Ryan Koenen

A few brands under management.

[Ryan Koenen @RyanKoenen01]

@zachmstuck @itschadross By selling scissors to cut your socks

[Ryan Koenen @RyanKoenen01]

@rokhladnik @Shopify Biggest drop-off is S1 -> S2

[Ryan Koenen @RyanKoenen01]

@Fried_rice April fools

[Ryan Koenen @RyanKoenen01]

@jforjacob Believe

[Ryan Koenen @RyanKoenen01]

I'm seeing more and more people launch AI-generated landing pages at scale

Nobody is thinking about what that actually does to the market

There's a law in economics called the Law of Diminishing Returns

Every additional unit of input added to a system produces less output than the one before it

Each extra lander you launch gets less budget less signal and less data than the previous one

Meta can't find a winner because the signal is too fragmented users recognize the pattern and CPMs go up for everyone

More landers isn't a growth strategy

But there's a flip side to this law

When every visit feeds a system that learns the returns don't diminish

They compound

[Ryan Koenen @RyanKoenen01]

@DTC_Quizbuilder What were the results? 🙂

[Ryan Koenen @RyanKoenen01]

2026 is the year 'funnel architecture' becomes a job title

[Ryan Koenen @RyanKoenen01]

@Alexanderrrjt The main reason why I joined X. Shit needs to change, too many knuckleheads 🤣

[Ryan Koenen @RyanKoenen01]

Most quiz funnels start with "What's your age?"

Not always wrong. But not always right either.

Two approaches:

Demographics first: "What's your age?" "What's your gender?"

Pain point first: "What's your biggest frustration?" "How often does this hurt?"

Demographics first works through:

Foot-in-the-door principle. Easy answer → momentum → harder questions feel easier.

Low friction entry. No thinking required.

Pain point first works through:

Immediate relevance. "This is about MY problem."

Activates problem-solving mode. Stronger engagement.

The truth:

There's no "cold traffic = demographics" rule.

It depends on what your ad promised, how aware they
are, product complexity.

Don't copy what I say works. Test both.

Track what matters:

→ Profit per visitor (PPV)
→ Quiz start → purchase %
→ CAC vs LTV

Example: Tested for a partner.

Demographics-first: 65% completion, 8% purchase

Pain-first: 48% completion, 14% purchase

Pain-first won on revenue despite lower completion.

Your data beats anyone's theory. Always.

[Ryan Koenen @RyanKoenen01]

@DTCMidas Friction is relative, cold traffic needs it to build conviction. Hot traffic already has intent.

"Reduce friction" as a blanket rule is lazy. It depends on whether it serves the conversion or fights it.

[Ryan Koenen @RyanKoenen01]

The complete workflow:

0. Is it worth testing? (Big levers only - 20%+ PPV impact potential)
1. Clear hypothesis (what + why mechanism)
2. Define PPV as primary metric
3. Calculate sample size (95% confidence)
4. 50/50 split, don't peek early
5. Check bounce + scroll first (relevance signals)
6. Calculate PPV + segment by source
7. Gradual rollout (50→80→100%)
8. Monitor post-implementation (2-4 weeks)

Don't blindly copy what works for others.

Test with YOUR traffic, YOUR product, YOUR audience.

Your data beats anyone's best practices.

[Ryan Koenen @RyanKoenen01]

Steps 7-8: Implementation + Monitoring

Winner declared? Don't just flip the switch and forget it.
Implementation:

Roll out to 100% of traffic gradually:

Week 1: 50/50 (confirm results hold)
Week 2: 80/20 (final validation)
Week 3: 100% (full rollout)

Sudden changes can reveal hidden issues.

Post-implementation monitoring:

Track the same metrics for 2-4 weeks:

→ PPV still improved?
→ Bounce rate stable?
→ AOV holding?

Sometimes winners in testing regress in production.

Traffic mix changes. Seasonal factors. External events.

