How many visitors do you need for your A/B test?
- 1. How many visitors do you need
for your A/B test?
testing simplified!
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- 2. Disclaimer
• We can never say that we need X number of
visitors for an A/B test
– Theoretically, an A/B test can take infinite number
of visitors before producing statistically significant
result
• Instead, what we can say is that we need to at
least test X number of visitors
– With Y probability (usually 80%) of detecting a
statistical difference in results (if there is any)
© Wingify Software Pvt. Ltd.
- 4. First, let’s define statistical significance
• Conversion rate is never an exact number, it is
always a range. That is, we can never say
conversion rate is 10%, although we always say it is
10% ± 1%
– This is because as we collect data, we are estimating
what real conversion rate is (in statistical terms, we are
estimating population mean from sample mean)
– Initially, our guesses are raw (as we only have few data
points) but as we test more visitors, the error range
decreases and we have better estimates of conversion
rate
© Wingify Software Pvt. Ltd.
- 5. But, still, conversion rates are always
estimates…
• So, we now have two conversion rate estimates for control
and variation, say following:
• Observe how these ranges are overlapping, and so even if
conversion of variation appears to be worse, we cannot say for sure
(until these ranges are non overlapping, as following)
© Wingify Software Pvt. Ltd.
- 6. So, how many visitors to A/B test?
• There are two scenarios in A/B test:
– Variation is performing better (or worse) as
compared to control
• Difference in conversion rate is statistically significant
– Variation is performing similarly as compared to
control
• Difference in conversion rate is not statistically
significant
© Wingify Software Pvt. Ltd.
- 7. So, how many visitors to A/B test?
• Aim of A/B test calculations is to make sure we test
enough visitors in order to know with certain
confidence whether there is any statistical difference in
control and variation conversion rate
• As stressed earlier, we can never be 100% sure that
after testing X number of visitors we will know if test
has a statistically better or worse performing variation
– If we test even more visitors, there are even better
chances of finding a statistical difference if it really is there
© Wingify Software Pvt. Ltd.
- 8. Factors important in calculations
• Suppose we want to calculate X, which is the number
of visitors we need to test in order to find out whether
statistical significance is there
• There are various factors which help us calculate X:
– Statistical Power (usually 80%): it is the probability with
which you expect to find out statistical significance after
testing X visitors. (There are 80% chances that after testing
X visitors, we will find statistical significant results if they
are there)
• As statistical power increases, your chances of finding a statistical
difference gets better (but of course you need to test more
visitors)
© Wingify Software Pvt. Ltd.
- 9. Factors important in calculations
– Statistical confidence (normally 95%): once statistical difference is found, it is
the confidence we have in that difference. (There is 5% chance that the
difference in conversion rate is not real and is due to randomness)
• If you need higher statistical confidence, we need to test more visitors
– Existing conversion rate of website: for lower conversion rates websites (say
ones with 1% conversion), we need to test many more visitors as compared to
situation if average conversion rate is higher (say 10%)
– Difference in conversion rate you want to detect: if you want to detect even a
small difference in conversion rate (say you want to know if variation differs from
control by even 0.1%), you need to test many more visitors. If you are only
concerned with detecting a large differences (say only >10%), you need to test
lesser number of visitors
– Number of variations you are testing: obviously, if you are testing 4 variations
you need twice the number of visitors as compared to situation when you are
just testing 2 variations.
© Wingify Software Pvt. Ltd.
- 10. You need a thumb rule?
Sorry, there is no thumb rule to find
out how many visitors you need to
test :(
© Wingify Software Pvt. Ltd.
- 11. Not all is lost, though…
• You don’t have to be a statistician in order to do
these calculations, you can use an online calculator
to find out number of visitors to test:
http://visualwebsiteoptimizer.com/ab-split-test-duration/
© Wingify Software Pvt. Ltd.
- 12. Questions?
Paras Chopra, CEO, Wingify
paras@wingify.com
© Wingify Software Pvt. Ltd.