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Bigger is not always better!

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Jun 7, 2020
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Hi everyone, 👋👋 - I posted another blog post over at CB Explorer:

Bigger is not always better!


Some interesting stats over at CB Cam Insights led me to write another blog post about different tip averages based on the size of an audience in Chaturbate cam shows.


viewer_tokens_insight.png


TL;DR - there's many ways to be successful on Chaturbate ChaturbateChaturbate- while many performers strive to be on top of the charts, there's many, many more performers that are supported by a smaller, loyal fanbase.

Cheers!
 
More popular means better chance of getting more tokens (but ofc doesnt guarantee it) and also less risk of getting bored at work. But yeah I know couple of girls who prefer to have small loyal group then be on the front page.
 
I prefer rooms with less traffic. I usually seek out models at the end of the list. To be honest, I get more attention this way. But I will tip between 500-2000 tokens when visiting my favorites. Some have outgrown me but that is the goal obviously.

Same. I never go to any rooms even near the top of the list. Usually the opposite. I'd much rather have more one-on-one interactions.

The models I see most often aren't making bank like the front page girls but they do great for the level that they're working with their regulars and others coming through.
 
Interesting. I appreciate that you may not wish to answer, but I'm curious about the basis for the graph data.
Over what period of time is the tokens per viewer (vertical axis) taken? Per show, per hour online, averaged over a number of shows?
Also, is the number of viewers in the room (horizontal axis) the absolute maximum number that were in the room during a show, or the total number of individuals from start to end of the show? Assume it include anonymous viewers too?
 
I don't know, with that logic Id still make more money over time with the influx of small tips verses the few larger ones. At least when the ratio is comparing 50 viewers vs 10,000 viewers.
 
I normally look for the rooms with less traffic for a few reasons. First of all the model will normally start a conversation with you and 2 they actually acknowledge the tip you make, no matter the size.
 
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I don't know, with that logic Id still make more money over time with the influx of small tips verses the few larger ones. At least when the ratio is comparing 50 viewers vs 10,000 viewers.
and with a higher number of viewers tipping a small amount opposed to a handful of members tipping large amounts, when one of those members stops visiting the room or stops tipping then that impact of that is felt a lot less.
 
and with a higher number of viewers tipping a small amount opposed to a handful of members tipping large amounts, when one of those members stops visiting the room or stops tipping then that impact of that is felt a lot less.
I don't spend much time in any of the really busy rooms these days, but when I did, it seemed that there was still a small overall number of viewers that tipped very large amounts. So I don't think you can apply this logic.
 
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I don't spend much time in any of the really busy rooms these days, but when I did, it seemed that there was still a small overall number of viewers that tipped very large amounts. So I don't think you can apply this logic.
I work on streamate. I personally make the bulk of my income from $5 tips and 5 minute shows.

Because they add up. They're easier transactions to get.

Ill probably get like 3 shows longer than 10 minutes in any 4 hour shift. Whereas I'll get tons of 5 minute shows and TONS of $5 tips. I wouldn't get all those little ones if I didn't have the traffic for it.

Any time you add a larger sample size the average per will go down, but that does not mean the end result is smaller.
 
I don't spend much time in any of the really busy rooms these days, but when I did, it seemed that there was still a small overall number of viewers that tipped very large amounts. So I don't think you can apply this logic.
The chart shows that as the room size gets bigger the average tip amount decreases this is confirmed in what you have found with larger rooms not having large tips, but the point that I am making is that even if the average tip size decreases, but the model ends up earning the same amount (as now there are more members tipping smaller amounts) the model is still in a better position at the end of the day.

let's say a model makes 1000 tokens in a day, 1000 people tipping 1 token or 100 people tipping 10 tokens or even 2 people tipping 500 tokens is better for the model 1 person tipping 1000 tokens, having more people that contribute to what the model makes means that if any of those members leave there is less of a negative impact on the models income.
 
I don't spend much time in any of the really busy rooms these days, but when I did, it seemed that there was still a small overall number of viewers that tipped very large amounts. So I don't think you can apply this logic.
Yeah it's really bad logic that doesn't take scale into consideration that makes the ratio of freeloaders to tippers pretty moot.

