“Outbreaks have sparked riots and propelled public-health innovations, prefigured revolutions and redrawn maps.” – The New Yorker, April 2020
“Nothing will be the same.”Read More
A new year brings another run at my annual predictions: For 17 years now, I’ve taken a few hours to imagine what might happen over the course of the coming twelve months. And my goodness did I swing for the fences last year — and I pretty much whiffed. Batting .300 is great in the majors, but it kind of sucks compared to my historical average. My mistake was predicting events that I wished would happen. In other words, emotions got in the way. So yes, Trump didn’t leave office, Zuck didn’t give up voting control of Facebook, and weed’s still illegal (on a federal level, anyway).
Chastened, this year I’m going to focus on less volatile topics, and on areas where I have a bit more on-the-ground knowledge — the intersection of big tech, marketing, media, and data policy. As long time readers know, I don’t prepare in advance of writing this post. Instead, I just clear a few hours and start thinking out loud. So…here we go.
So there you have it — 11 predictions for the coming year. I was going to stop at 10, but that Apple/Amazon one just forced itself out — perhaps that’s me wishing again. We’ll see. Let me know your thoughts, and keep your cool out there. 2020 is going to be one hell of a year.
If predictions are like baseball, I’m bound to have a bad year in 2019, given how well things went the last time around. And given how my own interests, work life, and physical location have changed of late, I’m not entirely sure what might spring from this particular session at the keyboard.
But as I’ve noted in previous versions of this post (all 15 of them are linked at the bottom), I do these predictions in something of a fugue state – I don’t prepare in advance. I just sit down, stare at a blank page, and start to write.
So Happy New Year, and here we go.
1/ Global warming gets really, really, really real. I don’t know how this isn’t the first thing on everyone’s mind already, with all the historic fires, hurricanes, floods, and other related climate catastrophes of 2018. But nature won’t relent in 2019, and we’ll endure something so devastating, right here in the US, that we won’t be able to ignore it anymore. I’m not happy about making this prediction, but it’ll likely take a super Sandy or a king-sized Katrina to slap some sense into America’s body politic. 2019 will be the year it happens.
2/ Mark Zuckerberg resigns as Chairman of Facebook, and relinquishes his supermajority voting rights. Related, Sheryl Sandberg stays right where she is. I honestly don’t see any other way Facebook pulls out of its nosedive. I’ve written about this at length elsewhere, so I will just summarize: Facebook’s only salvation is through a new system of governance. And I mean that word liberally – new governance of how it manages data across its platform, new governance of how it works with communities, governments, and other key actors across its reach, and most fundamentally, new governance as to how it works as a corporate entity. It all starts with the Board asserting its proper role as the governors of the company. At present, the Board is fundamentally toothless.
3/ Despite a ton of noise and smoke from DC, no significant federal legislation is signed around how data is managed in the United States. I know I predicted just a few posts ago that 2019 will be the year the tech sector has to finally contend with Washington. And it will be…but in the end, nothing definitive will emerge, because we’ll all be utterly distracted by the Trump show (see below). Because of this, unhappily, we’ll end up governed by both GDPR and California’s homespun privacy law, neither of which actually force the kind of change we really need.
4/ The Trump show gets cancelled. Last year, I said Trump would blow up, but not leave. This year, I’m with Fred, Trump’s in his final season. We all love watching a slow motion car wreck, but 2019 is the year most of us realize the car’s careening into a school bus full of our loved ones. Donald Trump, you’re fired.
5/ Cannabis for the win. With Sessions gone and politicians of all stripes looking for an easy win, Congress will pass legislation legalizing cannabis. Huzzah!!!! Just in time, because…
6/ China implodes, the world wobbles. Look, I’m utterly out of my depth here, but something just feels wrong with the whole China picture. Half the world’s experts are warning us that China’s fusion of capitalism and authoritarianism is already taking over the world, and the other half are clinging to the long-held notion that China’s approach to nation building is simply too fragile to withstand democratic capitalism’s demands for transparency. But I think there may be other reasons China’s reach will extend its grasp: It depends on global growth and optimistic debt markets. And both of those things will fail this year, exposing what is a marvelous but unsustainable experiment in managed markets. This is a long way of backing into a related prediction:
7/ 2019 will be a terrible year for financial markets. This is the ultimate conventional wisdom amongst my colleagues in SF and NY, even though I’ve seen plenty of predictions that Wall St. will have a pretty good year. I have no particular insight as to why I feel this way, it’s mainly a gut call: Things have been too good, for too long. It’s time for a serious correction.
8/ At least one major tech IPO is pulled, the rest disappoint as a class. Uber, Lyft, Slack, Pinterest et al are all expected this year. But it won’t be a good year to go public. Some will have no choice, but others may simply resize their businesses to focus on cash flow, so as to find a better window down the road.
9/ New forms of journalistic media flourish. It’s well past time those of us in the media world take responsibility for the shit we make, and start to try significant new approaches to information delivery vehicles. We have been hostages to the toxic business models of engagement for engagement’s sake. We’ll continue to shake that off in various ways this year – with at least one new format taking off explosively. Will it have lasting power? That won’t be clear by year’s end. But the world is ready to embrace the new, and it’s our jobs to invest, invent, support, and experiment with how we inform ourselves through the media. Related, but not exactly the same…
10/A new “social network” emerges by the end of the year. Likely based on messaging and encryption (a la Signal or Confide), the network will have many of the same features as the original Facebook, but will be based on a paid model. There’ll be some clever new angle – there always is – but in the end, it’s a way to manage your social life digitally. There are simply too many pissed off and guilt-ridden social media billionaires with the means to launch such a network – I mean, Insta’s Kevin Systrom, WhatsApp’s Jan and Brian, not to mention the legions of mere multi-millionaires who have bled out of Facebook’s battered body of late.
So that’s it. On a personal note, I’ll be happily busy this year. Since moving to NY this past September, I’ve got several new projects in the works, some still under wraps, some already in process. NewCo and the Shift Forum will continue, but in reconstituted forms. I’ll keep up with my writing as best I can; more likely than not most of it will focus the governance of data and how its effect our national dialog. Thanks, as always, for reading and for your emails, comments, and tweets. I read each of them and am inspired by all. May your 2019 bring fulfillment, peace, and gratitude.
Those of us fortunate enough to have lived through the birth of the web have a habit of stewing in our own nostalgia. We’ll recall some cool site from ten or more years back, then think to ourselves (or sometimes out loud on Twitter): “Well damn, things were way better back then.”
Then we shut up. After all, we’re likely out of touch, given most of us have never hung out on Twitch. But I’m seeing more and more of this kind of oldster wistfulness, what with Facebook’s current unraveling and the overall implosion of the tech-as-savior narrative in our society.
