Here is the number nobody selling you a testing tool leads with: to detect a 20 percent lift on a landing page that converts at 3 percent, you need about 14,000 visitors per variant, roughly 28,000 visitors total, at the standard 80 percent power and 95 percent confidence. If your page gets 5,000 visitors a month, that single test takes over five months. If it gets 1,000 a month, it takes more than two years. For most small sites, the honest answer to "how do I A/B test with low traffic" is: you mostly don't, and pretending otherwise produces random results with a scientific costume on.
That is not a reason to give up on conversion work. It is a reason to change methods. Big swings instead of button-color tweaks, because large effects need far smaller samples. Before-and-after comparisons with guardrails. Watching five real people use your page, which finds problems no test ever will. Cutting form fields and fixing speed, where the evidence is already strong enough that you do not need your own experiment.
This guide does the sample-size math in public so you can run it on your own numbers, then walks through each alternative in order of effort. It also covers the practical stuff that changed recently: what actually replaced Google Optimize for free testing after it shut down in 2023, and why INP replacing FID matters for your page speed work. Written for a founder with one landing page, real traffic numbers, and no data scientist down the hall.