Two-part data analysis to better gauge efficacy of boosts and reduce bias
Evidently in trying to collect data on the optimal way to implement the Boost feature, there's a group of streamers that are getting the boosts and others that are not. This makes sense but to reduce bias, it may be needed to have a second part data collection where the group that did not get any boosts get the boosts instead, and compare the results from the two parts. This can help identify any biases, if any, and will be more fair (and thus reduce dissatisfaction of smaller streamers that we're seeing).
Can we please have a response of some sort regarding this Idea? Whether it be that something of the sort is in the works, or an explanation on why this is not going to happen? Of all the other suggestions I believe this is the only one that takes into consideration the benefit of Twitch and I'm Baffled why this is not of interest to twitch.
Boosts are a great way to:
a)Interact with your community
b)Have a way to measure community interaction
c)Have incentives to spend channel points
And for that it should be something more accessible to smaller streamers, I APPROVE
I'm not sure if the analysis is being done concurrently with other factors, but if its just looking at the effect of one thing like the boost, It seems to be standard practice to switch and compare the Control and Experimental Group.