Say a page 1 model has 10k viewers and maybe she gets 50-100 people tipping her. That's still bringing in more than someone with <50 viewers, especially if the tip menu rates are higher.

I watched a model starting up a goal show make 4k tokens in her first 15 minutes. She had over 500 people trickle in but only about 10 were tipping her, yet she was still hitting goals at a steady pace like it was nothing.
 
Yes not disagreeing with any of you; especially as models, I'm sure you're very aware of how your own earnings function.
But that's one of the reasons I asked for clarification of how the graph stats are determined, because it really does matter.
I'm very interested as someone who has tried to support a fantastic model that I truly believe is competitive with the page 1 ranked models, yet often struggles to get more than a couple of hundred viewers into her room. Of which, maybe 60-70% are anonymous, and only around 5% have tokens. Of these, maybe only 1 or 2 that actually use them. And I'm one of them.

I joined a room a couple of nights ago, it had about 10,000 viewers present. There was a whale in the room, kept writing about how he had been buying and selling commodities (gold and bitcoin) lately, and made a fortune. Every now and then, he'd throw down a 5,000 or 10,000 token tip. No judgement, but literally, nobody else was tipping too. So here was a room at the right hand side of the graph shown at the top of this thread. The whale spent maybe 200,000 tokens while I was there, which would have averaged to 20 tokens per viewer in that time...... but all down to one guy. If he'd left, no doubt others would have begun tipping, but probably not to the same average spend.......
 
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Hello everyone, very interesting what I raised, besides being a webcam model I am a scientist and the rules for a "creative use of statistics" (that is not misleading) are the same in a molecular biology laboratory as in an office of marketing, then it happens that you can shed light on the events or else a truck full of shadows. When we talk about probability, it is always before the phenomenon, since once something really happens, it is totally affected by the incidence and the distribution does not say anything. The statistics that are obtained from observable data derived from processes that we do not know can be easily manipulated by people who know the internal workings of the system that produces the data. My style as a model is that of a small room where the host meets one and each of the people who enter and my effort is put into achieving intimacy and warmth, this is possible as long as they do not all enter the intimate together, here again Incidence is opposed to distribution, since to maintain the level of intimidation a widely distributed low is necessary, how do I bring this to my room (?) Instead of broadcasting 6 hours straight, I broadcast 2 hours in the morning 2 in the afternoon and 2 in the evening. Another point in favor of this wide distribution is that although people like to know what they are going to find, it is that same comfortable uniformity that ends up boring them. When the flow begins to thicken it is time to start thinking about the next eccentricity to apply. This is possible as long as they do not enter the intimate all together, here again The incidence is opposed to the distribution, since to maintain the level of intimidation a widely distributed low is necessary, how do I bring this to my room (?) Instead of transmitting 6 hours in a row, I transmit 2 hours in the morning, 2 in the afternoon and two at night. Another point in favor of this wide distribution is that although people like to know what they are going to find, it is that same comfortable uniformity that ends up boring them. When the flow begins to thicken it is time to start thinking about the next eccentricity to apply. This is possible as long as they do not all enter the intimate together, here again The incidence is opposed to the distribution, since to maintain the level of intimidation a widely distributed low incidence is necessary, how do I bring this to my room (?) Instead of transmitting 6 hours in a row, I transmit 2 hours in the morning, 2 in the afternoon and two at night. Another point in favor of this wide distribution is that although people like to know what they are going to find, it is that same comfortable uniformity that ends up boring them. When the flow begins to thicken it is time to start thinking about the next eccentricity to apply. Since a widely distributed low incidence is necessary to maintain the level of intimidation, how do I bring this to my room (?) Instead of broadcasting 6 hours straight, I broadcast 2 hours in the morning, 2 in the afternoon and two in the afternoon. Another point in favor of this wide distribution is that although people like to know what they are going to find, it is that same comfortable uniformity that ends up boring them. When the flow begins to thicken it is time to start thinking about the next eccentricity to apply. Since a widely distributed low incidence is necessary to maintain the level of intimidation, how do I bring this to my room (?) Instead of broadcasting 6 hours straight, I broadcast 2 hours in the morning, 2 in the afternoon and two in the afternoon. Another point in favor of this wide distribution is that although people like to know what they are going to find, it is that same comfortable uniformity that ends up boring them. When the flow begins to thicken it is time to start thinking about the next eccentricity to apply. it is that same comfortable uniformity that ends up boring them. When the flow begins to thicken it is time to start thinking about the next eccentricity to apply. it is that same comfortable uniformity that ends up boring them. When the flow begins to thicken it is time to start thinking about the next eccentricity to apply.

