Odd Lots - The Internet Is Secretly Powered By Billions Of Tiny Auctions

Episode Date: July 2, 2018

Everyone knows that online advertising pays for a massive chunk of the internet that people know and love, whether it's social networking sites, news, photo sharing apps, or anything else. But how do the ads get delivered to your desktop or phone? On this week's Odd Lots podcast, we speak to Afsheen Bigdeli, an engineer who works on online ad platforms about how every time you see an ad it's the result of a virtually instantaneous online auction in which the seller of ad inventory (a publisher) and a buyer of ad inventory meet at an exchange, not totally unlike exchanges used for financial markets. It turns out there's a lot we can learn about financial market structure based on these rapid transactions. See omnystudio.com/listener for privacy information.

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I'm Joe Eisenpaw. And I'm Tracy Allaway. Tracy, do you know what powers the internet? Hamsters on wheels. No. Electricity, I don't know. Data? Is this like a metaphor?

I guess you could probably say have a lot of different answers. Electricity is probably one. someone could say data. I was going to say online advertising. Ah, now this is interesting. Do you mean in the sense that online advertising pays for websites to actually run? Yeah, basically, it's like if you think about virtually anything we do on the Internet, if you think about at least some aspect of our careers, having written on the Internet,

if you think of all the social networking sites, literally everything, in some way it was probably paid for via online advertising. Yeah, I guess you're right. I mean, none of these things are really provided for free. And I guess the cliche is always, if you're not paying for the service, then the product they're selling is probably you and your personal data, and they're selling that to advertisers, right? Exactly.

And of course, as we know, a lot of the practices in online advertising these days are pretty controversial. and people are concerned about privacy, and as you said, your personal data and the reader or the user being the product. But have you ever wondered really how they figure out what ad to serve you in the split second? You go to a website and there's already an ad

that's perfectly tailored to your interest. Have you ever really explored how that happens? I'm not lying when I say I have actually wondered this. Specifically, I've wondered why the pair of shoes that I looked at for, like five seconds two weeks ago, follow me around the internet for months later, begging to be bought. That really annoys me. So if this is what we're going to talk about, then I'm on board, Joe. But what does it have to do with markets exactly? Well, it's a, first of all,

this is exactly what we're going to be talking about. So you're in luck. And of course, it's a markets thing because someone has to buy and sell that ad inventory. And essentially, you go to a website or you go to Facebook or whatever. And there has to, has to be some sort of process for allocating that advertising space and how much are people going to pay for it and how much is that worth and how much is the website going to sell it for and that is a marketplace. So the internet is fundamentally run by market structure is what you're telling me. I love this episode already.

Exactly. Well, I'm very excited about it. So without further ado, I want to bring in our guest. His name is Afshin Badelli. He is a systems engineer for online ad platforms, and we are going to talk about market structure as it pertains to the world of online advertising. Shane, thank you very much for coming in. Thank you. Hi, Tracy.

Hi, Joe. So what happens when I go to a website? Wow. Let's just jump right in. Great. So today, on average, for the average website, let's go through what happens. So you load up your favorite web page, whatever it is, let's say, Bloomberg.com. Bloomberg.com, of course.

And chances are you visited Bloomberg.com before. This is not the first time you visited this site. So that's important. We'll get back to that in a bit. What happens, the moment you load the page, there is a race. People want to find out who you are and whether it's worth their time to show you an ad. And the hope is, if they show you an ad, maybe you will in some way engage or convert or respond to that ad in different ways and there are different methods for measuring exactly

how you convert. So the whole game at this point is to show you an ad as quickly as possible that is as revenue impacting as possible for both the person purchasing the ad and the person selling you the ad, the publisher and the advertiser. So I have a bunch of questions already about how the buyers and the sellers kind of come together But I guess before we get to that, can you describe what kind of personal data is available if Joe or I actually click on a website, be it the Bloomberg website or something else? Sure. So we can divide this generally into three buckets of data, let's say. There's the data that we know about the user as soon as they visit the page, the data that is live that is part of the request.

Then there's the data that Bloomberg, in this example, has from your past visits, and then there is the data that the advertiser has purchased from a third party that has been collected from you over the course of months and years from all sorts of different sources. The party that is in charge of providing this last bit of data, which I'm guessing is the most interesting to you, is called a DMP, a data management platform. It's the job of these DMPs to find out as much data as they can possibly get about you in aggregate from all sorts of different databases and data sources and correlate it to the information that is returned to them by the publisher, in this case, Bloomberg. So I have a bunch of potentially different interests. I'm interested in financial markets. I'm interested in boxing. I'm interested in barbecuing. So in theory, there's a lot of different types of advertisers, very different from each other, that might want to compete for my attention, that might want to put up some product that they're selling in front of me.

