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Here's the basic idea:
I'm running several PPC ad campaigns and trying to determine the optimum bid price.
My question is this: what sample size must I take to make sure that the numbers are statistically significant?
Here's an example:
52 clicks ( gives a .8% CTR roughly)
2 conversions (3.85%)
Now,I'm not really concerned about the CTR, but the actual conversion ratio.
Most of are successful campaigns are seeing around 9-10% conversion. I want to be able to test for 1-2 weeks, and know with 95% certainty that the conversion rate I see will be within say, 1% (maybe .5%) of the results. How many samples (clicks) must I record to find this?
If you run what is known as a monte carlo analysis
(statistical simulation) 200 samples is usually enough.
However, in the case of marketing there can be delays
from click to conversion. I have found that after 1000 clicks statistics start to converge to a realistic number. In some cases I have noticed a good conversion rate for new ads and then after running the ad for a while it slows down.
To get within 1%, you need root(n)/n = 1/100.
So n = 10,000 conversions.
You simply don't have the numbers to get that sort of statistical confidence within the time frame.