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Making bank as a solo founder seems to be rare!

I am a long time podcast listener who recently joined the community.

One post I found particularly interesting was Holy heck this is hard. Being a solo founder myself, I was curious about the revenue distribution of solo founders here on IndieHackers. That’s why I created a simply chart highlighting this distribution.

On the products page, I applied the following two filters:

  • Solo founder
  • Stripe-verified revenue

And then I scrolled down for a while ;)

The first chart shows the revenue distribution for a total of 970 products matching the filters above.

785 (80.9%) products make less than 500 MRR, whereas 62 (6.4%) make more than 5,000 MRR. And then they are 37 (4.8%) „superstar products“ earning more than 10k every month (the second chart focuses on these products).

Overall, there seem to be few products in the mid-range of revenues: Either one is rather unsuccessful or very successful (although the cut at 10,000 dollars was of course arbitrarily chosen).

Finally, I want to share a few thoughts about this chart:

  • You shouldn't be too sure up front that a product's future revenue stream can replace an average income.
  • Launching a product that brings in only a few dollars a month is perfectly normal. Products that generate significantly more revenue are outliers. That's just reality and it doesn't have to be discouraging.
  • Even if the distribution is highly skewed, the chances of creating a successful product are still much better than in other areas where success is even rarer (e.g. writing a commercially successful book or becoming a successful actor).
  1. 5

    Keep in mind that companies with more income might be less likely to share it publicly. When you first start out it might be very fun and interesting to share your revenue, even from a marketing standpoint. But as you grow you don't have much to gain from it, and if anything it could cause you issues.

    1. 4

      Agreed. I suspect many solo founders may not want to broadcast their lucrative niches.

      Also, if a solo business is successful enough, it may make sense to set new goals, bring in more people, and no longer be solo (not sure how or if this gets reflected in the data).

    2. 2

      Yes, very true. In this sense, reality may not be as harsh as this dataset makes it seem ;)

      1. 1

        This comment was deleted 3 years ago.

  2. 4

    Seems like normal distribution compared to normal businesses. One of my projects makes the bulk of my income but is not reported in MRR. In fact it's at $57 MRR but has made me $34k in the past year.

    1. 1

      Good point! The charts only capture recurring revenue and therefore underestimate total revenue.

  3. 3

    log distribution

    It often helps to look at financial data using a log scale. I scraped the same values, pasted into Google Sheets, and created a second column that was calculated by applying the LOG10 function to the scraped data.

    One thing that happens is we get something that looks a lot more like a normal distribution, centered around 2.48. To turn that back into a dollar amount, we apply the inverse of LOG10, which is 10^x.

    10^2.48 = $302/month

    (I couldn't find a way to simply enable log scale within the chart for the x-axis of a histogram in Google Sheets. I would have preferred that, as then we'd be able to read the raw dollar amounts right off the x-axis labels. If someone knows a way to do that in this app, I'd appreciate a pointer.)

    If the distribution of the LOG10 values is normal, then the distribution of the revenues themselves is log-normal. Among other phenomena, this distribution seems to mostly match the distribution of personal income at large:

    In economics, there is evidence that the income of 97%–99% of the population is distributed log-normally.[60] (The distribution of higher-income individuals follows a Pareto distribution).[61] (from Wikipedia)

    Another thing that happens is that values of $0 or less are removed from the chart, since LOG10 has no value for these inputs. It turns out the majority (593 out of 970 total) of these products are at $0. Many are probably new and simply pre-revenue. Others could have previously had revenue, and since been wound-down. Others likely gave up prior to revenue. Maybe some ultimately decided to collect revenue in a different way than Stripe. Since we don't know that breakdown, I think the $0 revenue reports are ultimately noise, and they're better off not included in this chart.

    I was surprised to see that three companies are currently reporting negative revenue! I don't know how that happens, but I'd be curious to find out.

    The median value of all the positive revenues is $303... very close to the midpoint of that chart, as expected.

    Others have raised good points about confounding factors. I'll also add that a solo founder is simply more likely to be taking a part-time approach, which probably correlates with lower revenue to some degree. All in all, this is an interesting data set, but it's noisy, and I'd be careful before using it to talk yourself into or out of starting something.

    1. 2

      Wow, @mattgillooly! This is such a smart way to look into the data. It's amazing to see the normal distribution using the log scale.

      As for the x-axis labels, you'd have to built the histogram chart yourself. I mean,
      specify bins and calculate distribution using the FREQUENCY function. Next, you calculate a column with the original amounts corresponding to bin boundaries (10 ^ bin). Finally, you can create a bar chart with values from the calculated distribution and use the "10 ^ bin" column as labels.

    2. 1

      You make a lot of good points! There are probably a lot of confounding variables (many were mentioned in the comments), so we should be careful to draw any definitive conclusions from this data set. In general, low revenues might be over-sampled, while higher revenues are likely under-sampled.

      However, I think we'll still end up with some right-skewed distribution (mode > median > mean), which makes sense given how hard it is to start (and sustain) a business.

  4. 2

    Really nice post and interesting data! You could break this off to something like indiehackertrends, just like hntrends for hackernews ;)

  5. 2

    I believe i know the remedy to this. Indie Developers add value to their users with their product but don’t create an on platform environment where their users can add value to each other. You are the end of the journey more or less.

  6. 2

    This is why IHers should dip their toe in first with info products. Now if only there was an online course platform that was tailored to technical folk. Oh wait... :)

  7. 2

    I think this hits home for many. Yes, on the title page and in the podcast there are always the successful ones sharing their numbers, but many more without anything great to share.

  8. 2

    Yeah, the real big ones are rare for solos.

    You know, it's hard work doing everything from idea, building product, marketing, customer relations and building more.

    And hearing bad feedback about your beloved project can also be heart breaking.
    That's why I think this entrepreneurial lifestyle is tough, especially going at it alone.

    I will be doing my next missions with other people, for sure

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