Hence the chuckle many of us had when we saw this trending piece suggesting that perhaps it was time for us to finally unhook from Facebook and – wait for it – get our own personal webpage, one we updated for any and all to peruse. You know, like a blog, only for now. I don’t know the author – the editor of the tech-site Motherboard – but it’s kind of fun to watch someone join the Old Timers Web Club in real time. Hey Facebook, get off my lawn!!!
That Golden Age
So as to not bury the lead, let me state something upfront: Of course the architecture of our current Internet is borked. It’s dumb. It’s a goddamn desert. It’s soil where seed don’t sprout. Innovation? On the web, that dog stopped hunting years ago.
And who or what’s to blame? No, no. It’s not Facebook. Facebook is merely a symptom. A convenient and easy stand in – an artifact of a larger failure of our cultural commons. Somewhere in the past decade we got something wrong, we lost our narrative – we allowed Facebook and its kin to run away with our culture.
Instead of focusing on Facebook, which is structurally borked and hurtling toward Yahoo-like irrelevance, it’s time to focus on that mistake we made, and how we might address it.
Just 10-15 years ago, things weren’t heading toward the our currently crippled version of the Internet. Back in the heady days of 2004 to 2010 – not very long ago – a riot of innovation had overtaken the technology and Internet world. We called this era “Web 2.0” – the Internet was becoming an open, distributed platform, in every meaning of the word. It was generative, it was Gates Line-compliant, and its increasingly muscular technical infrastructure promised wonder and magic and endless buckets of new. Bandwidth, responsive design, data storage, processing on demand, generously instrumented APIs; it was all coming together. Thousands of new projects and companies and ideas and hacks and services bloomed.
Sure, back then the giants were still giants – but they seemed genuinely friendly and aligned with an open, distributed philosophy. Google united the Internet, codifying (and sharing) a data structure that everyone could build upon. Amazon Web Services launched in 2006, and with the problem of storage and processing solved, tens of thousands of new services were launched in a matter of just a few years. Hell, even Facebook launched an open platform, though it quickly realized it had no business doing so. AJAX broke out, allowing for multi-state data-driven user interfaces, and just like that, the web broke out of flatland. Anyone with passable scripting skills could make interesting shit! The promise of Internet 1.0 – that open, connected, intelligence-at-the-node vision we all bought into back before any of it was really possible – by 2008 or so, that promise was damn near realized. Remember LivePlasma? Yeah, that was an amazing mashup. Too bad it’s been dormant for over a decade.
After 2010 or so, things went sideways. And then they got worse. I think in the end, our failure wasn’t that we let Facebook, Google, Apple and Amazon get too big, or too powerful. No, I think instead we failed to consider the impact of the technologies and the companies we were building. We failed to play our hand forward, we failed to realize that these nascent technologies were fragile and ungoverned and liable to be exploited by people less idealistic than we were.
Our Shadow Constitution
Our lack of consideration deliberately aided and abetted the creation of a unratified shadow Constitution for the Internet – a governance architecture built on assumptions we have accepted, but are actively ignoring. All those Terms of Service that we clicked past, the EULAs we mocked but failed to challenge, those policies have built walls around our data and how it may be used. Massive platform companies have used those walls to create impenetrable business models. Their IPO filings explain in full how the monopolization and exploitation of data were central to their success – but we bought the stock anyway.
We failed to imagine that these new companies – these Facebooks, Ubers, Amazons and Googles – might one day become exactly what they were destined to become, should we leave them ungoverned and in the thrall of unbridled capitalism. We never imagined that should they win, the vision we had of a democratic Internet would end up losing.
It’s not that, at the very start at least, that tech companies were run by evil people in any larger sense. These were smart kids, almost always male, testing the limits of adolescence in their first years after high school or college. Timing mattered most: In the mid to late oughts, with the winds of Web 2 at their back, these companies had the right ideas at the right time, with an eager nexus of opportunistic capital urging them forward.
They built extraordinary companies. But again, they built a new architecture of governance over our economy and our culture – a brutalist ecosystem that repels innovation. Not on purpose – not at first. But protected by the walls of the Internet’s newly established shadow constitution and in the thrall of a new kind of technology-fused capitalism, they certainly got good at exploiting their data-driven leverage.
So here we are, at the end of 2018, with all our darlings, the leaders not only of the tech sector, but of our entire economy, bloodied by doubt, staggering from the weight of unconsidered externalities. What comes next?
2019: The Year of Internet Policy
Whether we like it or not, Policy with a capital P is coming to the Internet world next year. Our newly emboldened Congress is scrambling to introduce multiple pieces of legislation, from an Internet Bill of Rights to a federal privacy law modeled on – shudder – the EU’s GDPR. In the past month, I’ve read draft policy papers suggesting we tax the Internet’s advertising model, that we break up Google, Facebook, and Amazon, or that we back off and just let the market “do its work.”
And that’s a good thing, to my mind – it seems we’re finally coming to terms with the power of the companies we’ve created, and we’re ready to have a national dialog about a path forward. To that end, a spot of personal news: I’ve joined the School of International and Public Affairs at Columbia University, and I’m working on a research project studying how data flows in US markets, with an emphasis on the major tech platforms. I’m also teaching a course on Internet business models and policy. In short, I’m leaning into this conversation, and you’ll likely be seeing a lot more writing on these topics here over the course of the next year or so.
Oh, and yeah, I’m also working on a new project, which remains in stealth for the time being. Yep, has to do with media and tech, but with a new focus: Our political dialog. More on that later in the year.
I know I’ve been a bit quiet this past month, but starting up new things requires a lot of work, and my writing has suffered as a result. But I’ve got quite a few pieces in the queue, starting with my annual roundup of how I did in my predictions for the year, and then of course my predictions for 2019. But I’ll spoil at least one of them now and just summarize the point of this post from the start: It’s time we figure out how to build a better Internet, and 2019 will be the year policymakers get deeply involved in this overdue and essential conversation.
It seems like an eternity, but about one year ago this Fall, Uber had kicked its iconic founding CEO to the curb, and he responded by attempting a board room coup. Meanwhile, Facebook was at least a year into crisis mode, clumsily dealing with a spreading contagion that culminated in a Yom Kippur apology from CEO Mark Zuckerberg. “For those I hurt this year, I ask forgiveness and I will try to be better,” he posted. “For the ways my work was used to divide people rather than bring us together, I ask for forgiveness and I will work to do better.”
More than one year after that work reputedly began, what lesson from Facebook’s still rolling catastrophe? I think it’s pretty clear: Mark Zuckerberg needs to do a lot more than publish blog posts someone else has written for him.
And while I’m not much of a fan of the company he’s built, I think Facebook’s CEO can change. But only if he’s willing to truly lead, and take the kind of action that today may seem insane, but ten years from now, just might look like genius. What actions might those be? Well, let’s review.
