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Great! I saw some stats from this some time back and couldnt find the source!
Should be an interesting read.
Thank you, wherever you are!
Thanks for this that helps
What did you think were the best parts?
The stats really do make a difference I think.
The graphs didn’t have a time frame on them but in the text it mentioned they looked at the stats for a nine month period. I am not sure how recent the stats were.
Only .4% make over $50,000. Whether they mean per year or not was never mentioned.
They felt that a certain income level that is gaining regularly in sales volume is more likely to continue to increase in sales than those who have hit some kind of ceiling in sales and remains static. My impressions seem to drop the more I earn which is the reason my sales and earnings may remain static.
We find that more than 40% sellers have only earned
$5-$100 over the last nine months whereas the proportion
of sellers with revenue > $50,000 is only about
0.4% (see fig 1).
That was the most surprising thing to me.
$50,000 is the average per capita income in the U.S.
The other thing they mentioned, which doesn’t surprise me but would surprise most people, is the more competition in a category, the more the earnings of sellers there overall. Competition is healthy for everyone.
A few things seemed off to me, like I think they probably got to their very high percentage of $5 gigs taking only the $5 gig from the starting at $5 gig 3 gig packages into account while ignoring the 2 other gigs from those packages, but a lot of the numbers were rather interesting.
This seems to be from around June 2016.
And how do they know these statistics? Some of them would be closely guarded secrets only fiverr employees would know.
Most of the graphs are screwy too, lacking in details.
They say “35% of sellers respond within an hour”. Did they get this figure from fiverr itself or did they look at every profile and compile this themselves? I have this question about all the statistics. How do they know?
They said they "We crawled Fiverr data using preferential crawlers
in R. "
This chart doesn’t make much sense:
Table 2. Performance of sellers.
Level Avg. Sale Avg. Revenue Avg. Gigs
Level 1 12.94 $112.66 1.46
Level 2 158.22 $1417.15 2.22
Top rated 2344.24 $22,413.26 4.04
It mentions Sale Avg. and Revenue Avg. but over what time period?
Top rated sellers have an average sale price of $2344.24?
Thanks for this
Yes, a bit of clear info on how they got their stats would have been nice, and time references seem to be up to the reader to guess; either they did a lot of ‘crawler’ or manual or semi manual work or they must have had access to Fiverr info. Since that’s not stated anywhere which seems unusual for such a project (?) I suppose it wasn’t official access, unless I missed it being mentioned.
One study on Fiverr I saw recently was based on stats from a loan provider for people with poor credit history and so the stats were likely to be quite incorrect. The source is important but the stats are interesting all the same.
Another interesting thing is that the study is from around June 2016 but it is not clear when the data was collected. The data does not mention packages which as I remember was introduced in Feb/March of 2016?
The statistics and graphs are presented in such a careless way it doesn’t have any meaning for me.
Thanks for sharing.
Looking at the names of the analysers should be interesting for someone specific on here too, BTW.
I looked up the institute the authors (students, I assume) put with their names below the header, it´s the “Indian Institute of Technology Kharagpur”, so I don´t assume they were allowed to only do guesswork for their stats.
Don’t tempt him! We don’t need him in O/T Mod