Data

bytexplorers

reminder to @msilb7 @binji.eth @agaperste- @macbudkowski @kchain @pixel @titey @whyshock @mar1na and @govnerd 

that you guys are officially our first bytelight holders and can go ask any data questions you want in the /data channel ;) let's get some fun question/answering going!!!

What influence (if any) does lower user transaction fees have on “consumer user” activity on OP Chains?

Likely could start by comparing time periods with low L1 gas prices versus high L1 gas prices, post-Bedrock (modern fee model). 

Consumer = humans pressing buttons on a website, not bots

data @ op labs, building @optimism 🔴✨ | go /gators 🐊  | casts are my own things | msilb7.com

I wonder if a valid rephrasing of this is “what is the confidence interval of gas price that a user is willing to pay within”. So can we look at users over the last year who have transacted at least once a week and see if they have differing “gas ranges”? And from there, identify the 50th percentile gas max?

headmaster @duneanalytics, previously mirror and consensys

that could be a variant. I was thinking like:

When gas prices are lower, consumer users transact x% more often, and skew towards y types of apps.

But maybe per address / ~cluster you could try to index "normal" usage and sensitivities as prices go higher/lower?

Maybe way too in the weeds, though the source of my q is like:

Lower fees are obviously better & everyone wants cheaper txs. But what impact should we expect as prices drop to various levels?

Eventually you get to a point like "are fees the most important UX thing to solve now, or do we move on to something else?"