#7 - Inequality in the Creator Economy, and why it can be a good thing

Everything in moderation. Even inequality.

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Hello subscribers! Previously, we looked at the business model and incentive structure of content platforms .

Today, let’s dive into how this type of incentive structure causes inequality… and why that might be okay for the creator economy.

Who is this for?

Platform operators. >80% of value for creators on platforms are typically captured by <1% of the creators. Operators with intrinsic motivation to help smaller creators may take inspiration to consider how platform power laws might be adjusted internally.

Founders. Entrepreneurs helping aspiring creators may find lessons in the shape of incumbent platforms and the broader ecosystem, and take heed as they design and shape their own products and businesses.

Learners. Ninja & Shroud defecting to Mixer, Joe Rogan’s $100M migration to Spotify, the epic collapse of Vine. Platforms have a spicy history of losing the talent who generate outsized value. How does this impact platform longevity?

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Last time on Advance the Creator Economy…

I dug into how distribution platforms operate as a business, and how they grow.

As platforms attract creators, they provide broader content selection for consumers, get more engagement from consumers, and generate more revenue from advertisers, part of which they share with creators.

The platform then pours revenue back into additional content acquisition and creation tools, improved consumer experience, and better advertising tech (e.g. smarter targeting, ad formats, analytics). Doing so accelerates platform growth.

Creators benefit as more consumers come to the platform for their content. In theory.

In practice, platform growth disproportionately benefits a small set of creators, and rarely translates to uniform growth for all creators.

Success gaps occur at every level of the system

Uneven success is evident starting at the ecosystem level.

FB, IG, YouTube, and Tik Tok account for ~4 hours of consumer lives a day, representing >50% of the time people spend online. Going down the list of most popular social apps, there is a steep drop off in popularity after #5, hence no one knows the name of #10 (sorry Tiya).

This seems to be the case all around the world. In China, Douyin and Kuaishou command 60% of the country’s online video time, projected to reach ~65% by 2025.

Each platform within the ecosystem is also extremely top heavy.

On Twitch, creators averaging >10 viewers on their stream are in the top 3% of Twitch. In reality, the top 2-3% of Twitch streamers are still relatively small. They earn variable amounts from fan funding, and most of them earn <$5000 per year from ads.

On Spotify, 98%+ of artists make <$200 annually from the platform. There are factors with label and publisher revenue sharing at play, but in the end almost all artists on Spotify would be starving without other sources of income.

On YouTube, 97.5% of creators don't make enough to reach the U.S. poverty line.

Zooming down to the individual level, and the inequality remains obvious. If we plot a rough estimate of income distribution for creators (Lorenz Curve for my Economics nerds), the income inequality between top creators and other creators is even more apparent than the wealth disparity within the U.S. population.

Grey line = Line of Equality

  • Completely equal income distribution. Every person has the same income. In this case, the bottom N% of society would always have N% of the income.

Red curve = Actual 2019 U.S. Economy

  • Top 20% of population earn >50% of all income

  • Bottom 50% of population earn <25% of all income

Blue curve = Estimated Creator Economy

  • Top 1% of creators earn >80% of all creator income

  • Bottom 50% of creators earn <1% of all creator income (well below living wage)

Detriments of Inequality

Inequality becomes a problem when success is concentrated to the extent that it stifles innovation and chokes out the existence of a strong middle class.

In the creator economy, if attention is ubiquitously directed toward a few creators, leaving the rest unable to build audience and wealth, and the inflow of new and emerging creators will subside.

In the chart above, the area between grey line and blue curve represents the income inequality for creators. As it is today, the inequality between the top 1% of creators and other creators is far too great. Even top creators recognize this, and some are helping to fund the next generation of creators.

History tells us that extreme wealth inequality at a national level has led to collapse or violent revolutions numerous times. But research and analysis tells us that some degree of inequality is good, and perhaps inevitable in a successful economy.