Admit you have a problem. Yes, over and over and over, Facebook executives have copped a plea. But they’ve never acknowledged the real problem is the company’s core DNA. More often than not, the company plays the pre-teen game of admitting a small sin so as to cover a larger one. The latest case in point is this post-modern gem: Elliot Schrage On Definers. The headline alone says all you need to know about Facebook’s latest disaster: Blame the guy who hired the firm, have him fall on a sword, add a bit of Sandbergian mea culpa, and move along. Nope, this time is different, Facebook. It’s time for fundamental change. And that means….
Submit to real governance. Like Google, Uber, Snap, and other controversial tech companies, Facebook implemented a two-class system of shares which canonizes their founder as an untouchable god, rendering the company board toothless in moments of true crisis (and in appeasement mode the rest of the time). Following Uber’s lead, it’s time for Mark to submit to the governance of the capital markets and abandon his super majority voting powers. He must stand before his board naked and afraid for his job. This and this alone will predicate the kind of change Facebook needs.
Bring in outsiders. Facebook’s core problem is expressed through its insular nature. This is also the technology industry’s problem – an engineer’s determination that every obstacle can be hacked to submission, and that non-engineers are mainly good for paint and powder afterward. This is simply not the case anymore, either at Facebook or in tech more broadly. Zuckerberg must demand his board commission a highly qualified panel to review his company’s management and product decisions, and he must commit to implementing that panel’s recommendations. Along those lines, here are a two major thought starters:
Embrace radical change. Remember “Bringing People Closer Together” and the wildly misappropriated “Time Well Spent“? This was supposedly a major new product initiative to change Facebook’s core mission, designed to shift our attention from what was wrong with the platform – data breaches, the newsfeed, false news and election meddling – to what could be right about it: Community pages and human connection. Has it worked? Let’s just be honest: No. Community doesn’t happen because a technology company writes a blog post or emphasizes a product suite it built for an entirely different purpose. Facebook can’t be fixed unless it changes its core business model. So just do it, already. Which leads to:
Free the data. Facebook has so far failed to enable a truly open society, despite its embrace of lofty mission statements. I’ve written about this at length, so I’ll just summarize: Embrace machine-readable data portability, and build a true, Gates-line compliant platform that is governed by the people, companies, and participants who benefit from it. Yes, actually governing is a messy pain in the ass, but failing to govern? That’s a company killer.
Many brilliant observers are calling for Mark’s head, and/or for the company to be broken up. I’m not sure either of these solutions will do much more than insure that the company fails. What tech needs now is proof that it can lead with bold, high-minded vision that gives back more than it takes. Mark Zuckerberg has the power to do just that. The only question now is whether he will use it.
If you’re read my rants for long enough, you know I’m fond of programmatic advertising. I’ve called it the most important artifact in human history, replacing the Macintosh as the most significant tool ever created.
So yes, I think programmatic advertising is a big deal. As I wrote in the aforementioned post:
“I believe the very same technologies we’ve built to serve real time, data-driven advertising will soon be re-purposed across nearly every segment of our society. Programmatic adtech is the heir to the database of intentions – it’s that database turned real time and distributed far outside of search. And that’s a very, very big deal. (I just wish I had a cooler name for it than “adtech.”)”
But lately, I’m starting to wonder if perhaps adtech is failing, not for any technical reason, but because the people leveraging are complicit in what might best be called a massive failure of imagination.
I’m about to go on a rant here, so please forgive me in advance.
But honestly, who else out there is sick of being followed by ads so stupid a fourth grader could do a better job of targeting them?
Case in point is the ad above. I took this screen shot from my phone this past weekend while I was reading a New York Times article. The image – of a robe Amazon wanted me to buy – was instantly annoying, because I had in fact purchased a robe on Amazon several days before. Why on earth was Amazon retargeting me for a product I just bought?!
But wait, it gets worse! As I perused the next Times article, this ad shows up:
You might think this ad makes more sense. If the dude buys a robe, makes sense to try to sell him a new pair of slippers, no? Well, sure, but only if that same dude didn’t buy a new pair of slippers two weeks ago. Which, in fact, I did just do.
So, yeah, this ad sucks as well. Not only is it not useful or relevant, it’s downright annoying. The vast machinery of adtech has correctly identified me as a robe-and-slippers-buying customer. But it’s failed to realize *I’ve already bought the damn things.*
Is it possible that adtech is this stupid? This poorly instrumented? I mean, are programmatic buyers simply tagging visitors who land on ecommerce pages (male robe intender?) without caring about whether those visitors actually bought anything?
Are the human beings responsible for setting the dials of programmatic just this lazy?
I’ve been a critical observer of adtech over the past ten or so years, and one consistent takeaway is this: If there’s a way for a buyer to cut corners, declare an easy win, and keep doing things they way the’ve always been done, well, they most certainly will.
But why does it have to be this way? Digging into the examples above yields an extremely frustrating set of facts. Consider the data the adtech infrastructure either got *right* about me as a customer, or could have gotten right:
These are just the obvious data points. My mobile ID and cookies, all of which are available to programmatic buyers, certainly indicate a high household income, a propensity to click on certain kinds of ads, a rich web browsing history reflecting a thickly veined lodestar of interest data, among countless other possible inputs.
Imagine if a programmatic campaign actually paid attention to all this rich data? Start with the fact I just purchased a robe and slippers. What are products related to those two that Amazon might show me? Well, according to its own “people who bought this item also bought” algorithms, folks who bought men’s robes also bought robes for the women in their life. Now there’s a cool recommendation! I might have clicked on an ad that showed a cool robe for my wife. But no, I’m shown an ad for a product I already have.
I’ve got a few calls in to verify my hunch, but I suspect the ugly truth is pure laziness on the part of the folks responsible for buying ads. Consider: The average cost for a thousand views (CPM) of a targeted programmatic advertisement hovers between ten cents (yes, ten pennies) to $2. With costs that low, the advertising community can afford to waste ad inventory.
Let’s apply that reality to our robe example. Let’s say the robe costs $60, and yields a $20 profit for our e-commerce advertiser, not including marketing costs. That means that same advertiser is can spend upwards of $19.99 per unit on advertising (more, if a robe purchaser turns out to be a “big basket” e-commerce spender). So what does our advertiser do? Well, they set a retargeting campaign aimed anyone who ever visited our erstwhile robe’s page. With CPMs averaging around a buck, that robe’s going to follow nearly 20,000 folks around the internet, hoping that just one of them converts.
Put another way, programmatic advertising is a pure numbers game, and as long as the numbers show one penny of profit, no one is motivated to make the system any better. I’ve encountered many similar examples of ad buyers ignoring high-quality data signals, preferring instead to “waste reach” because, well, it’s just easier to set up campaigns on one or two factors. Inventory is cheap. Why not?
