hourly.fyi
I'd love any feedback you might have, and of course if you were to volunteer some data ;)
I'm aware it looks bad on mobile atm.
I had somebody spamming my rates with profanity. The same person, 2 separate days, for over 5 hours in total, attempting to personally sabotage my launch by having expletives publicly render in my table to the public.
To the point where I was forced to gate the data behind emails.
I notice your selling point is that you don't require email.
Are you having the same issues? Or perhaps, was it you?
I can’t say it was you. Although if it continues maybe I’ll start digging into my logs a bit more. It just looks mighty suspicious.
Good luck on your launch.
A datum says it is "Project Billing" and has a rate of $300. Is that $300 per hour? Is that $300 total? What does that mean?
I need to be able to filter by location. For me, comparable large US cities. My cost of living is vastly different than someone living in India.
For this to be most useful, I need to be able to put in my rough skillset and then find how much similar people charge. Just browsing rates around the world isn't that useful.
And that brings me to the last issue. Hourly billing is stupid [1]. As much as possible, you should avoid charging hourly. It incentives you to work slower, more poorly, and have a worse experience with the client. But it's too hard to say, "I charged USD 100k for my project," because you need to have a complete and intimate understanding of the project.
For example, my latest consulting gig was fixing some Google Analytics and Facebook conversions for a small business. They were broken, and I fixed them. It took me ~15 minutes, and they paid me $1000. They got incredible value (their ads started working properly again), and I got paid for minimal effort. What do I put down on a site like this, $4000/hr?
For example: "6 month contract ended in 2021, and paid $125/hr"
You'd also be able to show how income has trended over time and possibly overlay it with macro economic events to try to put odd data into context.