What makes a camgirl successful? Survey results

Option A: Having natural hair color
Option B: Being really hot
Option C: Doing lots of drugs
Option D: Doing a fuckton of games
Option E: All of the above

hint: the answer is E

My Data Has Limits, Beware!

I got 311 responses from people who identified as cam performers. I threw out all male cammers, people who hadn’t cammed in the last 6 months, people who had wildly inconsistent answers, and people who skipped a lot of questions.

This left me with a sample size of 278.

If there weren’t a lot of answers in a category, sometimes I grouped them together. For example, when asked to rate their own attractiveness, only a handful gave answers spread around the range of 1-5. I combined all of them to function as 5. So, for example, “15% of girls are 5 or under, 22% are 6, 18% are 7, etc.” I don’t know if this is the right way to handle data, so if I made an error here, let me know!

I tried to ensure all categories had at least 25 responses, but most have over 30.

All spectrum answers were out of 7 (e.g., on a scale from 1 (low) and 7 (high), rate your body weight)

I think the error margin for my answers is 5-7%, based off of some light googling, but the margin is probably much higher for correlations. Try to squint when you look at the graphs.

I used DataHero, a correlation finder for dummies complete idiots.

Also please remember my sample size is camgirls who are involved in networking! I used twitter and forums to spread the survey, so I missed camgirls who are disconnected from the community, and their numbers might be very different.

Onto the juice:

DataHero Untitled.png

When I asked about income, I asked for ranges, and plugged in the numbers as the bottom of that range. For example: an income of $1-10 I registered as ‘1.’ The number you see is the average sum of the bottom of all the ranges. The highest category is $200+/hr.

So, out of camgirls who struggle with anxiety/depression frequently, the bottom range of their earnings is $45/hr. Girls who don’t struggle make a bottom range of $62/hr. I don’t actually know if this is the right way to categorize the data, but at least the comparisons between categories seem legit for now.

The total average bottom-range number of all responses is $49 per hour.

DataHero Over last 6 mon, have you struggled with anxietydepression.png

Remember that correlation does not equal causation! It might be that girls who make more money end up being financially secure which leads to less depression. It might also be that girls who are prone to depression have this affect their work life, thus leading to lower income. I don’t know which one it is. Maybe/probably both.

Income and age:DataHero Income and age
I would guess that newer girls tend to be younger, and as thus have a less established base and less income. The income increases once the base is established, but drops off once get too ripe.

DataHero Age and Length of Cam Career
This seems to hold somewhat true. The 27-32 and the 33+ year old categories each generally have been camming for the same amount of time, but those over 33 make substantially less. The 23-26 year olds have cammed for less time than the 27+ age group, but make more money.

DataHero Length of Cam Career and Income.png

If you’ll notice I fucked up a bit when asking about length of camming. If you’ll also notice, there’s no difference in income between girls who have cammed 0-6 months and girls who’ve cammed 6-12 months. 2 years is where it really starts to take off. I don’t know about that dip in the 3rd year.

So far it looks like the secret to success is “start camming really young” and “cam for a long time.”

DataHero Body Weight.png
(Due to low answers, I combined people who answered “1” or “2” into just “2”, and same for 6-7)

Looks like 3/7 bodyweight earns the most – with an interesting spike at the heavier end. Is this a sign of niche preference for fluffier ladies?

DataHero Is camming your only source of income.png
This one is pretty obvious. Remember we don’t know which causes which – the income or the time put in!

DataHero Hours Per Week and Income.png
Turns out the ‘0-5′ and the ’40+’ categories have only around 20 responses each, so expect higher variance there.
That being said, all ways I looked at the data showed a spike around 10-20 hours a week, and 40+ hours a week. Is this indicative of two different types of successful camgirl strategies?

DataHero Days per week and income (1).png
I took out the ‘0-1’ category because there were few responses, but the average reported income for 0-1 days was very low. I say this because I don’t understand why 2 days a week is so high.

DataHero Hours and Days.png
That being said, the hours and days correlation is beautifully strong.

But it looks like there’s a bit of two sweet spots here – working 2 days a week, or 10-15 hours, and working 40+ hours a week, or 5 days a week.
There wasn’t enough data to look closely at the distinctions of hours ‘more’ than 40 a week, but I would guess it falls off at the upper ends, much like days of week falls off once you work over 5 days a week.

Remember: correlation does not equal causation. Working more than 5 days a week does not mean you will make less per hour – it’s very possible that 7-day girls are also ones who work from studios, or split-cam, or something, and thus bring down the income numbers. I don’t know.

DataHero Attractiveness and Income.png
(I combined responses in 1-5 and 9-10 due to low counts)
And maybe the obvious thing we all want to ignore – hotter (at least self-reported hotter) girls make more money. A 6/10 girl will make, on average, a whopping $33 less per hour than a 9/10 girl.

Of course it’s possible girls who think they are hotter are more confident, and confidence is what earns more money. I personally doubt this, however.