This is problematic. What’s the point of having all that rich (and hard won) targeting data if buyers won’t use it, and consumers don’t benefit from it? An ecosystem that fails to encourage innovation will stagnate and lose share to walled gardens like Facebook, Google, and others. If the ads suck on the open web (and they do), then consumers will either install ad blockers (and they are), or abandon the open web altogether (and they are).
We can do so much better. Shouldn’t we try?
If Walmart can leverage data tokens to lure Amazon’s best customers away, what else is possible in a world of enabled by my fictional Token Act?
Well, Walmart vs. Amazon is all about big business – a platform giant (Amazon) disrupting an OldBigCo (Walmart and its kin). Over the past two decades, Amazon bumped Walmart out of the race to a trillion-dollar market cap, and the OldCo from Bentonville had to reset and play the role of the upstart. The Token Act levels the playing field, forcing both to win where it really matters: In service to the customer.
But while BigCos are sexy and well known, it’s the small and medium-sized business ecosystem that determines whether or not we have an economy of mass flourishing. So let’s explore the Token Act from the point of view of a small business startup, in this case, a new neighborhood restaurant. I briefly touched upon this idea in my set up post, Don’t Break Up The Tech Oligarchs. Force Them To Share Instead. (If you haven’t already, you might want to read that post before this one, as I lay out the framework in which this scenario would play out.) What I envision below assumes the Token Act has passed, and we’re at least a year or two into its adoption by most major data players. Here we go…
Fresh off her $2,700 win from Walmart, Michelle decides she’s ready to lean into a lifelong dream: Starting a restaurant in her newly adopted neighborhood of Chelsea in New York City. Since moving to the area from California, she’s noticed two puzzling trends: First, a dearth of interesting mid- to high-end dinner spots walking distance from her new place, and second, what appears to be higher-than-average vacancy rates for the retail storefronts in the same general area. It appears to be a buyer’s market for retail restaurant space in Chelsea. So why aren’t new places launching? She read the Times’ piece on vacancies a few years ago (before the Token Act passed) and was left just as puzzled as before – seems like there’s no rhyme or reason to the market.
Michelle wants to start a high end American gastro pub – the kind of place she loved back when she lived in Northern California (she’s fond of Danny Meyers’ Gramercy Tavern, pictured above, but it’s a bit too far away from her new place). She has a strong hunch that such a place would be a hit in her new neighborhood, but she’s not sure her new neighbors will agree.
Now starting a restaurant requires a certain breed of insanity – they say the best way to make a small fortune in the business is to start with a large one. The truth is, launching restaurants has historically been a crap shoot – you might find the best talent, the best designer, and the best location – but if for some reason you don’t bring the je ne sai quois, the place will fail within months, leaving you and your partners millions of dollar poorer.
It’s that je ne sai quois that Michelle is determined to reveal. The tools she will leverage? The newly liberated resources of data tokens.
Before we continue, allow me to draw your attention back to the rise of search, indeed, the very era which begat Searchblog in the early 2000s. Google Adwords launched in 2000, and within a few years, the media world had been turned upside down by what I termed The Database of Intentions. As if by magic, people everywhere could suddenly ask new kinds of questions, finding themselves both surprised and delighted by the answers they received.
A Gates-Line compliant ecosystem quickly developed on top of this new platform, driven by an emerging industry of search engine marketing and optimization. SEO/SEM sprung into existence to help small and medium sized businesses take advantage of the Google platform – by 2006 the industry stood at nearly $10 billion in spend, growing more than 60 percent year on year. Adwords grew from zero to millions of advertisers by connecting to a long tail of small businesses that took advantage of an entirely new class of revealed information: The intents, desires, and needs of tens of millions of consumers, who relentlessly poured their queries into Google’s placid and unblinking search box.
Were you a limo service in the Bronx looking for new customers? It paid huge dividends to purchase Adwords like “car service bronx” and “best limo manhattan.” Were you a dry cleaner in West LA hoping to expand? Best be first in line when customers typed in “best cleaners Beverly Hills.” Selling heavy machinery to construction services in the midwest? If you don’t own keywords like “caterpillar dealer des moines” you’d lose, and quick, to whoever did optimize to phrases like that.
My point is simply this: Adwords was a freaking revolution, but it ain’t nothing compared to what will happen if we unleash data tokens on the world.
Ok, back to Michelle and her new restaurant. Of course Michelle will leverage Adwords, and Facebook, and any other advertising service to help her new business grow. But none of those services can help her figure out her je ne sai quois – for that, she needs something entirely novel. She needs a new question machine. And the ecosystem that develops around data tokens will offer it.
Thanks to her Walmart experience, Michelle has become aware of the power of personal data. She’s also read up on the Token Act, the new law requiring all data players at scale to allow individuals to create machine-readable data tokens that can be exchanged for value as directed by the consumer. After doing a bit of research, she stumbles across a startup called OfferExchange, which manages “Token Offers” on behalf of anyone who might want to query TokenLand. OfferExchange is a spinout from ProtocolLabs, a pioneer in secure blockchain software platforms like Filecoin. It’s still early in TokenLand, so an at-scale Google of the space hasn’t emerged. OfferExchange works more like a bespoke yet platform-based research outfit – the firm has a sophisticated website and impressive client list. It uses Facebook, Twitter, LiveRamp, and Instagram to identify potential token-creating consumers, then solicits those individuals with offers of cash or other value in exchange for said tokens.
Michelle does a Crunchbase search for OfferExchange and sees it’s backed by Union Square Ventures and Benchmark, which gives her some comfort – those firms don’t fund fly-by-night hucksters. And OfferExchange site is impressive – in less than five minutes, it guides her through the construction of an elegant query. Here’s how the process works:
First, the site asks Michelle what her goal is. “Starting a restaurant in New York City,” she responds. The site reconstructs around her answer, showing suggested data repositories she might mine. “Restaurants, New York City,” reads the top layer of a directory-like page. Underneath are several categories, each populated with familiar company names:
And so on – if she wished, Michelle could dig into dozens of categories related to her initial “restaurant New York City” search.
Michelle’s imagination sparks – the kinds of queries she could ask of these services is mind blowing. She could limit her query to people who live within walking distance of her neighborhood, asking her *actual neighbors* for tokens that tell her what restaurants they eat at, when they eat there, the size of their checks, related reviews, abandoned reservations, the works. She might discover that folks like Indian takeout on Mondays, that they rarely spend more than $100 on a meal on Tuesdays, but that they splurge on the weekends. She could discover the percentage of diners in Chelsea who travel more than two miles by car service to eat out at a place similar to the one she has in mind, and what the size of the check might be when they do. She can also check historical average rents for restaurants in her zip code, over time, which will certainly help with negotiating her lease. The possibilities are endless.
