The Proof Hook Library30 volumes

The Proof Hook Library.

Back the claim with receipts and results.

“I [activity] for [duration] — here's what happened”
a Proof hook#1
Examples
  1. I.“I cold-showered for 30 days — here's what happened”
  2. II.“I deleted every app for a week — here's what happened”
  3. III.“I journaled every morning for a year — here's what happened”
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30 proof hook templates

  1. 1.

    I [activity] for [duration] — here's what happened

    • “I cold-showered for 30 days — here's what happened”
    • “I deleted every app for a week — here's what happened”
    • “I journaled every morning for a year — here's what happened”
  2. 2.

    [N] million people are doing [action] — here's why

    • “4 million people are doing cold plunges — here's why”
    • “2 million people switched to creatine this year — here's why”
    • “10 million people quit alcohol this decade — here's why”
  3. 3.

    Before and after [duration] of [habit]

    • “Before and after 90 days of walking 15k steps”
    • “Before and after 6 months of morning sunlight”
    • “Before and after 30 days of no alcohol”
  4. 4.

    This [thing] has [large N] five-star reviews for a reason

    • “This $12 book has 40,000 five-star reviews for a reason”
    • “This running shoe has 11,000 five-star reviews for a reason”
    • “This Roth IRA provider has 25,000 five-star reviews for a reason”
  5. 5.

    Everyone's switching from [old] to [new]

    • “Everyone's switching from Google Docs to Notion”
    • “Everyone's switching from gym memberships to home setups”
    • “Everyone's switching from seed oils to ghee”
  6. 6.

    The results of [action] after [timeframe]

    • “The results of daily meditation after 6 months”
    • “The results of walking 15k steps a day after 90 days”
    • “The results of cutting sugar after 30 days”
  7. 7.

    I stopped [behavior] for [duration] — the data is wild

    • “I stopped coffee for 60 days — the data is wild”
    • “I stopped scrolling in bed for 90 days — the data is wild”
    • “I stopped snoozing for 30 days — the data is wild”
  8. 8.

    [N] top [profession] agree: [claim]

    • “10 top cardiologists agree: red meat isn't the problem”
    • “8 top sleep researchers agree: melatonin is overused”
    • “15 top economists agree: the rate cut won't save housing”
  9. 9.

    [Thing] went from [small N] to [large N] users in [timeframe]

    • “Notion went from 1k to 20 million users in 7 years”
    • “ChatGPT went from 0 to 100 million users in 2 months”
    • “Strava went from 10k to 100 million users in a decade”
  10. 10.

    [N]% of [group] swear by [action]

    • “78% of Olympic athletes swear by cold exposure”
    • “92% of pilots swear by the 10-3-2-1 sleep rule”
    • “84% of nurses swear by compression socks”
  11. 11.

    The trend [N] million people can't stop doing

    • “The trend 3 million people can't stop doing — mouth taping”
    • “The trend 5 million runners can't stop doing — Zone 2 training”
    • “The trend 2 million founders can't stop doing — no-code stacks”
  12. 12.

    Check the numbers on [thing]: [metric]

    • “Check the numbers on Costco memberships: 94% renewal rate”
    • “Check the numbers on Robinhood: 23M monthly users”
    • “Check the numbers on this newsletter: 60% open rate”
  13. 13.

    [N] studies say the same thing about [topic]

    • “27 studies say the same thing about morning light and sleep”
    • “12 studies say the same thing about caffeine timing”
    • “40 studies say the same thing about strength training past 60”
  14. 14.

    When [N] [experts] all agree, you listen

    • “When 10 oncologists all agree on sunscreen, you listen”
    • “When 8 tax attorneys all agree on Roth conversions, you listen”
    • “When 12 chess grandmasters all agree on openings, you listen”
  15. 15.

    This [thing] outsells [benchmark] by [multiplier]

    • “This $40 cookbook outsells the New York Times bestseller by 3x”
    • “This electric kettle outsells every Breville model 4 to 1”
    • “This independent newsletter outsells CNN's flagship by 2x”
  16. 16.

