Ashwin Aravind

I spent years at Meta testing everything—features, algorithms, UX changes. Every change went through rigorous A/B testing before reaching users.

Creators don't have that luxury. You post a video, see how it performs, learn... slowly.

But what if you could test your hook before publishing? Not with millions of impressions, but with 20-30 data points that tell you what's likely to work?

Here's the framework I built for creators to test hooks systematically, based on patterns from Meta's testing culture.

The Problem: One Shot Per Video

When you publish a video on TikTok or Instagram, you get one shot. The algorithm tests it on a small audience in the first hour. If the hook doesn't land, the video dies.

You can't A/B test hooks like Meta does with features. You can't show version A to 50% and version B to 50%.

But you can test before publishing.

The Framework: Pre-Publish Hook Testing

This is a lightweight testing methodology that borrows from Meta's experimentation culture but works for individual creators.

Phase 1: Generate Hook Variations

Don't start with one hook. Start with 5-10 variations.

Hook Types to Test:

Question Hook - "Ever wondered why...?"
Problem Statement - "This wasted 10 hours of my time..."
Contrarian Take - "Everyone says X, but actually..."
Direct Benefit - "This will save you hours..."
Curiosity Gap - "The secret that changed everything..."
Pattern Interrupt - shows unexpected action
Story Hook - "Last week something wild happened..."

Example for a coding tutorial video:

V1: "This Python script saved me 10 hours last week" (Direct benefit)
V2: "Why is no one talking about this automation?" (Question + contrarian)
V3: "I used to spend entire days on this task" (Problem statement)
V4: "The one command that changed my workflow" (Curiosity gap)
V5: "Everyone automates X, but Y is 10x more valuable" (Contrarian take)

Generate these in 10 minutes. Use AI if needed (see my post on AI for creators), but customize to your voice.

Phase 2: Create Test Materials

You need to simulate the scrolling experience. Create mockups of how each hook would appear.

Option A: Screenshot Test (Quick)

Take your video's first frame and add text overlays with each hook variation.

Tools: Canva, Figma, or even iOS Photos markup.

Takes 5 minutes per variation.

Option B: Actual Short Clips (Better)

Record 3-second versions of each hook.

Same content, same video, different opening line/visual.

Takes 30 minutes but gives more realistic signal.

Phase 3: Test with Target Audience

This is where the framework differs from "ask your friends."

Who to test with:

Not your family or friends (unless they're your target audience)
Not random people
Yes people who match your target demo

Find 15-20 people who:

Are in your niche
Don't know you personally (removes bias)
Consume content like yours

Where to find them:

Post in niche Discord/Slack communities: "Testing video hooks for [topic], need 30 seconds of feedback, will reciprocate"
Use Close Friends story on Instagram (if your Close Friends are your target demo)
Twitter polls (show variations, ask which would make them stop scrolling)
Tools like PickFu or UsabilityHub (paid but fast)

Phase 4: Structured Testing Method

Don't just ask "which do you like?"

Use this specific protocol:

The Test:

Show them all variations in random order.

Ask three questions:

1. "Which version would make you stop scrolling?"
   (This measures hook effectiveness)

2. "Which version makes you most curious about what comes next?"
   (This measures engagement potential)

3. "Which version sounds most like something you'd actually watch?"
   (This measures audience fit)

The Scoring:

Track responses in a simple spreadsheet:

| Hook Version | Stop Scrolling | Curious | Would Watch | Total Score | |--------------|----------------|---------|-------------|-------------| | V1 | 8 | 6 | 9 | 23 | | V2 | 12 | 14 | 11 | 37 | | V3 | 4 | 5 | 3 | 12 | | V4 | 15 | 13 | 12 | 40 | | V5 | 11 | 12 | 15 | 38 |

V4 wins. That's your hook.

Sample Size:

15-20 testers minimum
More is better, but diminishing returns after 30
If results are split 50/50, test more or test both versions as separate videos

Phase 5: Secondary Signal - Recall Test

This is a Meta-inspired technique that predicts virality.

The Test:

After someone views all your hook variations, wait 10 minutes.

Then ask: "Without looking back, which hook do you remember?"

Why This Matters:

At Meta, we learned that memorability correlates with shareability. If someone can remember your hook 10 minutes later, they're more likely to:

Watch the full video
Remember to share it
Think about it later and come back

How to Run It:

After your testers complete the main test, say:

"I'll follow up in 10 minutes with one more question"

Set a timer. After 10 minutes, message them:

"Without scrolling back, which video hook from my test do you remember most clearly? (Just describe it briefly)"

Track recall rate:

| Hook Version | Recall Rate | Stop Scrolling Score | Final Weighted Score | |--------------|-------------|---------------------|----------------------| | V1 | 3/20 (15%) | 23 | 26.45 | | V2 | 9/20 (45%) | 37 | 53.65 | | V4 | 12/20 (60%) | 40 | 64.00 |

V4 wins decisively when you factor in recall.