So what is the process by which that collection of data that the DMP has on me turns into someone putting an ad in front of me? Ah, so that is the job of the DSP, the demand side platform. Are you enjoying the alphabet? I am already. I have a feeling there's more to come to. There are. Okay. So the demand side platform partners with several DMPs, and it's their job to look at your incoming

data, your page visit data that happens when you visit Bloomberg.com in this one moment, and correlate it to all the different data it gets from the DMPs. And how they go about that is sort of proprietary. It's the special sauce. But imagine they have just about any imaginable. data source that they can possibly call on you based on your email address and how, who you've given to in the past, cookies that you've dropped on websites in the past, even location beacons from brick and mortar real life stories that you visited in the past. And they're correlating

it all in that single moment while you're viewing the page in order to figure out which ad is best to serve to you. It's weird to think there's like a behind the scenes battle happening every time you open up a new web page. I'm wondering, how did this structure actually? come into place. Who made the decision that this was going to be the way that the internet essentially works and that advertising is sold online? So let's go through a brief history of how the market microstructure of online advertising involved. Those are words I never thought I'd be saying before, but here we are. So in the beginning, there was...

This is why the... Welcome to the Outlaws podcast. So in the beginning, there were advertisers and publishers. So in this case, there's, let's say, Bloomberg and someone who would want to advertise on Bloomberg. And around, let's say, 20 years ago, is fairly easy for these two parties to find each other match up. There were not that many people who were advertising and there not many people publishing websites. But more and more advertisers and more publishers makes this market microstructure really inefficient. Imagine the equivalent of an open outcry pit, but only about five people in each pit scattered all around the world. How do buyers and sellers match up with each other after they've reached

a certain volume? The solution to that first became advertising networks. This would be an aggregation of advertisers under one umbrella being presented to publishers. That solves one problem. How do you get more supply to satisfy demand? But it exposes another problem. To give an example of what that problem is, let's put some color on what ad we're serving on Bloomberg.com. Let's say we're serving an ad for men's shoes.

So if I present that ad to Joe when he's viewing a Boolmoor.com, there's probably a higher percentage of a chance that he's going to convert and actually engage with that ad than if I were to show those same men's shoes to Tracy, who I'm guessing is not in the market for Adidas right now. So we need a way to... Not men's shoes, no. No. So we need a way to solve that problem. We need a way to actually show Joe the ads that he cares about and Tracy the ads that she cares about. So that led to ad exchanges, and that in turn became demand-side platforms. The evolution, how we went from ad networks to add exchanges to demand-side platforms, basically

came from the recognition of this problem that although we have the ability to match up advertising publishers, buyers, and sellers, neither of them really know how to match up the best inventory with each other. They know how to give each other, you know, a certain lot size, a certain amount, a certain quantity in terms of number of ads or in terms of revenue spent, but they don't really know how to connect to Joe to give him the best ad that he wants. Tracy, I'm listening to Offsheen describe this. I'm thinking back to some of our early episodes with Chris White talking about bond market structure and just the sheer multitude of potential players in the game and varieties of bonds that people could be selling, different coupons, different times, different

structures, and the sort of complicated challenges that that poses in terms of bringing everyone together. Yeah, absolutely. I wonder in that case, again, how they're able to do it so quickly that we don't even notice that it's actually happening in the background. So, Afshin, what's the technology that's actually allowing people to do this? So the technology is referred to as, You Ready, Joe, another acronym, RTB, real-time bidding. And it's meant to happen as quickly as possible to connect advertisers and publishers through

supply-side platforms, SSPs, and demand-side platforms, DSPs. Why it's so fast, well, there's an interesting wrinkle or two there. First off, the publisher always has the option of showing you a house ad if they don't get a proper real-time bid that they could match you up with in time. The reason you might want to show a house ad versus a targeted ad is because you never want to leave a user waiting for an ad load. I'm sure you've all had the experience of visiting a page and waiting for it to load and waiting for it to load, and when it does, you get a pop-up or something more inoxious. Generally, you want to avoid that. What RTB allows publishers to do is present the best

possible targeted ad, but if they can't do that in time, they'll just be happy to show you any ad. Maybe they have their own personal brands. They'd like to show off to you. Maybe they have a preferred private partner whose ads they have an inventory that they would front run in front of their RTV ads. It really depends on the publisher. So explain to us the auction process. Real-time bidding is essentially describing an auction. So walk us through what in that micro-second or whatever where that ad is delivered, how the bidding works.

