A/B testing is, in my experience, usually an attempt to improve some business metric like landing page conversions and engagement etc. They're great if done right, but they inherently add a lot of complexity and coordination that can cause holes that are hard to dig out of.
Big orgs do a lot of A/B testing, but they devote the resources to making it work, and I'm sure they still have their issues. Smaller engineering orgs get in trouble trying to add split testing into an already rigorous workload.
There is also a stats issue involved. And how many misunderstand stats.
Seen way too many startup spending way too much time trying to use A/B, as a means to try find a magical 10x conversion rate improvement through it. With sample size of under a thousand.
Over simplifying, my rule of thumb, until one reach over a million hits per month, or a team of 50, one should never consider A/B. Till then incremental improvement and feedback is good enough.
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A/B testing is, in my experience, usually an attempt to improve some business metric like landing page conversions and engagement etc. They're great if done right, but they inherently add a lot of complexity and coordination that can cause holes that are hard to dig out of.
Big orgs do a lot of A/B testing, but they devote the resources to making it work, and I'm sure they still have their issues. Smaller engineering orgs get in trouble trying to add split testing into an already rigorous workload.
There is also a stats issue involved. And how many misunderstand stats.
Seen way too many startup spending way too much time trying to use A/B, as a means to try find a magical 10x conversion rate improvement through it. With sample size of under a thousand.
Over simplifying, my rule of thumb, until one reach over a million hits per month, or a team of 50, one should never consider A/B. Till then incremental improvement and feedback is good enough.