Put another way, with OfferExchange’s services, Michelle can litigate the merde out of her je ne sai quois.
This post is getting long, so I’ll stop here and pull back for a spot of Thinking Out Loud. I could continue the story, imagining the process of the token offer Michelle would put out through OfferExchange’s platform, but suffice to say, she’d be willing to pay upwards of $5-20 per potential customer for their data. The marketing benefit alone – alerting potential customers in the neighborhood that she’s exploring a new restaurant in the area – is worth tens of thousands already. And of course, OfferExchange can connect anyone who offers their tokens to Michelle’s new project a discount on their first meal at the restaurant, should it actually launch. Cool!
But let’s stop there and consider what happens when local entrepreneurs have access to the information currently silo’d across thousands of walled garden services like Uber, LoopNet, Resy, and of course Facebook and Google. While better data won’t insure that Michelle’s restaurant will succeed, it certainly increases the odds that it won’t fail. And it will give both Michelle and her investors – local banks, savvy friends and family members – much more conviction that her new enterprise is viable. Take this local restaurant example and apply it to all manner of small business – dry cleaners, hardware stores, bike shops – and this newly liberated class of information enables an explosion of efficiency, investment, and, well, flourishing in what has become, over the past four decades, a stagnant SMB environment.
Is this Money Ball for SMB? Perhaps. And yes, I can imagine any number of downsides to this new data economy. But I also believe the benefits would far outweigh the downsides. Under the Token Act as I envision it, co-creators of the data – the services like Uber, OpenTable, or Facebook – have the right to charge a vig for the data being monetized. Sure, it’d be possible for an entrepreneur to steal customers via tokens, but I’m going to guess the economic value of allowing your customers to discover new use cases for their data will dwarf the downside of possibly losing those customers to a new competitor. Plus, this new competitive force will drive everyone to play at a higher level, focusing not on moats built on data silos, but instead on what really matters: A highly satisfied customer. That’s certainly Michelle’s goal, and the goal of every successful local business. Why shouldn’t it also be the goal of the data giants?
In my last post I imagined a world in which large data-driven platforms like Amazon, Google, Spotify, and Uber are compelled to share machine-readable copies of data to their users. There are literally scores, if not hundreds of wrinkles to iron out around how such a system would work, and in a future post I hope to dig into some of those questions. But for now, come with me on a journey into the future, where the wrinkles have been ironed out, and a new marketplace of personally-driven information is flourishing. We’ll return to one of the primary examples I sketched out in the aforementioned post: A battle for the allegiance – and pocketbook – of one online shopper, in this case, my wife Michelle.
It’s a crisp winter mid morning in Manhattan when the doorbell rings. Michelle looks up from her laptop, wondering who it might be. She’s not expecting any deliveries from Amazon, usually the source of such interruptions. She glances at her phone, and the Ring app (an Amazon service, naturally) shows a well dressed, smiling young woman at the door. She’s holding what looks like an elegantly wrapped gift in her hands. Now that’s unusual! Michelle checks the date – no anniversaries, no birthdays, no special occasions – so what gives?
Michelle opens the door and is greeted by a woman who introduces herself as Sheila. She tells Michelle she’s been sent over by Walmart. Walmart? Michelle’s never set foot in a Walmart store, and has a less than charitable view of the company overall. Why on earth would Walmart be sending her a special delivery gift box?
Sheila is used to exactly this kind of response – she’s been trained to expect it, and to manage the conversation that ensues. Sheila is a college-educated Walmart management associate, and delivering these gift boxes is a mandatory part of her company training. In fact, Sheila’s future career trajectory is based, in part, on her success at converting Michelle into becoming a Walmart customer, and she’s learned from her colleagues back at corporate that the best way to succeed is to be direct and open while engaging with a top-level prospect.
“Michelle, I know this seems a bit strange, but Walmart has identified you as a premier ecommerce customer – I’m guessing you probably have at least three or four packages a week delivered here?”
“More like three or four a day,” Michelle answers, warming to Sheila’s implied status as a premium customer.
“Yes, it’s amazing how it’s become a daily habit,” Sheila answers. “And as you probably know, Walmart has an online service, but truth be told, we never seem to get the business of folks like you. I’m here to see if we might change that.”
Michelle becomes suspicious. It doesn’t make sense to her – sending over a manager bearing gifts? Such tactics don’t scale – and feel like an intrusion to boot.
Sensing this, Sheila continues. “Look, I’m not here to sell you anything. I’ve got this special gift for you from Doug McMillon, the CEO of Walmart. You’ve been selected to be part of a new program we’re testing – we call it Walton’s Circle. It’s named after Sam Walton, our founder, who was pretty fond of the personal touch. In any case, the gift is yours to keep. There’s some pretty cool stuff in there, I have to say, including La Mer skin cream and some Neuhaus chocolate that’s to die for.”
Michelle smiles. Strange how the world’s biggest retailer, a place she’s never shopped, seems to know her brand preferences for skin care and chocolate. Despite herself, she relaxes a bit.
“Also inside,” Sheila continues, “is an invitation. It’s entirely up to you if you want to accept it, but let me explain?”
“Sure,” Michelle answers.
“Great. Have you heard of the Token Act?”
Michelle frowns. She read about this new piece of legislation, something to do with personal data and the right to exchange it for value across the internet. In the run up to its passage, her husband wouldn’t shut up about how revolutionary it was going to be, but so far nothing important in her life had changed.
“Yes, I’ve heard of it,” Michelle answers, “but it all seems pretty abstract.”
“Yeah, I hear that all the time,” Sheila responds. “But that’s where our invitation comes in. Inside the box is an envelope with a code and a website. I imagine you use Amazon…” Sheila glances toward an empty brown box in the hallway with Amazon’s universal smiling logo. Michelle laughs. “Of course you do! I was a huge Amazon customer for years. And that’s what our invitation is about – it’s an invitation to see what might happen if you became a Walmart customer instead. If you go to our site and enter your code, a program will automatically download your Amazon purchase history and run it through Walmart’s historical inventory. Within seconds, you’ll be given a report detailing what you would have saved had you purchased exactly the same products, at the same time, from us instead of Jeff Bezos.”
“Huh,” Michelle responds. “Sounds cool but…that’s my information on Amazon, no? I don’t want you to have that, do I?”
“Of course not,” Sheila says knowingly. “All of your information is protected by LiveRamp Identity, and is never stored or even processed on our servers. You maintain complete control over the process, and can revoke it at any time.”
Michelle had heard of LiveRamp Identity, it was a third-party guarantor of information safety she’d used for a recent mortgage application. She also came across it when co-signing for a car loan for her college-aged daughter.
