)

  • Local operator focused on towing large trucks (18-wheelers) instead of only cars
  • Claimed benefits:
    • Equipment-enabled advantage
    • Potential to “name your price”
    • High-margin niche
  • Scaling approach:
    • Start with one truck and expand the fleet within your service area

• GFL / Green for Life (waste management)

  • Founder: Patrick Dovigi
  • Started (2007) with small Ontario waste management companies
  • Expanded via 100+ acquisitions
  • 2011: won a Toronto trash collection contract, beating larger competitors
  • Today (as stated):
    • 20,000+ employees
    • Multi-billion dollar company
    • Publicly traded; North America coverage
  • Execution takeaway:
    • Study local gaps (e.g., insufficient pickup frequency) to find entry angles

• John window cleaning example (cash-flow margin focus)

  • Started with basic tools
  • Grew to $10M revenue and 40% net margins (≈ $4M/year net)
  • Lessons:
    • Doing processes yourself early helps later system building
    • Systems come from knowing real operational pain points

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Key metrics / KPIs and targets (as stated)

• David / Filterby

  • Filterby makes $22M/month (company scale context)

• ATM example

  • Initial investment: $2,100
  • Initial profit: ~$500/month
  • By 2021 profit: $10,000+/month
  • ATMs owned: 30+
  • ATM Together claim: $8M+/year (stated as earnings)

• Laundromats

  • Success rate claim: 95% vs ~50% for many businesses

• Equipment rental

  • Example rental cost: $500/day
  • Tax efficiency claim:
    • If buy equipment for $100,000 and rent for $60,000/year, then $100,000 can be written off; described as making the $60,000 effectively tax-free

• Window cleaning

  • Revenue: $10M
  • Net margin: 40%
  • Net income: $4M/year

• GFL (waste management)

  • Employees: 20,000+

Note: The subtitles list many headline numbers, but provide limited formal KPI definitions (e.g., CAC/LTV/churn). The emphasis is on margins, operational readiness, and repeatability.

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Actionable recommendations extracted

• Don’t overcommit at launch

  • Start part-time/gradually for property-style businesses (e.g., ATMs expanded slowly while keeping a day job).

• Treat maintenance + infrastructure as core to cash flow

  • In ATMs and laundromats, “functionality” and convenience/cleanliness are non-negotiable.

• When operations break, quantify risk and substitute

  • David used a rental workaround ($500/day) to protect uptime and learned an adjacent business model (equipment rental).

• Validate the business before scaling capex

  • Use drop shipping / landing pages + ads to prove repeatable customer acquisition.

• Go hyperlocal first

  • Establish dominance in one community; perfect the model before wider expansion (Domino’s analogy).

• Prefer service businesses when scaling

  • Lower upfront capital; scalability comes from systems and knowledge.

• Build systems by doing the work

  • David claims he personally performed every process/job early on even as the company grew.

• Avoid resource dilution

  • Narrow the focus to a smaller segment/community early; expanding too fast reduces focus and increases failure risk.

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Presenters / sources

• Presenter/Speaker: David (CEO of Filterby)
• Referenced sources:
  • “Industry publication” (laundromat success rate claim: 95% vs ~50%)
  • Patrick Dovigi (GFL / Green for Life example)
  • Paul Alex (ATM Together example)
  • John (window cleaning business example)
  • Domino’s founders / Domino’s brand history (college-town focus example)