The Trillion Dollar Scam - How Google Really Makes Money
By FortNine
Summary
## Key takeaways - **Google's PageRank: The Foundation of Search**: Google's PageRank algorithm revolutionized search by mathematically sorting web pages based on their link structure, ensuring relevant results and preventing irrelevant content from dominating searches. [01:04] - **The Toothbrush Test: Google's Original User Focus**: Google's initial success was attributed to the 'toothbrush test,' meaning they created a product useful twice a day, like brushing teeth, that genuinely improved users' lives. [02:03] - **Spy Pixels: The Invisible Ad Tracker**: Spy pixels, often unseen, track user interactions with ads by requesting information from servers, allowing Google to claim credit for ad views even if the user merely scrolled past. [02:48] - **JavaScript Pixels: Deeper User Tracking**: Modern tracking involves JavaScript pixels installed on websites, which send detailed user behavior data to Google Analytics, enabling precise customer profiling. [03:03] - **Advertising as Inference, Not Influence**: Google's advertising model has shifted to 'inference,' predicting purchases based on vast data, rather than 'influence,' actively persuading customers, leading to inflated success claims. [06:34] - **Ghost Ads Expose Google's Predictive Flaws**: Promoting non-existent pages (404 errors) and still getting credited with sales reveals Google's algorithm often attributes conversions that would have happened regardless of the ad. [06:09]
Topics Covered
- Google's Ad Model Fails Its Own "Toothbrush Test."
- Is Google's Ad Model a Trillion-Dollar Scam?
- Modern Ads: Inference, Not Influence.
- Why Don't Marketers Challenge Ad Attribution?
Full Transcript
Hello, I'm Ryan F9 and this is a
bicycle. Bicycles are for children and
adults with DUIs, but I'm riding one
today because it might help a buddy of
mine. A buddy on the losing end of a
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So, how does a search engine scam a
trillion dollars? Well, you remember in
1998 the internet was really annoying to
use and you could search for the Stanley
Cup and end up on the personal blog of
some dude named Stanley who sells
dishwear.
So Google's founder wrote the page rank
algorithm. Imagine a tiny internet of
three websites. A links to B, B to C,
and C to A. A random surfer clicking on
random links will have a 33% chance of
landing on each site. So each site has a
page rank of 0.33. But if B links to C
and A, then A must be most important. So
it acquires half of B's page rank, too.
It's a mathematically simple way to sort
the worth of web pages. So page rank can
crawl the internet fast, always
rebuilding its leaderboard so your
search for the Stanley Cup doesn't pull
up something irrelevant like the Toronto
Maple Leafs.
When Larry Pageige won a Maronei prize
for page rank, they said human access to
information hadn't taken such a quantum
leap since Gutenberg built his printing
press. And all Larry said was that he
was happy his company passed the
toothbrush test. That is Google built
something that people can use twice a
day that makes
people's lives better.
Oh no,
what ridiculous stupid machines who
builds these things? But no one foresaw
just how long this tooth touch would be.
5 trillion searches a day is twice a day
for every person on the planet. And that
mega data enables the most profitable
scam in history. Say you need some new
pedals for your little toy here. And the
first thing a company like Fortnite
would do is make an ad for your precious
anglets.
Somewhere on this ad is a transparent
one by one image called a spy pixel.
You'll never see it, but your browser
must still request it from the server
and in doing so share its IP. That's how
Google knows you've scrolled past the ad
side.
>> And nowadays it goes even deeper, Alice.
Pixels are a small piece of JavaScript
Google gets customers to install on
their own websites. Hit that inspect
network tab and you'll see them firing
off to google analytics.com. What you're
scrolling, when, for how long, on what
browser, reporting more than enough data
for Google to say when you go to forand
buy your trinkets, this is my customer.
They saw my ad, I earned my pay. That
type of advertising makes up 75% of
Google's billions. It's 98% of Meta's
revenue. What a doozy of a duopoly. And
I have no inherent problem with selling
the ad space between the titties on your
Instagram feed. Except it doesn't work
like that anymore. Nowadays, people
think in search queries. Google knows
your pedals are wearing out. They know
about the crank brothers shoes on your
feet. They know where you live. They
know you've been creeping that pedal
page you pedal file. They know you
bounced when you saw the looney 250
looney price tag. But they know you're a
55-year-old dentist who gets paid in one
week and they're guessing you'll be
back. So, here is the scan. Now,
sometime over the next few days, you'll
be watching a mountain biking video, and
you won't even notice the banner ad for
those pedals that you were planning to
buy.
But since your browser loaded the spy
pixel, Google gets credited with the
sale when you do.
The customer didn't discover a product
that they hadn't already chosen, and the
company didn't gain a customer that they
didn't already have. Google just
predicted who was about to buy, then
showed them an ad at the last minute.
It's the digital equivalent of handing
out flyers in the checkout line, then
claiming success when people pay for
their carts 2 minutes later.
Phew. That's how Google makes most of
their revenue. And that's a failing of
their own toothbrush test. Doesn't make
anyone's life better, just makes money.
We can prove this in a few ways. An
expensive option is to massively upscale
the spend on a campaign and watch the
conversions drop off a cliff, indicating
Google had false success, showing your
ad to people who were already predicted
to be in tomorrow's customer list, but
could not convert when forced to cold
call a larger group. The [ __ ] is that?
But let's put some real numbers on it
with, ironically, Google's own tool. Say
Montreal sells 50 helmets one day,
Ottawa sells 20. Over time, their causal
impact tool can learn to extrapolate
Ottawa's data to predict Montreal's. So,
when we run ads in Montreal and
purposely keep Ottawa dark, we can see
the difference the ads actually made. In
such a test, Google claimed to generate
4,74
sales. But subtract the predicted sales
from our fictitiously adless Montreal
and we get 160. meaning Google took
credit and got paid for 4,544
sales that would have happened anyway.
One final spooky proof is to run ghost
ads. Pay to show people empty boxes,
then watch as Google claims customer
acquisitions from that blank rectangle.
My buddy once accidentally promoted a
404 page that generated 73 sales. how
Google is using their mountain of data
to show ads to people who are already
about to buy.
To quote my anonymous
marketing guru, that's advertising as
inference, not influence. And if that
sounds like a subtle difference, the
half trillion dollars that it brings in
every year is not.
Of course, there are some real new
conversions mixed in with the preach to
choir, but Google and Meta's blackbox
attribution algorithms ain't going to
tell you which is which. And that's
precisely how it's possible to scam such
a large amount of money because the
victims are precisely the people who
would want to believe that it's all
good. What marketing manager is going to
look at a long list of advertised sales
and not go, "Damn, my campaign's working
great. I'm a genius." And what marketing
manager is going to spend a bunch of
company money just to show people a
blank ad and prove that they're not a
genius? Well, my buddy did,
and it made for an interesting expose,
even if it didn't make it any easier for
him to advertise the fact that Fort 9
now sells 45,000 mountain bike parts,
accessories, and apparel. Hope this
video helps you, buddy. Links for those
things are down below. Thanks very much
for watching.
stupid ridiculous things.
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Today that makes day.
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Yeah.
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