“When you put that code into our site, a token is generated that gives us permission to compare our data to yours, and a report is generated,” Sheila explained. “The report is yours to keep and do with what you want. In fact, the report becomes a token in and of itself, and you can submit that token to third party services like TokenTrust, which will audit our work and tell you if our results can be trusted.”
TokenTrust was another service Michelle had heard of, her husband had raved about it as one of the fastest growing new entrants in the tech industry. The company had recently been featured on 60 Minutes – it played a significant role in a story about Google’s search results, if she recalled correctly. Docusign had purchased the company for several billion just last year. In any case, Michelle’s suspicions were defused – may as well check this out. I mean, why would Walmart risk its reputation stealing her Amazon data? It was worth at least seeing that report.
Sheila sensed the opening. “The reports are pretty amazing,” she says. “I’ve had clients who’ve discovered they could have saved thousands of dollars a year. And here’s the best part: If, after reviewing and validating the report, you switch to Walmart, we’ll credit your account with those savings – in essence, we’ll retroactively deliver you the savings you would have had all along.”
“Wow. That almost sounds too good to be true!” Michelle says. “But… OK, thanks. I’ll check it out. Thanks for coming by.”
“Absolutely,” Sheila responds. “And here’s my card – that’s my cell, and my email. Let me know if you have any questions.”
Michelle heads back inside and places the gift box on the table next to her laptop. Before opening the box, she wants to be sure this thing is for real. She Googles “Walmart Walton Circle Savings Token” – and the first link is to a Business Insider article: “These Lucky Few Amazon Customers Are Paid Thousands to Switch – By Walmart.” So Sheila wasn’t lying – this program is for real!
Michelle tugs on the satin ribbon surrounding her gift box and raises its sturdy lid. Nestled on straw inside are two jars of La Mer, several samples of Neuhaus chocolates, two of her favorite bath salts, and various high end household items. The inside lid of the box proclaims “Welcome to Walton’s Circle!” in elegant script. At the center of the box is an creamy envelope engraved with her name. Michelle opens it, and just as Sheila mentioned, a URL and code is included, along with simple instructions.
What the hell, may as well see what comes of it. Turning to her laptop, Michelle heads to Walmart.com – for the first time in her life – and enters her code. Almost instantaneously a dialog pops up, informing her that her report is ready. Would she like to review it?
Why not?! Michelle clicks “Yes” and up comes a side-by-side comparison of her entire Amazon purchase history. She notices that during the early years – roughly until 2006 – there’s not much on the Walmart side of the report. But after that the match rates start to climb, and for the past five or so years, the report shows that 98 percent of the stuff she’s bought at Amazon was also available on Walmart.com. Each purchase has a link, and she tries out one – a chaise lounge she purchased in 2014 (gotta love Prime shipping!). Turns out Walmart didn’t have that exact match, but the report shows several similar alternatives, any of which would have worked. Cool.
Michelle’s eye is drawn to the bottom of the report, to a large sum in red that shows the difference in price between her Amazon purchases and their Walmart doppelgangers.
Holy….cow. Michelle can’t believe it. Is this for real? Anticipating the question, Walmart’s report software pops up a dialog. “Would you like to validate your token’s report using TokenTrust? We’ll pay all fees.” Michelle clicks yes, and a TokenTrust site appears. The site shows a “working” icon for several seconds, then returns a simple message: “TokenTrust has reviewed Walmarts claims and your Amazon token, and validates the accuracy of this report.”
Michelle is sold. Next to the $2700 figure at the bottom of her report is one line of text, and a “Go” link. “Would you like to become a founding member of the Walton Circle? We’ll take care of all your transition needs, and Sheila, who’ve you already met, will be named as your personal shopping concierge.”
Michelle hovers momentarily over “Go.” What the hell, she thinks. I can always switch back. And with one click, Michelle does something she never thought she would: She becomes a Walmart customer.
Satisfied, she turns her eyes back to her work. Several new emails have collected in her inbox. One is from Doug McMillon, welcoming her to Walton’s Circle. As she hovers over it, mail refreshes, and a new message piles on top of McMillon’s.
Holy shit. Did Jeff Bezos really just email me?!
Is such a scenario even possible? Well, that question remains unexplored, at least for now. As I wrote in my last post, I’m not certain Amazon’s terms of service would allow for such an information exchange, though it’s currently possible to download exactly the information Walmart would need to stand up such a service. (I’ve done it, it takes a bit of poking around, but it’s very cool to see.) The real question is this: Would Walmart spend the thousands of dollars required to make this kind of customer acquisition possible?
I don’t see why not. A high end e-commerce customer spends more than ten thousand dollars a year online. Over a lifetime, this customer is worth thousands of dollars in profit for a well-run commerce site like Walmart. The most difficult and expensive problem for any brand is switching costs – it’s at the core of the most sophisticated marketing efforts in the world – Ford spends hundreds of millions each year trying to convince customers to switch from GM, Verizon spends equal amounts in an effort to pull customers from AT&T. Over the past five years, Walmart has watched Amazon run away with its customers online, even as it has spent billions building a competitive commerce offering. What Walmart needs are “point to” customers – the kind of people who not only become profitable lifelong buyers, but who will tell hundreds of friends, family members and colleagues about their gift box experience.
But to get there, Walmart needs that Amazon token. Wouldn’t it be cool if such a thing actually existed?
Social conversations about difficult and complex topics have arcs – they tend to start scattered, with many threads and potential paths, then resolve over time toward consensus. This consensus differs based on groups within society – Fox News aficionados will cluster one way, NPR devotees another. Regardless of the group, such consensus then becomes presumption – and once a group of people presume, they fail to explore potentially difficult or presumably impossible alternative solutions.
This is often a good thing – an efficient way to get to an answer. But it can also mean we fail to imagine a better solution, because our own biases are obstructing a more elegant path forward.
This is my sense of the current conversation around the impact of what Professor Scott Galloway has named “The Four” – the largest and most powerful American companies in technology (they are Apple, Amazon, Google, and Facebook, for those just returning from a ten-year nap). Over the past year or so, the conversation around technology has become one of “something must be done.” Tech was too powerful, it consumed too much of our data and too much of our economic growth. Europe passed GDPR, Congress held ineffectual hearings, Facebook kept screwing up, Google failed to show up…it was all of a piece.
The conversation evolved into a debate about various remedies, and recently, it’s resolved into a pretty consistent consensus, at least amongst a certain class of tech observers: These companies need to be broken up. Antitrust, many now claim, is the best remedy for the market dominance these companies have amassed.
