Why Your “Sample Size” Could Be Lying to You
Most people start a clothing brand without understanding product creation, sourcing, marketing, pricing, and brand building. This 100-day course is built to help you understand the path before you start working on it.
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Let’s shift gears and talk about something most brand owners ignore -- the law of large numbers.
Sounds fancy, right? But let me break it down with a cricket analogy.
Virat Kohli vs. a newbie opener
Virat Kohli’s ODI average right now is roughly 57.88.
If he scores 0 runs in every ODI match from now until the end of 2026 (approx. 16 matches), his average will still be above 52! (Maybe that’s why he is called the “King Kohli” and “Chase Master”.)
Why? Because his career already has 302 ODI innings in the calculation. One bad series or even a year barely moves the needle.
Now, imagine I’m a newbie opener for India. (Let’s assume it's me!)
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First match: I scored 100. Wow! My average is 100.
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Second match: I scored 0. My average drops to 50.
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Third match: I scored 0 again. My average is now 25.
I know the averages are not calculated just like this, straight division – but for simplicity, let’s keep it this way. In just 3 matches, my “performance” has gone from looking like a legend to looking like I should be dropped from the team.
What does this mean for your brand?
When making decisions, be it pricing changes, product tweaks, or marketing strategy, you can’t base them on tiny numbers.
If you only ask 10 customers for feedback and 3 give negative reviews, it feels like “Oh no, 30% of my customers are unhappy!”
But that’s not statistically meaningful, is it?
You need to collect enough data, 100, 200, sometimes even 500+ data points, before drawing serious conclusions, especially for high-impact decisions.
Where brands mess this up
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A few bad reviews lead them to think the product is “failing.”
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One weak ad campaign convinces them “Meta Ads don’t work.”
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A handful of COD RTOs makes them turn off COD entirely.
The reality? Small samples can swing wildly. Large samples smooth out those spikes and reveal the true trend.
So next time you’re testing a new product page, running a new ad, or gathering feedback, remember: Small numbers = noisy data. Large numbers = reliable insights.
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