DataHero Predicted rank and Actual Income.png

For this question, I asked girls to rank themselves in comparison to other camgirls (for income), and then compared it to the actual income ranking.

There might be something fucky going on with the way I organized the data, but from this it looks like girls who rated themselves “3” or “4” (out of 7) in comparison to other camgirls are overrating themselves. You 3 and 4 girls, you’re doing worse than you think!

DataHero Hair Color and Income.png
Blonde and Brunette competes for the goal, while ‘Other’ lags behind. (grey was an option, but there were so few responders that I filtered that out.) There’s a pretty significant difference in income, with ‘other’ hair colors earning $24 less per hour.

I thought that maybe less attractive people tend to dye their hair weird colors, so I looked at the correlation between hair color and self-rated attractiveness. There was no significant correlation (the biggest difference was 7.26 at black hair, and 7.52 at blonde hair, which I don’t think is a huge difference? ‘Other’ was 7.45, anyway).

DataHero Sexy Shows and Income
Here, “1” was “no sexualness” and “7” was “very explicit. I interpret this as “non-nude” models doing ok, and “kinda sexy girls” doing ok, with everyone else failing for some reason. I really don’t understand that huge difference between 3 and 4.

DataHero Alcohol and Drugs and Income.png

The question was “Do you drink or do other drugs specifically to assist with cam performance or coping with camming?”

I thought maybe this is due to correlation with camming time – girls who cam for a long time eventually turn to drugs or alcohol to cope/help. I was right!
DataHero Cam Career Length and DrugAlcohol use.png
DataHero Member Communication and Income.png
I merged ‘no’ (very few responses) into ‘rarely.’
And, as is unsurprising, the more girls talk to their members off cam, the higher their income.

DataHero Freeloader Complaints and Income.png
This is the question that started it all! I wanted to know if girls who vocalize their disapproval of freeloaders tend to make more or less money. Girls who say ‘no’ or ‘rarely’ make more money than girls who say ‘frequently’ or ‘occasionally’ – though frequently makes more money than occasionally. I don’t know what that’s about.

DataHero Games and Income.png

Here, ‘1’ was low on the “how much do you do games” scale, and ‘7’ was high.

This is really interesting. Girls who say they are 7 on the scale of games do way better than everyone else.

DataHero Site and Income.png
Interestingly, Chaturbate cammers do worse than ‘other.’ Unsurprisingly, MFC girls rake in the big bucks.

DataHero Number of Sites and Income.png
Girls who use 1 site make $28 more per hour than girls who use 2.

DataHero Top 3 Tippers and Income.png
The question was, what percentage of your income comes from your top 3 tippers?
(each answer was a range; ’90’ on the graph was ’90-100%’ range in the answer selection)

DataHero Vocalizing Complaints and Income.png
The question was about whether girls vocalize their complaints about slow days. The results weren’t strong and it appears as though this doesn’t have any significant effect on income.

DataHero Relationship Status and Income.png
Girls who pretend they are single make $18/hr more than girls who admit they aren’t.
However girls who don’t have a SO at all make even less. Most probably, men are less likely to tip girls who they know are dating someone. However a few things:

Girls who have jealous SOs might be more open about them, and jealous SOs might be less supportive of camming in other areas.
Girls with supportive SOs might put less pressure on them to disclose their relationship.
Girls who don’t have any SOs might have much less help in camming overall.

Although – are less attractive girls less likely to date? Let’s check.
DataHero Relationship Status and Attractiveness.png
Nope! No correlation to attractiveness (biggest difference is 0.12).
I suspect this indicates that SOs provide a great deal of behind-the-scenes assistance and motivation.

It’s also possible that girls without SOs also tend to have fewer household expenses, and thus need to make less money to support themselves, and so take camming less seriously.

I don’t think I had enough data to make good predictions about age and relationship status, but it’s possible older women still camming are more likely to be single, and older women make less money.

DataHero Physical Sex and Income.png

“For pay” category had low response number, so don’t take it too seriously.
That being said, 22.4% of girls reported having sexual contact with their members, 15% of it voluntary. Girls who have had voluntary sexual contact with their members make more money. I think this is just that girls who cam longer both tend to make more and tend to eventually become more likely to sex a member. I checked – girls who haven’t sex’d a member have been camming on average 2.55 years, and those who ‘have’ voluntarily sex’d a member have cammed on average 3.62

DataHero Niche Cammers and Income.png

Had low-ish (25) numbers for ‘yes, very much’ so take it with a grain of salt.

DataHero Aesthetic Style and Income.png
Here, 1 was ‘very alternative, tattoos, piercings, etc.’ and 7 was ‘very traditional; no piercings, long hair, etc.’

Generally speaking, the more traditional a camgirl looks, the higher her income.

DataHero Thinking About Work and Income.png
0-4 were combined due to low answer volume.
Looks like girls who either don’t take their work home with them, or do, make the most.

