Network Effects of Twitter Blue Verification Pricing
Source: https://www.cnbc.com/2022/11/10/poll-will-verified-twitter-users-pay-to-keep-their-blue-checkmarks.html
Following Elon Musk’s acquisition of Twitter, a number of changes came very quickly. One of these is the decision to charge $8/month for a Twitter Blue subscription that would allow any user to have a blue checkmark that previously was only given to celebrities and other well-known figures. This decision resulted in mixed reactions, with some praising the power being given to the people, and some criticizing that this destroys a system that works and there is little incentive to pay for such a service.
According to this article, the primary purpose of the verification in the past was to prevent impersonation of well-known people, and it mostly worked. Under this new system, impersonation could increase if anyone can pay to be verified, but Yoel Roth, Twitter’s head of safety and integrity, claims that paid verification is in fact a strong signal to identify a human over a bot or impersonator. The article polled a number of already verified users on Twitter regarding whether they would pay to keep their verification, and they all said no. They claimed that Twitter should encourage verification rather than add a tax on it. Additionally, the article shows a poll done on Twitter asking regular users if they would pay to be verified. Out of over 2 million votes, 81.5% of respondents would not pay to be verified through Twitter Blue. Overall, the new Twitter Blue product has little support, and by extension, Twitter itself now has many opposers due to these decisions.
We can connect to the course material by considering the network effects of Twitter and Twitter Blue. In this case, the product is a Twitter Blue subscription at $8/month, so we can say that p=8. Consumers can be represented as real numbers from 0 to 1, where the consumers are all of the users of Twitter. The reservation price for a consumer x when a z fraction of Twitter users purchase Twitter Blue can be represented as r(x)f(z). We do not know the exact form of these functions, but we can assume a general parabolic form when graphing r(z)f(z).
Now, the current value of z is the percent of Twitter users that were already verified before this change, which is very few as it is only given to well-known users. A quick search shows that less than 1% of users are currently verified, so we can set a conservative value of z=0.01. Now, under this new model, even most of those 0.01 users don’t want the new Twitter Blue, meaning their reservation price is below 8. This means that they have verification, but don’t want it under the new model, meaning demand will decrease over time. With a current z value as low as 0.01, we can relatively safely assume that this value is between the equilibrium values of 0 and whatever z’ is. We know from the course material that when z is between 0 and z’, z will decrease over time as it tends towards the equilibrium of 0. Thus, the implementation of this new program seems to be pointing to fewer subscribers of Twitter Blue and thus fewer verified users when we analyze it under our network effects model. So, we see that Elon Musk’s plan to boost revenue through a paid product might backfire after all.