One of my favorite moments is cleaning the rooms of my friends of how imbesil appears, this leads to a growing experience like Mod, from which I have been able to make some interesting observations, it is not very clear that to be able to clearly observe the emerging phenomena; The theory must never precede the phenomenon, if not the opposite: any hypothesis or attempt at generalization is derived from the facts. While it is true that a writing whale discourages the skinniest fish from writing. The opposite is also true, many times I see how many sperm whale cubs are concentrated in a room without any of them acting, in that case a small mojarrita that types 25 Tokens is usually enough to bait the monsters.

Another trick is to maintain a constant level of typing so that the user who enters always does so in a room that already has a minimum and constant base activity, this could represent a real budget for a moderator or for a User-primer. a trick, which I will not reveal in public, if anyone needs to know, contact me by message.


Me encanta este foro !!!! Yeeeahhhhhhhhhhhhhh ¡
Onfirebigman

Saludos cordiales a todos! Onfirebigman


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The chart shows that as the room size gets bigger the average tip amount decreases this is confirmed in what you have found with larger rooms not having large tips, but the point that I am making is that even if the average tip size decreases, but the model ends up earning the same amount (as now there are more members tipping smaller amounts) the model is still in a better position at the end of the day.

let's say a model makes 1000 tokens in a day, 1000 people tipping 1 token or 100 people tipping 10 tokens or even 2 people tipping 500 tokens is better for the model 1 person tipping 1000 tokens, having more people that contribute to what the model makes means that if any of those members leave there is less of a negative impact on the models income.
^ This is absolutely true - larger rooms on average still make more money. What the chart shows is the multiplier you can use to get the expected token earnings per room size (take it with a grain of salt, it's an average over a very diverse set of cam sessions).
So for 100 viewers x ~22.5 = 2,250 tokens earnings, 10,000 viewers x ~2.5 = 25,0000 tokens earnings. The point is the multiplier is lower, expected earnings still higher but not by as much as you would think just looking at the viewer numbers!
 
So for 100 viewers x ~22.5 = 2,250 tokens earnings, 10,000 viewers x ~2.5 = 25,0000 tokens earnings. The point is the multiplier is lower, expected earnings still higher but not by as much as you would think just looking at the viewer numbers!
You also have to take into account that most rooms on CB with 7000-10000+ viewers are at least 90% annon, and 4-5% grey. So you really only have about 350 to 500 actual token holders. From that amount maybe 80-100 will be tipping with 5-10 whales in that group.
 
You also have to take into account that most rooms on CB with 7000-10000+ viewers are at least 90% annon, and 4-5% grey. So you really only have about 350 to 500 actual token holders. From that amount maybe 80-100 will be tipping with 5-10 whales in that group.

Yeah, the variable "viewers" is not really viewers in this analysis if you don't remove the anons that are from random popups and aren't even really watching the stream. As far as I know CB doesn't make a distinction between viewing anons and advertisement/popup anons though.

The same analyses with "registered accounts" could be interesting. And "coloured accounts" (although coloured accounts now also include people that only bought tokens once and don't have tokens anymore, so only kinda signals people that have been willing to spend on the site at some point in their accounts lifetime)

I think a lot of people will be surprised how low the registered & tokened and tippers rates actually are based on how big certain roomsizes appear 😆 (also depends on time of day)
 
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