Pattern Recognition: Building Your Hook Library

After testing 10-20 videos this way, you'll start seeing patterns.

Track in a spreadsheet:

| Video Topic | Hook Type | Test Score | Actual 3s Retention | Actual Total Views | |-------------|-----------|------------|--------------------|--------------------| | Python automation | Direct benefit | 40 | 52% | 15K | | Code review tips | Question | 28 | 31% | 4K | | Tool comparison | Contrarian | 45 | 61% | 28K |

After 10-20 rows, patterns emerge:

Your audience loves "Direct benefit" hooks
"Question" hooks underperform for you (even if they work for others)
"Contrarian" hooks test AND perform well

Now you can make educated guesses about which hooks will work without testing every time.

The Validation Loop

Here's how to know if your testing framework is working:

Week 1-2: Test → Publish → Measure

Test 3-5 hooks per video
Publish the winner
Track actual 3-second retention

Week 3-4: Compare Test vs. Reality

Calculate correlation:

Hook test score vs. actual 3s retention

If correlation is positive → your testing works
If no correlation → adjust who you're testing with

Example from a creator I work with:

| Video | Test Score (out of 60) | Actual 3s Retention | |-------|------------------------|---------------------| | 1 | 45 | 58% | | 2 | 28 | 34% | | 3 | 52 | 67% | | 4 | 31 | 38% | | 5 | 48 | 61% |

Strong correlation. The testing predicts real performance.

After 10 videos with this pattern, she stopped testing as rigorously and just used her hook library patterns.

Advanced: Cohort-Based Testing

Once you have the basics down, segment your testing:

Test with different audience cohorts:

Beginner vs. Advanced
Platform (TikTok users vs. Instagram users)
Age ranges
Geographic regions

Example:

A tech creator tested coding tutorial hooks:

| Hook | Beginners Score | Advanced Score | |------|----------------|----------------| | "This saved me hours" | 42 | 28 | | "Why X algorithm beats Y" | 18 | 51 |

Conclusion: Use different hooks for different audience segments.

She now creates two versions of technical videos:

Beginner-focused with "direct benefit" hooks
Advanced-focused with "technical deep dive" hooks

Both perform well because hooks match audience sophistication.

The Tool I Built

I built a simple tool that automates this:

Upload hook variations (text or video)
Share link with testers
They rate hooks (stop scrolling, curious, would watch)
Automatic recall test (10 minutes later)
Get scored results with winner highlighted

It costs ~$5/month to run (Supabase + Vercel).

You can build the same thing in a weekend, or just use the spreadsheet method above.

Common Mistakes

Mistake 1: Testing with the Wrong People

Your mom will say everything is great. Your friend who doesn't watch YouTube will guess randomly.

Test only with your actual target audience.

Mistake 2: Only Testing One Thing

Don't test "Hook A vs. Hook B." Test 5-10 variations to see patterns, not just pick a winner.

Mistake 3: Ignoring the Recall Test

The hook that scores highest on "stop scrolling" might not be the most memorable. Test both.

Mistake 4: Not Tracking Real Performance

The testing is only useful if you validate it against actual video performance.

Track Test Score vs. 3s Retention for 10 videos. If there's no correlation, adjust your testing methodology.

What This Looks Like in Practice

A creator I work with uses this framework weekly:

Monday:

Generate 5-6 hook variations for next 3 videos
Create test materials (screenshots with text overlays)

Tuesday:

Post test in niche Discord: "Testing hooks for coding tutorials, 2 min of your time?"
Get 20 responses in a few hours
Run recall test in evening

Wednesday:

Analyze results
Pick winners
Record videos with winning hooks

Thursday-Saturday:

Publish videos

Sunday:

Compare test scores to actual performance
Update hook library

Time investment: ~2 hours/week Result: 3x improvement in 3-second retention over 8 weeks

The Framework Checklist

Before you publish your next video:

[ ] Generate 5-10 hook variations
[ ] Create test materials (screenshots or short clips)
[ ] Find 15-20 testers from target audience
[ ] Run structured test (stop scrolling, curious, would watch)
[ ] Run recall test after 10 minutes
[ ] Calculate scores, pick winner
[ ] Record video with winning hook
[ ] Track actual performance vs. test score
[ ] Update hook library

When to Skip Testing

You don't always need to test:

Skip testing when:

You have <10 videos published (learn platform basics first)
You're testing a new content format (no baseline yet)
Your hook library has clear patterns and you're confident

Always test when:

Trying a new content type
Audience growth has plateaued
Recent videos underperformed

The Meta Lesson

At Meta, we didn't ship features without testing. But we also didn't over-test.

The key was:

Test what matters (hooks, core UX)
Use small samples to get signal fast
Validate tests against real metrics
Build intuition over time

Creators can do the same.

Start with this framework. After 20-30 videos, you'll develop intuition for what works. Then you can test less and ship more.

But until you have that intuition, test systematically.

The algorithm doesn't give second chances. Test before you publish, not after.

A Framework for Testing Hooks: Before You Publish the Video