Benefits of Inequality

Inequality is expected in a capitalist system. People are motivated to achieve greater economic outcomes based on their efforts and sacrifices. If the outcomes were deterministically equal for everyone regardless of their value to society, people would not have the same drive to succeed.

In a sense, capitalistic inequality has a positive effect on society. It rewards those who provide more value for others, and incentivizes each of us to be more productive.

The best in the world at any skill is disproportionately rewarded. At the extremes, the difference maker could be infinitesimally small. The fastest sprinter in the world is fractions of a percent better at running than the 100th fastest. Everyone knows Usain Bolt. No one knows the other person.

This is true for creators as well, whose victory points are often tallied in attention. Attention spent on one thing cannot be spent on another, so consumers would rather watch the best video available on a given topic than all of the rest. This is also why…

Distribution Platform Dynamics lead to Inequality

Platforms measure the success of their discovery systems by metrics that are meant to be a proxy signal that users are finding and consuming content they enjoy.

So discovery mechanisms on platforms are decoupled from creator success. The discovery engine only cares about the engagement and satisfaction of consumers.

A common signal used by these systems is how others have engaged with a piece of content. For instance, if 1M others (whose consumption patterns are like yours) already watched, liked, and commented on a video, the system is much more certain that you will too, compared to a video with low or no user engagement. This can lead to the “rich gets richer” phenomenon.

If the system predicts that more time can be garnered by recommending the same 1 video to 10M people than recommending 10M different videos to 10M people, it will show the same 1 video. This isn’t hypothetical, it is the reality of platforms today.

Note: Tik Tok is an exception in some ways, as its algorithm (for now) heavily favors showing fresh, new content to give everything a chance to become a hit.

Why is inequality okay for platforms, and perhaps even important to grow the creator economy?

Inequality has drawbacks, but it creates the outlier winners, which motivates others.

Gaming and content creation are mainstream partly because of success stories like those of Ninja and Casey Neistat. People want to be Like Mike, not GenericGirl13.

As long as there are superstar creators, the dream is alive and new creators will enter the content creation world. If there are no superstar creators, the next generation will have none to look up to, and interest in this career path may fade.

As for platforms, the primary revenue stream is advertising. As long as advertisers receive targeted attention at scale to drives awareness, consideration, purchase, they’ll happily pay. Therefore, platform incentive is aligned with maximizing the overall attention that can be monetized through ads.

So as far as the system is concerned, “rich gets richer” is not an issue. If platforms produce more attention with outrageous success for the top 0.1% of creators than with moderate success for the top 20% of creators, the path with more attention wins.

If top creators are so successful, wouldn’t losing them pose a risk to platforms?

Every platform wants to keep their top talent. But as long as not all top creators leave together (Vine), creator departures aren’t showstoppers. That’s why platforms have little fear of amplifying the Economics of Superstars.

A recent point of reference is the live streamer bidding craze of 2019, when dozens of creators signed new lucrative deals with minimum guarantees — deals structured like star athlete contracts — for exclusive partnerships, meaning the creator can only live stream to one particular platform.

Among the streamers who signed deals with new platforms were Ninja and Shroud, two of the top 10 Twitch streamers. They defected to Mixer, and set off ripples that shook the live streaming industry as everyone looked on with the same curiosity: “Is this the end of Twitch?”

Months after the streamers’ departure, it was clear that Twitch wasn’t going anywhere. Shroud and Ninja didn’t deliver the viewers and momentum Mixer needed. Mixer has since shuttered its business, and Ninja and Shroud both returned to streaming on Twitch after collecting their $15+ million checks.

This sequence of events signaled to other platforms that if they have enough momentum, and a wide enough selection of quality content, the platform is what consumers form habits around, not individual creators.

While Shroud and Ninja were gone, it’s almost as if the hole they left on Twitch was quickly filled by other streamers, and this should set off alarms in every creator’s head to plan a transition from renting to owning their relationship with their audience.

Another example is Joe Rogan’s $100M dollar departure to Spotify, which had no noticeable impact to YouTube’s business despite JRE’s massive popularity.


