Good material to work with: confusion about the annual toggle and an unclear enterprise tier are both clear things to test on the pricing page. To write testable hypotheses with real sample sizes, I need two required numbers:
- One baseline conversion rate. "Around 2-4% depending on the month" is a range, and the sample size changes a lot across it. At a 2% baseline a test needs roughly twice as many visitors as at 4%. Give me one figure, such as last month's or a recent 3 month average, and say what counts as a conversion on this page (a signup, a demo request, or a click to checkout).
- Weekly visitors to the pricing page. Without this I can't say how many weeks a test would take, and I won't assume traffic.
It also helps to know how many emails mentioned the enterprise tier, and to have one or two quoted lines. Each hypothesis cites its evidence, and "a few emails" is weaker evidence than a count with quotes.
Defaults I'll use unless you tell me otherwise: - Smallest lift worth detecting: 10% relative. - Significance and power: two sided 0.05, power 0.80. - Variants: 2 (control plus one variant).
Send the baseline, the weekly visitors and, if you have them, the email quotes. You'll get the hypotheses, sample size and weeks for each, the priority order and a spec for the top test.