Posted July 29, 2010
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Following up my earlier post about 100 Fans in the Rain, I done some magical systems simulations to help illustrate the way my brain is working. And wow, did I get surprised by my own numbers! But first, a recap:
There’s a theory called 1,000 True Fans, wherein any artist who can dig up a thousand passionate followers can earn a living. If each follower spends about $100 annually on the artist, they’re making $100,000 a year, which ain’t too shabby. The goal of the 1,000 True Fans approach is to find people who are dedicated enough to spend that much without worrying about it. It’s only $8.33 per month, but that’s a lot of money for some people.
100 Fans in the Rain are a different class of supporter altogether. These fans are even more fanatical than the 1,000 True ones. They’re the ones who will put up with crap nobody else will tolerate, tell you you don’t suck when you really do, and pitch your work to strangers while drunk at parties. They’re the dedicated few who really keep you afloat, even if they don’t spend any money on you. You need their support more than you need their money, so a smart artist will find and hold on to their Rain Fans at all costs.
I ran this through some simulation models to see how they add up, because I wanted to get a sense of how valuable these people really are. The numbers are pretty exciting.
We need to look at this backwards, starting with our goal 1,000 True Fans (TFs). For the sake of simplicity, let’s say each TF spends $9/month on you for the duration of their stay (which we’ll assume is indefinite). Realistically, you probably won’t sell $9 subscriptions so much as sales of things… but subscriptions are easier to model. Our goal is to earn $9,000/month or $108,000/year. How do we do that?
To start, you have to look at word of mouth (WOM). TFs talk to uninitiated readers and help them discover you… a Twitter post here, a Goodreads review there. Nothing dramatic, but enough to spread the word. Thanks to their efforts, we’ll guess you’re adding the equivalent of 0.015% of the potential reader pool every month (the reader pool itself is a fraction of the total weblit reader community of 10,000, and grows at 2.2% per month. Both these numbers are out-of-thin-air guesses). At that rate, it will take approximately 60 months for you to reach your goal of 1,000 TFs.
60 months is a long time. If we start today (July, 2010), 60 months in the future is July 2015. Five years! And even if we assume you’re creating something worth paying for every month for 60 months, counting on uninterrupted exponential growth is not always the best strategy. So how do we supplement it?
Rain Fans (RFs) are a totally different kind of fan. Never mind how much they spend, it’s all about how much they talk about you. Their WOM rate is 0.038%, more than double that of normal fans, so when you add even one into the mix, it suddenly takes 54 months instead of 60.
But RFs don’t just affect the adoption of TFs… they also self-recruit. Their WOM rate is greatly reduced by the fact that it’s a lot harder to make a Rain Fan than a True Fan, but even at a pessimistic 0.0089%, they reduce your wait to only 49 months. That’s almost a year shaved off your journey to 1,000 True Fans!
Even if RFs aren’t paying you anything, they’re worth a lot of money. In fact, you might argue it would be worth offering potential RFs an enticement to sign up. Find ways to bring new RFs in, and you increase the rate at which they can recruit themselves. Even a modest increase from 0.0089% to 0.01% would get you to your goal in 47 months. Reach 0.05% and you’re down to 33 months!
How do you do that? Rewards programs are an excellent approach. Special perks, behind-the-scenes access and direct and privileged communication with their favourite author can work wonders. The most elite and lavish you make the world of RFs, the more people you’ll attract, and the faster your WOM will grow.
None of this, of course, takes into account promoting yourself outside your site, or Kindle books, or anything else that helps boost your TF base in isolated bursts. On the other side of the coin, we also assume you’re turning out content worth reading month after month, and there are never any hiccups in your delivery schedule. And possibly most flawed of all, we assume the weblit world only has 10,000 readers in total, of which you will only ever really access 10%. I know some stats put the weblit world at 20,000 or higher, but I wanted to be conservative, just to avoid it sounding too pie-in-the-sky.
Putting it bluntly: even with things going your way, at normal growth, you can expect to have 6 true fans at the end of your first year, 32 at the end of your second, and 154 at the end of your third. 154 TFs would pay $1,386/month. That’s not bad at all, but remember there will be literally YEARS of small returns before you get to that point. This is still a game of patience.
The only way I can see speeding the process up is to recruit more RFs at the start. Instead of building from scratch, start with five, and the end of your second year jumps from 32 to 130. But then, can you really create RFs, or do they have to happen naturally? And what happens if you make your RF treats so exciting that you start converting TFs away from paying customers? Lots of issues to consider, but at least there’s a base to work from.
Extra note: The WOM rates I outlined above are not entirely based on thin air. I looked at my old stats from the last 2 years and tried to deconstruct numbers based on confirmed events that I felt related to RF activity. It’s very possible (and even highly likely) that TFs will recruit at a rate totally unlike the 0.015% I suggest here, but I wanted to pull my numbers from SOMEWHERE, rather than just make them up out of thin air, like I did with the weblit audience and growth rate. Oh, and I should also say 0.015% is actually 0.01531% before I rounded it for presentation, and there is a certain amount of randomized “jitter” added to my simulator that I have not bothered to average out, so many of the estimates above could be +/- 2 weeks depending on which run you look at.
If you’d like numbers for a custom simulation, just let me know your parameters in the comments. It only takes me a few minutes to do, and I’m happy to tweak things if you’d like to see how new ideas work out.
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