According to CNBC, Facebook made $7.89 in revenue per average global user in the 3rd quarter last year (with a high of $39.63 in the US and Canada, and a low of $2.22 outside US, Canada, Europe and Asia-Pacific).
According to Yahoo! Finance and my calculation, if its expenses in the same quarter were $13.4 billion, expense per user was $13.4 / $21.5 * $7.89 = $4.92 on average (proportionally allocated given expense / revenue ratio).
Revenue per user is obviously quite different in different parts of the world, but what about costs? It seems to me that on a per-user-basis, selling and serving all those ads in the US and Canada that led to so much revenue per user is probably more expensive, compared to some places that have less commerce. But as dramatically different as $39.63 and $2.22 on the revenue side? I don’t think so. Not even close.
In other words, users in the rest of the world at $2.22 of revenue per user are almost certainly not profitable. Even if expenses there were only half of average, it would still not be enough.
Of course these numbers are averages across the regions, and chances are that the differences between users within one region are also quite striking. I don’t have numbers on those. But I would bet that some users in the US and Canada also bring in less revenue than the $4.92 in average cost per user.
Who would those unprofitable users be in the US, say? Well, those demographics and those neighborhoods in the social graph in which advertisers see little opportunities to make a sale, because, for example, everybody is unemployed and angry.
(So if, for example, a certain presidential campaign came by and wanted to specifically target this demographic with political ads … I for one can vividly imagine the leap of joy of some Facebook business guy who finally saw how to get promoted: “I turned a million users from being a cost center to being a profit center”. And democracy be damned. Of course, I’m speculating here, but directionally I don’t think I’m wrong.)
Which suggests another strategy to unseat Facebook as the dominant social network: focus on picking off the users that generate the most revenue for Facebook, as they subsidize the rest. If that relatively small subset of users jumped ship, the rest of the business would become unprofitable.
(I jotting this down because I hadn’t seen anybody suggest this strategy. We do need to find ways of ending surveillance capitalism after all.)
Let’s take Whatsapp, acquired by Facebook, and Signal, independent. Both apps largely do the same thing (chat), are based on the same technology, and even led/funded by the same guy, Brian Acton (who is funding Signal to atone for his sin of selling Whatsapp to Facebook according to this article).
Here are screen shot shots of the privacy implications of both apps, according to the excellent disclosures now required by Apple:
If this doesn’t convince you to use Signal over Whatsapp, and that touching anything that Facebook does is a high-risk activity, I don’t know what will.
Newsweek has the story:
The latest data from the Census Bureau’s Household Pulse Survey, taken between November 25 and December 7, found that 35.3 percent of U.S. adults are “living in households not current on rent or mortgage where eviction or foreclosure in the next two months is either very likely or somewhat likely.”
More than one third of adults.
Washington D.C. holds the record with 67.3% in this survey.
Can you imagine a third of all adults being evicted? Or two thirds in DC? I don’t think that is possible, because wouldn’t they have to move into the apartments and houses of other people being evicted, in a grand game of musical chairs? And if they indeed were evicted, with a third of the population suddenly homeless, the real estate market would totally collapse, and that wouldn’t make landlords happy either. So I would expect some kind of compromise to be found because it’s in the interest of renters and landlords, buyers and lenders.
But if you are in danger of being evicted, it means that you are basically wiped out financially. Risking the roof over your head, or any roof over your head, is not something anybody does easily.
But we are nowhere done with COVID-19. We may have made it into the second half of the pandemic, but not by much: vaccination has only started, and is supposed to continue into the summer. So if by now 35% of people are wiped out, what about, say 6 months from now?
And even if they somehow make it, and we beat back the virus, how are 35% of people, or more by the summer, ever supposed to financially recover? Just the accumulated debt would take years to pay off even with good jobs. Which are in short supply, and shorter supply now given the impact the pandemic is having on even further worsening inequality.
Many have been wondering why there aren’t more people on the streets, demanding a proper government response. They simply may not because a pandemic is going on. Once the threat from the virus recedes, however, there may be a very hot summer.
The annual MyData conference is starting in just a few hours. Thanks to COVID, I don’t have to get on an airplane to Helsinki!! They instead use QiQoChat, a conference wrapper around Zoom. See you there? (You can still get tickets.)
