Your A/B Test Was Clean. Your Result Was Garbage.

🧪 In Theory, This Works

Why real-world CRO rarely follows the textbook… and shouldn’t

A commenter on my last piece about 2-week test durations said this:

| “This is just CRO dogma. Microsoft can call tests in hours. If you randomize traffic properly and size your test correctly, you don't need two weeks.”

And they’re not wrong.
In theory.

But here's the thing:

Real-world testing is not a math problem.
It’s an operations problem in a messy, unpredictable environment.

You’re not optimizing inside a spreadsheet.
You’re optimizing inside a live business with:

• Budget constraints

• Campaigns turning on and off

• Platform bugs

• Holidays & sales

• And users who definitely didn’t read your experiment plan

📉 “The numbers say it worked” — and then it didn’t

Let’s say your test “hits significance” in 6 days. You’re tempted to roll it out.

But the following week:

• Meta re-optimizes ad delivery

• Direct traffic dips due to a blog post aging out of Google

• That one influencer with wild CVR drops off

Now your “winning” variant underperforms.
What changed? Just… life.

This isn’t rare.
It’s normal. And if you’re not accounting for it, your “CRO” is just confirmation bias with prettier graphs.

🧠 Why traditional CRO brains struggle here

A lot of CRO professionals, especially from big tech, come from design, dev, or analytics roles.

They’ve been trained to believe:

• Process = protection

• Control = confidence

• Clean data = clean conclusions

Which works great when:

• You have massive traffic

• Your stack is internally owned

• You’re not tied to revenue, just experiment volume

But outside of Google or Uber, most businesses don’t live in that sandbox.
They need performance - and fast.
They can’t afford false wins or wasted quarters.

⚡ Why growth teams think differently

When your background is growth, marketing, or acquisition, you approach testing with different instincts:

• You’ve owned revenue targets

• You understand traffic volatility

• You know when a result feels too good to be true

• You balance speed vs. signal like a portfolio manager

It’s not that you don’t care about data.
You just recognize the cost of being technically right but practically wrong.

🏆 Performance is the north star

Theory is useful. But it’s only half the equation.

Good testing is about tension.

• Between rigor and practicality

• Between significance and sense-checks

• Between optimization and outcome

The best CRO folks?
They’ve built funnels. Launched offers. Managed paid budgets.
They don’t just ask “Is it valid?”
They ask, “Will this still win next month?”
And: “What happens if I’m wrong?”

That’s the mindset that drives results.

💡 TL;DR

Real-world CRO means designing for noise, not ignoring it.
And success comes from teams who know how to operate in the wild… not just in the lab.

I hope this helps you think about how you can and should run your testing program. And if you want to work with a team whose entire foundation incorporates these principles, give me a shout (reply to this email) or book some time with me.

Or, if you just enjoyed this and believe other people need to start approaching CRO this way - the right way - it’d mean so much to me if you forwarded it along.

Talk to you soon,

Kanika