    The [thing] winning in every [group/market]

    • “The pickleball paddle winning in every club”
    • “The weight loss drug winning in every demographic”
    • “The 401(k) provider winning in every industry”
  17. 17.

    A test on [N] people — results inside

    • “A test on 1,200 dieters — results inside”
    • “A test on 400 job seekers using AI resumes — results inside”
    • “A test on 300 runners using carbon-plated shoes — results inside”
  18. 18.

    Everything I tracked while [action] for [duration]

    • “Everything I tracked while running a half marathon program for 16 weeks”
    • “Everything I tracked while eating 200g of protein a day for 90 days”
    • “Everything I tracked while sleeping 8 hours for 60 days”
  19. 19.

    [Celebs] all use [thing] — coincidence?

    • “Hugh Jackman, Chris Hemsworth, Mark Wahlberg all use creatine — coincidence?”
    • “Huberman, Peter Attia, David Sinclair all use rapamycin — coincidence?”
    • “Naval, Seth Godin, Ryan Holiday all use Roam Research — coincidence?”
  20. 20.

    The receipts: [concrete metric] in [timeframe]

    • “The receipts: $140k in 90 days from a cold-email funnel”
    • “The receipts: 30k newsletter subs in 6 months”
    • “The receipts: 11-pound fat loss in 12 weeks”
  21. 21.

    [Thing] has a [N]-year waitlist for a reason

    • “This dentist has a 2-year waitlist for a reason”
    • “This contractor has a 3-year waitlist for a reason”
    • “This therapist has an 18-month waitlist for a reason”
  22. 22.

    [Famous group] quietly all doing [action]

    • “NFL quarterbacks quietly all doing vision therapy”
    • “Oscar-winning actresses quietly all doing facial massage”
    • “Top VCs quietly all doing Pilates”
  23. 23.

    My [metric] after [duration] of [practice]

    • “My resting heart rate after 6 months of Zone 2”
    • “My HRV after 90 days of nose-only breathing”
    • “My bench press after 12 weeks of daily creatine”
  24. 24.

    This [thing] hit [milestone] faster than [comparison]

    • “This startup hit $10M ARR faster than Stripe did”
    • “This creator hit 1M subs faster than MrBeast”
    • “This drug hit FDA approval faster than Ozempic”
  25. 25.

    [N] out of [N] [specialists] pick [option]

    • “9 out of 10 dermatologists pick mineral sunscreen for their own kids”
    • “8 out of 10 sleep doctors pick mouth tape over nasal strips”
    • “7 out of 10 CPAs pick Vanguard over Fidelity”
  26. 26.

    The numbers on [thing] are hard to argue with

    • “The numbers on Costco stock are hard to argue with”
    • “The numbers on walking 8k steps a day are hard to argue with”
    • “The numbers on meal prepping twice a week are hard to argue with”
  27. 27.

    My [metric] comparison before and after [change]

    • “My bodyfat comparison before and after switching to strength training”
    • “My revenue comparison before and after firing my worst client”
    • “My sleep score comparison before and after blackout curtains”
  28. 28.

    [Group] quietly all adopted [thing]

    • “Fortune 500 CMOs quietly all adopted AI copy tools”
    • “NBA teams quietly all adopted a standing-desk policy”
    • “Major hospitals quietly all adopted continuous glucose monitors”
  29. 29.

    [Thing] dethroned [incumbent] — here's the data

    • “Notion dethroned Evernote — here's the data”
    • “Rhode dethroned Glossier — here's the data”
    • “Figma dethroned Sketch — here's the data”
  30. 30.

    Receipts for [claim]: [specific data]

    • “Receipts for my $10k month: here's the Stripe dashboard”
    • “Receipts for my 40-pound loss: here's the InBody scan history”
    • “Receipts for my book advance: here's the contract page”

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