DataHero Parents and Length of Cam Career.png
I initially did this as correlation between parents and income, but then I figured it’s probably more just about ‘how long have you been camming,’ and I think I was right. The longer a camgirl has been camming, the more likely it is that their parents know.

Since the graph cuts it off – the first ‘yes” is “mostly accepting,” and the second “yes” is “mostly disapproving.”

And, as a last bonus: non-nude models (both strictly and loosely, so probably including ‘teasy’ models) make only $4 less per hour than nude models!

So in summary: Start camming early. Be young. Have cammed a lot. Work either really hard or kinda hard, but nowhere in between. Be traditional. Don’t have weird colored hair. Do drugs and drink. Don’t have anxiety. Cam on MFC (only) and do a ton of games. Be super hot. Talk to your members offline. Have sex with your members. Get a boyfriend but don’t tell anyone about it. Don’t be too graphically sexy. Be kinda skinny but not too skinny.

And whalah, you have the recipe (or a description, at least) of a successful camgirl!

If you’re interested in taking more surveys, all currently open ones are under the ‘surveys’ tab above, and I will tweet about new ones I add. This survey has taught me a lot about what things to avoid in survey making, and hopefully the next one will be a lot more accurate, fine-tuned, and useful!

Thank you everyone for your help!

12 thoughts on “What makes a camgirl successful? Survey results”

  1. I saw this on a Facebook friend’s wall; I’d be interested in looking at your source data to see what I can make of it.

    Full disclosure: I run a data science bootcamp 🙂

  2. Let’s mention another huge factor of success on cam: finding very rich client, a whale, who supports the girl regularly. Great example is Mary aka CrazyTeam. She has multiple rich tippers, but one of them is a real multi millionaire, who sends her thousands of dollars per shift. Her ranking would be way lower without his support. Many other girls on MFC got “famous” and rich thanks to those type of members, who sent them 200-400 000 tokens. So, it’s also about luck and finding the right member.

  3. Another theory for why women who lie about their relationship status make more is because we know these subgroup wants to craft a certain persona for their patrons and are willing to lie for it. And thus these individuals are more sophisticated with how they craft how their patron’s perceptions. So you would imagine these individuals would make more money from these behaviors.

    Also I would like to see how attractiveness and sexuality interact. I’ve noticed that the cam girls(on mfc) that are both successful (top 10) and do less sexual shows also tend to be extremely pretty like Crazy or extremely sophisticated like Kickaz.

  4. Just a few thoughts:

    Hair color: Red hair is my favorite. And my least favorite. And that’s just counting NATURAL red hair. The right shade with the right hair style is absolutely divine – but another shade and style, especially if it is stringy, does poorly compared to blond or brunette. Natural redheads tend to have pale skin, and I love pale skin – but not pasty skin. But what might really drive this stat down is the large number of cam girls with bright red, artificially colored hair. That artificial red hair ruins everything else – I don’t even want to look at them. If that’s included in the stats, it will give a false impression of the attractiveness of redheads.

    Self-rated attractiveness: A host of problems here. Ugly girls tend to overrate themselves, stunning girls tend to underestimate themselves. I wouldn’t put much confidence in this.

    Complaints about freeloaders: It makes perfect sense to me that no complaints and rare complaints rank highest, frequent complaints next, and occasional complaints rank lowest on income. Part of the fantasy is that the girl actually likes talking to you. You know she’s doing it for money, but it’s nice to think that she at least enjoys camming a little bit. A rare complaint, delivered gently, won’t affect things much, more than that is a definite turn-off – but with frequent complaints a girl might get a slight bump by way of a guilt trip – but it won’t make up for the loss of the fantasy.

  5. Sent here from slatestarcodex. This looks really interesting! As a journeyman data person, I rarely run across data that’s both a) interesting and b) relatively unexplored, and this definitely fits the bill. Would you be open to sharing the data somewhere? I’d love to take a crack at it.

    The biggest thing I would suggest for future analyses is error bars–ideally based on standard deviation, which I would hope DataHero offers. Should help a lot with evaluation; there are a lot of differences and bumps in these graphs which could be meaningful but are likely just noise.

    1. I’d be happy to share the data! I’m doing a 2nd survey for camgirls right now, with some of the questions fixed and more questions added. I can share that set with you once it’s ready if you’d like

  6. I think the non-zero’d axis on a couple of the graphs might be a bit misleading. Especially on the ‘sexy shows’ graph, the actual income difference isn’t huge from top to bottom ($14), but it looks much bigger because the graph starts at $40.

  7. who gives a flying fart about natural hair color? i cant tell the difference, if it looks good thats all that matters

  8. I really find your posts fascinating. An inquisitive mind is extremely attractive. Objectively.

    Adam S. Plotkin 804-402-5100 iPhone. iTypos. iApologize.

    >

Leave a Reply to falenas108Cancel reply