Evolution of the Freemium Pricing Model

Ryan Gosha
5 min readMar 23, 2024

If you spend time on social media and streaming services, you will likely notice that almost all social media platforms and streaming platforms increased their ad-rendering frequency in the last 6 months.

It's a hostage situation: pay up or else we will inundate you with ads.

  • X (formerly Twitter) now renders an ad for every 4 tweets you scroll through. This is true for me. It’s possibly true for other non-paying users. Make the free version unusable so that anyone who wants to use X regularly pays for it.
  • Peacock renders 3 or 4 ads in one go, all of them irrelevant. Watching one of the Resident Alien episodes there, I almost thought they knew of some medical issue that I have that I am not yet aware of, because the number of chronic condition drug ads they rendered was just too high.
  • YouTube twitched its algorithm this year to the point of unusability. It makes you wish for a return to the era of downloading all the videos you want to watch and creating a playlist on the good old VLC media player.
  • Facebook has gotten worse (I am told) but it has always been a cesspool of irrelevant ads.
  • Amazon Prime Video is headed the same route. Pay for it, or else we will show you an unbearable number of ads (one after the other).

Almost all of them have changed their algorithm settings to render more ads. All of them at once — it's too much of a coincidence. There must be a Strategy Consulting firm behind this, advising all of them to implement the same strategy to maximize profits.

The Freemium Business Model with regards to pricing has been around for a long time, since the beginning of the internet. You have one version of the product/service offering to paying clients and another version to non-paying clients. The payers get a better version, more features, unlimited usage, etc. The non-payers don't get the extra benefits. That has always been the case. The extra benefits are a positive reinforcement that incentivizes non-payers to pay.

The newfound version has a twist to it. It doesn’t dangle a carrot. It uses a stick to punish you for being a non-payer. The new version only works for social media and streaming services, because they have network effects.

The stick is the number of ads you are rendered. If you pay, good job son, you don't get ads. If you don't pay, we will render an excessive number of ads to you, naughty child. This other time I asked myself, “What am I doing, I am just sitting here watching ads, I should just pay more”. I almost paid for the premium version, but then my sense of fairness (justice warrior) kicked in telling me not to do it, because that's exactly what they want you to do, you are better off quitting, and that's what they don't want you to do.

Is this Sustainable?

We are left to wonder. If you push the non-payers to the edge, you can easily mess it up. Another tightening of the screw will result in some non-payers exiting. For example, if X increased their ad-rendering to me from an average of 1 ad for every 4 tweets to 1 ad for every 3 tweets, I would quit. The number doesnt have to be an integer, it's an average. 1 ad for every 3.6 tweets will probably have me quitting as well. Also, my tolerance level is not constant. On a moody day, I could just quit.

Once I declare that X has evolved into a cesspool of irrelevant ads no longer worth watching I will quit. At some point, every other non-paying user will have to make that decision. The problem is not affordability. The challenge is the sense of fairness that users have ingrained in their minds. We have been accustomed to free social media. We know that these companies make money from rendering ads and selling our data. That is the reason why we are annoyed at paying.

What's the sweet spot between users quitting en-masse and users staying? It's a tight balancing act.

You are balancing the short-term need to maximize profits vs the long-term need to retain users.

As we know, for most listed companies, the short-term goal always wins. It gets prioritized over the long term.

The pressure for quarterly performance comes from the equity markets. As such, it is highly unlikely that tech leaders would reverse these highly profitable short-term moves.

The Enshittification of Social Media Platforms that Cory Doctorow spits continues. Cory is point-on, except for the unquittable remark. At some point, at the edges, users will quit. It will simply be not worth it.

Three-Way Optimization

The platform companies know that at some point, you will quit after being overwhelmed by the stick. They have a dashboard with metrics to monitor this. The overall goal is profit maximization. The means is via revenue maximization. They have two sources of revenue; subscriptions and ad revenues

The secondary goal is enhancing or at least maintaining network economics (long-term goal).

The challenges are:

  1. Ad revenues are inversely related to subscription revenues — if more people sign up for the paid ad-free version, ads will be rendered to fewer people, and vice versa.
  2. For a saturated market, Ad revenues are inversely related to network effects. Social media has peaked. We are at the saturation point. If you overload non-payers with ads to an unbearable level, they quit, or they simply become less active on that platform. This reduces your daily Active Users, negatively affecting your network economics. Everyone loses including the payers who now have less reach, less influence, and get less content from people they liked. This only applies to a saturated market. For a growing market, as a marketplace owner, you can get away with some stuff.

In short, you should be optimizing for Maximum Revenues and Sustainable Network Economics.

Optimal State = Maximum Revenues + Sustainable Network Economics

Maximum Rev’s = Maximum Ad Rev + Maximum Subscription Rev

Therefore:

Optimal Eq Point = Max Ad Rev + Max Sub Rev + Sus Network Effects

The guys managing the platforms have chosen to Maximise Ad revenues by rendering punitive ads to force more users to the paid version. The plan sounds good. However, the unintended consequence arising from the complex interactions of these variables is that you can easily trigger a self-perpetuating decline in Network Effects as users flee, which will then lead to lower Ad Revenues, lower subscriptions, and an overall low-value network.

Platforms are betting that they can continuously find the sweet spot.

It's a dangerous balancing act. Is it worth playing? You're risking it all, for what? It could be better to choose a side and stick to it, in terms of the pricing model. Either go a for full subscription model or go for a full ad revenue model. Going for a mix is playing with fire, if network effects are involved.

That is it!

Ciao!

--

--