I’ll be speeaking in the following sessions:
Thursday, Dec. 10, 2:45pm pacific (22:45 UTC).
Thursday, Dec. 10, 4:30pm pacific (Friday 0:30 UTC).
MyData Governance Interoperability Landscape. I’ll be moderating this international panel with panelists Matthias De Bievre (France), Nat Sakimura (Japan), Joni Brennon (Canada), Harshvardahn Pandit (Ireland), Paul Knowles (Switzerland), Antti “Jogi” Poikola (Finland) and Mark Lizar (Canada).
Friday, Dec. 11, 2:45pm pacific (22:45 UTC).
This is going to be fun! And a great kickoff for 2021, which I think will become Year 1 of the user-controlled personal data revolution.
My friend Doc Searls has been talking about this book repeatedly in recent months, as have many others interested in rolling back surveillance capitalism, improving privacy and user agency, and cleaning up the unholy mess that on-line advertising has become. Finally I have read the book, and here are a few notes.
Tim Hwang makes three core points:
- Programmatic, on-line advertising is fundamentally, irredeamably broken.
- It’s not a matter of whether it will implode, but just when.
- Apply the lessons from the 2018 subprime mortgage crisis: advertising inventory is a different asset class, but the situation is fundamentally the same: eroding fundamentals in the face of an opaque, overhyped market, which will lead to a crash with similarly major consequences when it occurs.
I buy his first point. I mostly buy his second, but there are too many important differences with the market for collateralized mortgages in 2008 for me to buy his third. Ultimately that parallel isn’t that important, however: if he’s right that programmatic on-line advertising is headed for something dramatic, whether it’s like 2008 subprime mortgages or some other crash doesn’t matter in the end.
Why would anybody say programmatic, on-line advertising is broken? He has many examples, go read the book, but let me mention my personal favorite from personal experience: ads, to me, on Spotify:
Spotify, for a long time, advertised joining the Marine Corps to me. I should be flattered how young, vigorous, and gung-ho they consider me, but hmm, I don’t think so. This must be because they have some wrong data about me, and while Spotify got the Marine Corps' money all the same, the Marine Corps totally wasted their spend.
While this example is particularly egregious, Hwang has many other examples, which argue that this is a major and pervasive problem.
I recently downloaded the personal data Spotify have about me, as I can because we have the CCPA in California. Looking at the advertising subjects they have tagged me with, guess what?
It was worse than I was afraid of. I loaded the tags into a spreadsheet, and categorized them into three groups:
Interests I definitely have. Example: “Computers and software high spender”. Guilty as charged.
Interests I definitely do not have. Example: “March Madness Basketball Fan”. What? Never watched basketball in my life. I don’t actually know what “March Madness” might even be and I’m disinclined to look it up.
Interests that I might or might not have, Meh so to speak. Example: “Vitamin C category purchasers”. Maybe I bought some one day. I don’t remember.
How do you think these categories break down? The majority (30/66, almost half) of tags Spotify has about me is in the Meh category. Will I buy more Vitamin C if they advertise it to me? Maybe, but quite unlikely. Consider the ad spend money in this category mostly wasted on me.
But this is the kicker: 24 of the remaining tags were “definitely not” and only 12 were “definitely yes”. Twice as many categories about me were absolutely wrong as were correct!!
Only 18% of the total categories were clearly correct, and worth spending ad money on to target me.
From the name of the tags in the Spotify export, I guess most of them were purchased from third parties. (Makes sense: how would Spotify know I’m interested in Vitamin C, or not?) In other words, 18% of the data they purchased about me was correct, 36% incorrect, and the rest more or less random. No wonder Hwang immediately thinks of junk mortgage bonds with numbers like these.
But as he points out, advertisers keep spending money, however. Why? I suggest the answer is very simple: because of a lack of alternatives.
If you stop advertising on-line, what are you going to do instead? As long as there isn’t a better alternative, it’s a better plan to pinch your nose and go to your CEO and say, yes, I know that today, not just half but a full 82% of our advertising money is wasted, but it’s better to waste all that money than not to advertise at all. I can understand that. Terrible, but reality.
So, for me, the more interesting question is: “How can we do better?” And I think the times are getting ripe for doing something better… stay tuned :-)