Document everything:

Test date, hypothesis, results, decision, why.

Post-implementation performance vs test results.

Simple spreadsheet works. No fancy tools needed.

Build institutional knowledge. Future you needs to know what you tested and why.

[Ryan Koenen @RyanKoenen01]

Step 6: Calculate PPV, not just conversion

Higher conversion ≠ more profit.

Check full funnel:

→ PPV (profit per visitor) - Your north star
→ Bounce rate (relevance check)
→ AOV (customer quality)
→ Purchase rate

Segment by traffic source. Facebook ≠ Google ≠ Email.

Sometimes higher conversion with lower AOV = worse PPV.

Optimize for profit, not vanity metrics.

[Ryan Koenen @RyanKoenen01]

Step 5: Check relevance BEFORE conversion
Bounce rate = relevance signal

60%+ bounce? Wrong message or wrong traffic. Fix that first.

20-40% bounce? Good relevance. Now optimize conversion.

Scroll depth = engagement signal

If people don't scroll past 25%, your content isn't engaging.

Can't convert people who bounced or never scrolled.

[Ryan Koenen @RyanKoenen01]

Steps 3-4: Sample Size + Traffic Split

Calculate sample size using significance calculator ( aim for 95% confidence).

Typically need 100-200 conversions per variant, but depends on your baseline.

Run 50/50 traffic split. Not 90/10.

50/50 reaches significance 9x faster.

Don't peek at results daily. Early data is noise.

[Ryan Koenen @RyanKoenen01]

Step 2: Define your primary metric upfront
Profit Per Visitor (PPV)

Formula: (Revenue - COGS - Ad Spend) / Visitors

This is what pays bills. Not conversion rate. Not engagement.

Secondary metrics: CAC, AOV, purchase rate.

Know what "winning" looks like before you start.

[Ryan Koenen @RyanKoenen01]

Step 1: State ONE clear hypothesis

Bad: "Let's test if the quiz works better"

Good: "Pain-point-first questions will increase quiz → purchase conversion by getting people into problem-solving mode faster"

You need to know WHAT you're testing and WHY you think it'll work.

Guessing without reasoning = random experiments.

[Ryan Koenen @RyanKoenen01]

Step 0: Before you test - Is it worth testing?

Only test things that could realistically move PPV 20%+.

Don't test:

→ Button colors (2-5% impact max)
→ Micro-copy tweaks
→ Font changes

Do test:

→ Offer structure (bundle vs single)
→ Message match (pain point vs feature)
→ Pricing strategy
→ Funnel sequence
→ Page formats

Test big levers, not small dials.

[Ryan Koenen @RyanKoenen01]

Everyone says "test everything."

Nobody explains HOW to test without wasting money on inconclusive results.

Here's the workflow I use to test funnel hypotheses and get reliable data:

[Ryan Koenen @RyanKoenen01]

Dopamine isn't the reward chemical. It's the anticipation chemical.

Your brain releases dopamine when it predicts a reward is coming. Not when you get it.

I see this with my 18-month-old every night. She gets dessert after dinner. Her brain learned the pattern.

Dopamine spikes before dessert even arrives.

Skip dessert one night? Dopamine crash. Her amygdala fires up. Complete meltdown. No reasoning possible. ( I would be upset as well 🙂 )

That's why scrolling social media is addictive but never satisfying. Each scroll promises something good is coming.

Dopamine fires. But the reward never matches the prediction. So you keep scrolling.

Landing pages work the same way.

Your headline creates a dopamine spike if it promises a solution to their active problem.

But if the page doesn't deliver on that promise fast enough, dopamine crashes. Their amygdala flags it.

They bounce.

The fix isn't better copy. It's faster reward delivery.

State the benefit. Prove it immediately. Don't make them hunt for why they should care.

Your headline is the dopamine promise. Everything below needs to be the dopamine payoff.

Gap too big? They're gone.