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The Benjamin Button Economy
Who are the winners in our algorithmically driven economy? Consider a
graph. On the
y
axis is the number of people a company reaches. Facebook
and Google, of course, are in the exclusive billion-plus club. But plenty of
other companies, from Walmart to Twitter to the TV networks, reach
hundreds of millions. On that level, they’re superpowers.
But let’s put “intelligence” on the
x
axis. How much does a company learn
from its customers? What kind of data do these customers provide? How
seamlessly and quickly does it improve the user experience, like auto-
populate your destination on Uber, or suggest songs you’ll like on Spotify?
Over the last five years, only thirteen in the S&P 500 have outperformed the
index each year—evidence of our winner-take-all economy.
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What do most
of these firms have in common? They use the peanut-butter-and-chocolate
combination of receptors (users) and intelligence (algorithms that track usage
to improve the offering).
This is tantamount to a car that becomes more valuable with mileage. We
now have a Benjamin Button class of products that age in reverse. Wearing
your Nikes makes them less valuable. But posting to Facebook that you are
wearing Nikes makes the network more valuable. This is referred to as
“network effects” or “agility.” Not only do users make the network more
powerful (everyone being on Facebook), but also when you turn on Waze,
the service gets better for everyone, as it can geolocate you and calibrate
traffic patterns.
Where should you work or invest? Simple: Benjamin Buttons.
Look back at the graph. In the upper right quadrant are the winners,
including the three platforms: Amazon, Google, and Facebook. Registering,
iterating, and monetizing its audience is the heart of each platform’s business.
It’s what the most valuable man-made things ever created (their algorithms)
are designed to do.
Newspapers can reach millions, and many more if you consider how their
stories pop up on the three platforms. But they gain almost no intelligence
from this contact. Thus, while the three dominant platforms—search,
commerce, and social—know me upside down, the
New York Times
has only
skeletal details, starting with my address and zip code. It might know I lived
in California most of my life. But maybe not. It might try to keep track of my
vacation schedule. It sees the stories I read and share, but it’s an algorithm
targeting a cohort, not a feed-based platform designed specifically for me.
Facebook’s algorithm can be used to microtarget distinct populations in
specific geographic areas. An advertiser can say, “Give me all the millennial
women around Portland looking to buy a car.” Using data mined from the
social media accounts of millions of Americans, Cambridge Analytica, a data
firm that worked on Brexit and on the Trump campaign, created a
“psychographic profile” of voters ahead of the 2016 election. The company
used behavioral microtargeting to deliver specific pro-Trump messages that
resonated with specific voters for highly personal reasons.
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With knowledge
of 150 likes, their model could predict someone’s personality better than their
spouse. With 300, it understood you better than yourself.
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Like the rest of traditional media, the
Times
let Google handle its search
function—until it realized too late its mistake. And so, compared to
Facebook, the
Times’
knowledge of me, a fifteen-year subscriber, remains
bare bones. TV stations know even less. For the twenty-first century, they’re
remarkably dumb. And judging by this scheme, dumb companies correlate
closely to losers. They were paid to be dumb, as data could have helped
advertisers determine which 50 percent of their advertising was wasted and
reduce spend.
Some digital companies also lag. Twitter, for example, doesn’t know much
about its customers. Millions of them have fake names, and as many as 48
million (15 percent) are bots.
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The result is that while the company can
calculate changing moods and appetites in different areas of the planet, it
struggles to target individuals. It aces humanity but gets a C in humans. This
is the reason Twitter’s relevance, similar to Wikipedia or PBS, will always
outpace its market value. Good for the planet, bad for Twitter shareholders.
No company is higher or farther to the right on this chart than Facebook. It
crushes on both reach and intelligence. This power gives it a huge edge in the
digital world. Facebook has access to quinine in a mosquito-infested market
—digitally savvy talent. Smart people want to work at a dominant company
that they think gets it. Its prospects are bright, opportunities everywhere.
There are interesting problems to solve, and ridiculous amounts of money in
play. Few firms had the stones, or firepower, to drop $20 billion on a five-
year-old company, WhatsApp.
At L2, we track migration patterns between the largest firms, including
traditional agencies and the Four. WPP is the world’s largest advertising
group. Some 2,000 of its former employees have migrated to Facebook or
Google. By comparison, only 124 former Facebook or Google peeps left to
go work at WPP.
Consider the reverse migrants—124 that went back to WPP. Many of
them, it turns out, had only interned at Facebook or Google, and went to WPP
when they weren’t extended offers in Palo Alto or Mountainside.
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The ad
world today is increasingly run by the leftovers.
This underscores the dominance of the digital giants. It’s not just that their
machines are getting smarter, day by day, as they gorge on our data. They
attract the best and brightest. Just look at the infamous gauntlet of
intelligence tests that America’s job seekers are willing to put themselves
through for a job at Google. Getting hired at Facebook is no less difficult, just
less publicized.
L2 Analysis of LinkedIn Data.
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