Keeping in mind how platforms make money (maximize monetizable attention), we see why they may not view uneven distribution of creator success as a problem.

But let’s assume for a minute that platforms are open to change this. What options can they consider to help small creators while delivering business results?

Adjust relative creator payouts

The extreme option to consider is to create an even distribution of creator payouts.

Let’s play out this scenario with YouTube, which offers the most creator payout of any platform. In the past 3 years, YouTube paid out $30B (80% of its revenue) to creators and publishers. That averages out to $834M per month, huge right?

If we estimate roughly 40M active YouTubers, that $834M comes to $20.85 per creator per monthAn annual income of $250 per creator. Even 50x that amount would be below the U.S. poverty line.

Additionally, if creators generate unequal value but get equal income, top creators would lose motivation (to put it lightly).

Through its public earnings, it’s clear that YouTube can’t support this many full-time creators. If YouTube’s creator revenue were distributed more evenly, the top creators would get much less, leaving them no reason to try as hard on the platform since better performance doesn’t translate to better rewards.

There is a middle ground here, which is to lower the relative payouts to top creators only beyond a certain earning threshold, and use that money to benefit emerging creators instead. This requires a change in platform incentive structure, and could mirror a tax system that progressively increases the “tax” as creators earn more.

Setting aside consistency issues and top creator perception problems, if re-investing in the next generation of creators can yield better long term profit for the platforms than the current payout model, then it is a worthwhile exploration that could also help reduce uneven distribution.

Use company profits to help small creators

Besides existing creator & publisher payouts, this is the other place money can come from to reduce inequality and subsidize aspiring creators.

As stated above, YouTube is already paying 80% of its revenue to creators and publishers. Assuming other platforms are in a similar boat, these companies would need to justify to their board of directors and shareholders how a smaller profit margin today will fuel its growth trajectory tomorrow. It’s not impossible, but an answer is required for this to be a viable path.

The crux of this direction is that most creators simply won’t become top creators, and so funding the creative endeavors of all aspiring creators would likely result in net negative financial outcomes for platforms.

This idea becomes appetizing to platforms if it creates business value, for example:

  1. The next wave of top creators are born on the platform out of a grant for aspiring creators.

  2. Existing creators stick with the platform more as they grow because of a subsidy for emerging creators.

  3. Public sentiment drastically improves for the platform as a result of its attention toward the next generator of creators, leading to more usage.

To be clear, platforms have not thrown in the towel on helping new creators. In the near term, companies including Pinterest, Tik Tok, and Snap are leaning on creator funds to kickstart the journey for new creators who show potential.

The results from these funds will inform the platforms’ long term strategy as they adjust their monetization machine to adapt to the next generation of creators. Perhaps one day, some form of Universal Creator Income could exist that benefits creators, consumers, and platforms.

Closing Thoughts

Today, the creator economy is extremely top heavy, with 80%+ of the value going to the top 1% of creators. History tells us that extreme wealth disparity over a long time leads to revolution and systemic collapse. For the creator economy to have longevity, more creators need a path toward achieving meaningful financial outcomes.

This means we need to carve out room for a strong creator middle class, which Li Jin presented sound arguments for. I support this, and believe there is immense value in enabling more mid-sized creators to succeed. However, it’s unlikely that this creator segment will thrive on platforms under their current structure.

Distribution platforms have their hands tied because 1) even the most successful platforms do not generate enough revenue to financially support a higher percentage of creators on the platform, and 2) the incentive structure of an ad-based business model leads platforms to maximize monetizable attention, which may not align well to the success of middle class creators.

I hope existing platforms prove me wrong by earnestly exploring options such as adjusting relative creator earnings, and allocating funds to subsidize new creators who show promise. These initiatives may yield no value for platforms, or they can be the key to the next growth inflection point for platforms and the creator economy.

For now, I’m convinced that distribution platforms will not solve this problem, but new monetization platforms will (future post).


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