> In my experience working in software, empiricism is the only thing valued anymore. Intuition and thoughtfulness is out the window because it's not scientific enough.
With things like A/B testing, its not entirely an objective as you need to make assumptions which can be difficult to measure (although typically randomisation solves a lot of them), but you can only measure what you've decide to measure (which isn't random), so you don't know when you're in a local max. So IMO intuition and thoughtfulness is necessary. Sometimes product managers don't listen to data scientists when they say you can't measure Y with X, or the research design violates the required assumptions to make a causal claims (like reverse causality or controlling on a post treatment effect, e.g. employment as control when measuring income after hospitalisation (the treatment)). I think the worse offences I've seen have been from marketing teams.
But proper research design does require intuition and thoughtfulness, because statistical models require thought, like other forms of supervised learning.
I've seen both
- PMs use questionable experiments to justify shipping something.
- PMs dismiss experiments when it was a null result and shipped anyways.
In either case I don't think the methodology is the cause of problems here, although I think shipping with a null result is justifiable if it's a larger unit of work (provided its not a regression).
Sometimes things that have heterogenous effects get measured as a homogenous effect, Like say:
- Your primary user base is X1 and X2 is a larger consumer base but makes up a small portion of your user base.
- Your experiment does poorly with X1, but say there was an increase in user base X2.
- However because X1 dominates the user base and your signups (because say you target ads to X1 over X2), no one drills into the effects on these different user bases, the result gets discarded as it seems to be a bad outcome.
There's valuable information in the experiment outcome but without thought and attention you can miss it.
> Google recently started doing all of these on anonymous searches with a modal overlay and a big bright blue "Continue" primary button that takes you to a login screen, while a "don't sign in" button appears as far less noticeable text above it.
I mean that sucks, but IMO with their market share, the way Google chrome is inclined to develop their product is very different to firms in more competitive spaces.
Perhaps A/B Tests, allows google to optimise the things they are incentivised to pursue, but in the hands of smaller firms with different incentives are willing to tweak things to be more appealing to users when they have far less market power, which I think is probably more the issue in the case of Google.
I just don't think this is a universal problem with the methodology