It’s a seductive response, with seductive historical precedent. In the 1970s and 80s, antitrust broke up AT&T, ultimately paving the way for the Internet to flourish. In the 90s, antitrust provided the framework for the government’s case against Microsoft, opening the door for new companies like Google and Facebook to dominate the next version of the Internet. Why wouldn’t antitrust regulation usher in #Internet3? Imagine a world where YouTube, Instagram, and Amazon Web Services are all separate companies. Would not that world be better?
Perhaps. I’m not well read enough in antitrust law to argue one way or the other, but I know that antitrust turns on the idea of consumer harm (usually measured in terms of price), and there’s a strong argument to be made that a free service like Google or Facebook can’t possibly cause consumer harm. Then again, there are many who argue that data is in fact currency, and The Four have essentially monopolized a class of that currency.
But even as I stare at the antitrust remedy, another solution keeps poking at me, one that on its face seems quite elegant and rather unexplored.
The idea is simply this: Require all companies who’ve reached a certain scale to build machine-readable data portability into their platforms. The right to data portability is explicit in the EU’s newly enacted GDPR framework, but so far the impact has been slight: There’s enough wiggle room in the verbiage to hamper technical implementation and scope. Plus, let’s be honest: Europe has never really been a hotbed of open innovation in the first place.
But what if we had a similar statute here? And I don’t mean all of GDPR – that’s certainly a non starter. But that one rule, that one requirement: That every data service at scale had to stand up an API that allowed consumers to access their co-created data, download a copy of it (which I am calling a token), and make that copy available to any service they deemed worthy?
Imagine what might come of that in the United States?
I’m not a policy expert, and the devil’s always in the details. So let me be clear in what I mean when I say “machine-readable data portability”: The right to take, via an API, what is essentially a “token” containing all (or a portion of) the data you’ve co created in one service, and offer it, with various protections, permission, and revocability, to another service. In my Senate testimony, I gave the example of a token that has all your Amazon purchases, which you then give to Walmart so it can do a historical price comparison and tell you how much money you would save if you shopped at its online service. Walmart would have a powerful incentive to get consumers to create and share that token – the most difficult problem in nearly all of business is getting a customer to switch to a similar service. That would be quite a valuable token, I’d wager*.
Should be simple to do, no? I mean, don’t we at least co-own the information about what we bought at Amazon?
Well, no. Not really. Between confusing terms of service, hard to find dashboards, and confounding data reporting standards, The Four can both claim we “own our own data” while at the same time ensuring there’ll never be a true market for the information they have about us.
So yes, my idea is easily dismissed. The initial response I’ve had to it is always some variation of: “There’s no way The Four would let this happen.” That’s exactly the kind of biases I refer to above – we assume that The Four control the dialog, that they either will thwart this idea through intensive lobbying, clever terms of service, and soft power, or that the idea is practically impossible because of technical or market limitations. To that I ask….Why?
Why is it impossible for me to tokenize all of my Lyft ride data, and give for free it to an academic project that is mapping the impact of ride sharing on congestion in major cities? Why is it impossible for a small business owner to create an RFP for all OpenTable, Resy, and other dining data, so she can determine the best kind of restaurant to open in her neighborhood? I’m pretty certain she’d pay a few bucks a head for that kind of data – so why can’t I sell that information to her (with a vig back to OpenTable and Resy) if the value exchange is there to be monetized? Why can’t I tokenize and sell my Twitter interactions to a brand (or more likely, an agency or research company) interested in understanding the mind of a father who lives in Manhattan? Why can’t I tokenize and trade my Spotify history for better recommendations on live shows to see, or movies to watch, or books to read? Or, simply give it to a free service that’s sprung up to give me suggestions about new music to check out?
Why can’t an ecosystem of agents, startups, and data brokers emerge, a new industry of information processing not seen since the rise of search optimization in the early aughts, leveraging and arbitraging consumer information to create entirely new kinds of businesses driven by insights currently buried in today’s data monopolies?
Such a world would be fascinating, exciting, sometimes sketchy, and a hell of a lot of fun. It’d be driven by the individual choices of millions of consumers – choosing which agents to trust, which tokens to create, which trades felt fair. There’s be fails, there’d be fraud, there’d be bad actors. But over time, the good would win over the bad, because the decision making is distributed across the entire population of Internet users. In short, we’d push the decision making to the node – to us. Sure, we’d do stupid things. And sure, the hucksters and the hustlers would make short term killings. But I’ll take an open system like this over a closed one any day of the week, especially if the open system is governed by an architecture empowering the individual to make their own decisions.
It’s be a lot like the Internet was once imagined to be.
I’ve been noodling on such an ecosystem, and I’m convinced it could dwarf our current Internet in terms of overall value created (and credit where credit is due, The Four have created a lot of value). It’d run laps around The Four when it comes to innovation – tens of thousands of new companies would form, all of them feeding off the newly liberated oxygen of high quality, structured, machine readable data. Trusted independent platforms for value exchange would arise. Independent third party agents would munge tokens from competing services, verifying claims and earning the trust of consumers (will Walmart really save you a thousand bucks a year?! We can prove it, or not!). Huge platforms would develop for the processing, securitization, permissioning, and validation of our data. Man, it’d feel like…well, like the recumbent, boring old Internet was finally exciting again.
There’s no technical reason why this world doesn’t exist. The progenitors of the Web have already imagined it, heck, Tim Berners Lee recently announced he’s working pretty much full time on creating a system devoted to the foundational elements needed for it to blossom.
But until we as a society write machine-readable data portability into law, such efforts will be relegated to interesting side shows. And more likely than not, we’ll spend the next few years arguing about breaking up The Four, and let’s be honest, that’s an argument The Four want us to have, because they’re going to win it (more money, better lawyers, etc. etc.). Instead, we should just require them – and all other data services of scale – to free the data they’ve so far managed to imprison. One simple new law could change all of that. Shouldn’t we consider it?
*In another post, I’ll explore this example in detail. It’s really, really fascinating.
Yesterday, I lost it over a hangnail and a two-dollar bottle of hydrogen peroxide.
You know when a hangnail gets angry, and a tiny red ball of pain settles in for a party on the side of your finger? Well, yeah. That was me last night. My usual solution is to stick said finger into a bottle of peroxide for a good long soak. But we were out of the stuff, so, as has become my habit, I turned to Amazon. And that’s when things not only got weird, they got manipulative. Sure, I’ve been ambiently aware of Amazon’s algorithmic pricing and merchandising practices, but last night, the raw power of the company’s control over my routine purchases was on full display.
There’s literally no company in the world with better data about online purchasing than Amazon. So studying how and where it lures a shopper through a purchase process is a worthy exercise. This particular one left a terrible taste in my mouth – one I don’t think I’ll ever shake.
