Sorry, in my Comment (now deleted), I think I misinterpreted your 'data structure' example.
With such a brief discussion and not much mention of what issues are important, it is difficult to know how to help. I will make up some data, and show results from Minitab (which tends to have user-friendly output for beginners).
Maybe this will provide your answer or a framework for a revised question and a more helpful answer. We understand if you can't reveal certain
proprietary information, but you have to address the main issues before we can be of much help.
For Day 1: In Cohort A, suppose 257 were opened and 77 were clicked. In Cohort B, 271 opened an 95 clicked. Then we can find the CTRs for A and B, and compare them to see if they are significantly different. This is a test 'comparing two binomial proportions'. (For more discussion about such tests, perhaps see this Q&A or this---oe one of the links under 'Related' in the right-hand margin of this page.)
Minitab's version gives the following output:
Test and CI for Two Proportions
Sample X N Sample p
1 77 256 0.300781
2 95 271 0.350554
Difference = p (1) - p (2)
Estimate for difference: -0.0497723
95% CI for difference: (-0.129666, 0.0301218)
Test for difference = 0 (vs ≠ 0):
Z = -1.22 P-Value = 0.223
Although cohort A has a CTR of .30 and B a CTR of .35, the numbers opened are not large enough for these two rates to be deemed
significantly different at the 5% level: the P-value $0.223 > 0.05.$
You might also wonder whether the rate of opening differed according to Cohort. Then you could use counts 1000 Deliveries and number Opened to run a similar test.
If you seem to get substantially different results (for Clicking opened sites, or for Opening delivered sites) on different days,
then you might want to look at a 3-way contingency table
with three categorical variables: Day (1-5), Cohort (A, B), and
Result (Open, Not). Then you could test whether results really do differ from day to day. If the five days give very similar
results, I would consider combining counts for all five days.