The fraction of A/B tests I've seen personally that mentioned ANOVA at all is very small. Or thought that critically about experiment design. Understanding of p values is also generally poor; prob/stat education in engineering and business degrees seems to be the least-covered-or-respected type of math.
Even at places that want to ruthlessly prioritize velocity over rigor I think it would be better to at least switch things up and worry more about effect size than p-value. Don't bother waiting to see if marginal effects are "significant" statistically if they aren't significant from the POV of "we need to do things that can 10x our revenue since we're a young startup."
Even at places that want to ruthlessly prioritize velocity over rigor I think it would be better to at least switch things up and worry more about effect size than p-value. Don't bother waiting to see if marginal effects are "significant" statistically if they aren't significant from the POV of "we need to do things that can 10x our revenue since we're a young startup."