First the detail. Take a look at my search results for “Hydrogen Peroxide” on Amazon. I’ve annotated them with red text and arrows:
As you can see, the most eye catching suggestions – the four featured panels with large images – are all Amazon brands. Big red flag. But Amazon knows sophisticated shoppers like me are suspicious of those in house suggestions, so it’s included a similar product in the space below its own brands (we’ll get to that in a minute).
Above the featured items are ads: sponsored listings that are not Amazon brands, which means the advertiser (a small player named “Blubonic Industries”) is paying Amazon to get ahead of the company’s own promotional power. Either way, Amazon makes money. Second red flag.
By now, I’ve decided I’m not interested in either the sponsored brands at the top, or Amazon’s four featured brands, because, well, I don’t like to be so baldly steered into buying Amazon’s stuff. Then again, before I move down to the results below, I do notice something rather amazing – Amazon’s familiar brown bottle of peroxide is really, really cheap – as in, $1.29 cheap. There’s even a helpful per oz. calculation next to the price, screaming: this shit is eight pennies an ounce cheap!
Well, I’m almost sold, but because I hate to be directed into purchases, I’m still going to consider that similar brown bottle below, the one with the red label. Amazon knows this, of course. It’s merchandising 101 – make sure you give the consumer choices, but also, make sure the most profitable choice is presented in such a way as to win the day.
So my eye moves down the page to check out the second bottle. It’s from Swan, a brand I’ve vaguely heard of. Then I check its price.
Nine dollars and sixty nine cents.
Which would you buy? After all, this is a staple, a basic, a chemical compound. And you trust Amazon to get shit right, don’t you? I mean, a buck and change – nearly nine times cheaper? What a deal!
So…my eyes revert to Amazon’s blue labeled bottle. It wouldn’t have a four-star plus review if it burned your skin, right? And that’s when I notice the tiny icon next to it, which looks like this:
What’s this? Is this yet another annoying subscription service? Ever since we moved to New York, my wife and I have tried to figure out Amazon’s subscription services (Fresh? Pantry? Prime Now? Whole Foods Delivery? Who knows?!). I’m already deeply suspicious of any attempt by Amazon to lure me into paying them monthly for a service that I don’t understand.
But…a buck twenty nine! So I click on the bottle, and the landing page is super clean, and there’s no obvious Prime Pantry mention. Plus, it turns out, that bottle from Amazon is the Whole Foods generic brand, which for whatever reason seems a bit better than a generic Amazon brand. Did I just get lucky? Maybe I can just get some super cheap chemicals delivered in a day to my door, and my annoying hangnail will be a thing of the past soon enough….Right?
Here’s the landing page:
Looks great, the price is amazing, but…Uh oh. I can’t get this bottle of peroxide until Sunday. By then, I’ve likely lost my finger to a flesh eating bacteria. As I feared, this bottle is nothing more than a baited fish hook for one of Amazon’s subscription offers – which I find out, will cost somewhere between five and thirteen bucks a month. I’ve signed up for Prime Pantry by mistake in the past, and it wasn’t a smooth or enjoyable experience. No thanks. I click back to the original search results. Seems to me Amazon is gaming the shipping deals.
Well of course it is. I’m no longer a happy Amazon customer at this point. Now I’m annoyed.
But what’s this? If I scroll down below the $9.69 bottle, there’s another choice, also from Swan, and, it seems, exactly the same, if one is to judge just by the image (and we do judge just from the images, let’s just admit it). This one costs almost half as much as the one above it. What’s going on?! Here’s an annotated screen shot:
As you can see, there’s a lot going on. I’ve narrowed my choice down to two non-Amazon brands. They look nearly identical. The most significant difference, at least in terms of the information provided to me by Amazon, is the price – the top bottle is nearly twice as expensive as the bottom one. But the top bottle has a major benefit: I can get it nearly immediately! The bottom one makes me wait a day. Is the wait worth four or five bucks? Hmm.
Also confounding: The bottom bottle has its price broken out on a per ounce basis – 32 cents, exactly four times more than the 8 cents-an-ounce bottle I just looked at from Amazon’s Prime Pantry. Ouch! Now I’m really annoyed, and confused. My eyes dart back up to the $9.69 bottle. As I’ve shown with the empty red circle, there’s….no per-ounce breakdown shown by Amazon. It does tell me that this particular bottle is 32 ounces, whereas the bottom one is 16 ounces.
But why not do the math for me? A quick calculation shows that the top bottle comes out to about 30 cents an ounce – two cents less than the bottom bottle. Why not show that fact?
This, folks, this is algorithmic merchandising at its finest.
Amazon knows exactly how many clicks it’s going to take for me to reach shopping fatigue. Not “on average for all shoppers,” or even “on average for each shopper who’s ever considered a bottle of hydrogen peroxide.” Amazon knows all of that, of course, but it also knows exactly how long it takes ME to get fatigued, to enter what I like to call “fuck it” mode. As in, “fuck it, I’m tired of this bullshit, I want to get back to the rest of my life. I’m going to buy one of these bottles.”
And because there’s no per-ounce breakdown of the 32-ounce bottle, and because that makes me suspicious of it, and because hell, who ever needs 32 ounces of hydrogen peroxide anyway, well, I’m just going to buy the $5 one.
Ca-ching! Amazon just made a nearly seven percent markup on my purchase. It took five clicks, 15 seconds, and a vast architecture of data and algorithmic mastery to make that profit. Each and every time we purchase something on Amazon, that machinery is engaged in the background, guiding us through choices which insure the company remains the trillion dollar behemoth we know and…
Do you love Amazon anymore? For that matter, do you love Facebook, Google, or Twitter? Interactions like the one I’ve detailed above are starting to chip away at that presumption. Personally, I’ve gone from cheerleader to skeptic over the past few years, and I’m broken out into full-blown critic over the last twelve months. I no longer trust Amazon to have my best interests at heart. I’ve lost any trust that Facebook or Twitter can deliver me a public square representative of my democracy. I’ve given up on Google delivering me search results that are truly “organic.” And YouTube? Point solution, at best. I can’t possibly trust the autoplay feature to do much more than waste my time.
What’s happened to our beloved tech icons, and what are the implications of this lost trust? In future posts, I plan on thinking out loud on that topic. I hope you’ll join me. In the meantime, I think I’ll stroll down to CVS and buy myself another bottle of hydrogen peroxide. By the time Amazon’s comes, I’m sure my hangnail will be a distant memory. But that taste in my mouth? That’s going to remain.
Update: Many readers have pointed out that I missed the fact that the top package of peroxide was, in fact, a two-pack. True that, and it would have changed my on-the-fly calculation around which to buy, given the per ounce comparison. However, it would not change the fact that the act of not adding the per ounce calculation directly on the page somehow discolored that choice.
Also, a rather rich post note: The bottle I did buy never came. It was “lost” – and Amazon offered me a refund. Sometimes it pays to just hit CVS.