Let's say I have a daily conversion rate of 33.1% with a sample size of 4,500 daily visitors. If I want to run an A/B test and detect a 3% difference in conversion, I would need around 3,881 visitors in each group for a total of 7,762.
Since the desired sample size is greater than the number of daily visitors, I cannot run the test. What ways can I remedy this outside of settling for increasing my minimum detectable difference?
I thought about evaluating weekly conversion rates since I have more unique visitors in a week compared to a day. However, I have some visitors who will convert twice in a week, thus, I believe this invalidates the experiment, right?
I also thought about just running the a/b test for some time and then I can compare the average daily conversion rate of the two groups using a t-test, however, that does not seem to be appropriate either, does it?
Any help/elucidation would be awesome. I've been scanning Cross Validated and other sources for a solution to no avail.