Sure. Okay. So let's walk through our example again of Joe visiting Bloomberg.com. Joe visits Bloomberg. Bloomberg sends Joe's data to their SSP, their supply-side platform. The SSP, in turn, transforms this data into a bid and passes it off to the ad exchanges. The ad exchanges, in turn, pass this off to their DMPs. Are you following the micrarch?

Command-side platform. Yep. Sorry, did I say DMPs? Not DMPs? DSPs, even I get confused. The DMPs are the data management platforms. They're in charge of getting the data. The DSPs are the demand-side platforms.

Got it. And the demand-side platforms, in turn, look for the best inventory, the bids that match up with the eyeballs that they're getting from Bloomberg, and try to make the best match. It's the DSPs side or a job to serve as sort of the matching engine here. So this all goes through three counterparties end-to-end, if you're counting.

So I'm curious what pricing actually looks like under the system. Because if I think back to old style advertising, and you know, please let me engage in some media navel gazing here. But if you were selling newspapers, for instance, you would know roughly what the audience for your newspaper circulation was. And you would have a decent idea of, you know, their income levels and where they live and what they like to spend money on and things like that. But now these online ads are so targeted, does that drive down the pricing?

Because you're not really targeting like a big swath of the population that you're hoping might buy your product. You're actually targeting a specific person. It actually seems to drive up the pricing because you don't really want to flood the market with ad volume that most people won't engage in. You want to hit the lowest number of people because remember, there's a ton of technical effort going behind. all this. There are servers that need to run and engineers that need to be paid and all that. You want to put the least amount of effort into pushing your ads to the most people who are most likely to engage with them. You never want to have any extra ad targeted, that hits someone who's unlikely to click it. Ideally not. Think about it like this. Let's say you have a thousand ads that you want to push to people. If you have the choice, and this is how it used to work about 10 or 15 years ago, of just agreeing to a rate up front with a publisher. saying these thousand ads will sell for $10 and leaving the publisher in charge of running those

ads as fast as they can sell. And some people will be engaging with those ads Monday, around 2 p.m., some at Saturday, 4 a.m. in the morning, some from the United States, some from Indonesia. They'll all get the same rate. That's really not efficient from an advertiser's point of view. They're really not getting the most bang for their buck. So what they would like to do instead is push to people who they know as much information about and for whatever reason they've decided have the high-

confidence in their ability to convert with the ad. I'm June Grasso, inviting you to join me for the Bloomberg Law podcast. Every weekday, we help you make sense of the legal stories that shape the nation and the world. Listen for complete analysis of the biggest court cases, the latest actions from Congress and regulators, and the legal moves driving the markets. From corporate law to constitutional law and from state courts to the Supreme Court. At Bloomberg Law, we go beyond the day's headlines. We speak with top attorneys, judges, scholars, and policy experts to break down what the rulings really mean.

We do this every weekday, then bring you the best conversations in our daily podcast. Search for Bloomberg Law on YouTube, Apple, Spotify, or anywhere else you listen. On the East Coast, listen as you start your day. And on the West Coast, catch up in the evening. That's the Bloomberg Law Podcast. with me, June Grasso. Subscribe today wherever you get your podcast. Now, I'm curious about sort of, you know, if we really dive into the sort of financial

market aspect of this, are there players in the market that attempt to, for better, lack of better words, engage in arbitrage, buy up cheap, buy up inventory that they think they could get on the cheap and then sort of repackage it in some way and resell. up more expensive, like essentially become traders? Absolutely. And there are several different arbitrage strategies, just as you'll find in any other market microstructure. There are plenty of companies who are in the business of taking in raw ad supply and sort

of cherry picking what they think is the best possible converting ad. And on the other side, there are plenty of people who are in the business of aggregating eyeballs and only presenting the best possible eyeballs to advertisers. Unfortunately, I'm not sure I can give any of their names on air. How profitable is that business then? Can you make a ton of money out of it, given that the pricing is quite low? It is extraordinarily profitable in the tens of billions of dollars a year. So from time to time, you mentioned Secret Sauce, I think, at one point, and you talked about this.

And you hear about this world of companies called AdTech. And I never am totally clear what they do. and a lot of them seem to rise really fast and fall really fast. So what are some of the competing strategies? Some company comes along and says, we have something new. We have a new way that you can reach your clients more efficiently or we're going to use AI or machine learning or big data or whatever. Like what are these ad tech companies?

Where are they in the process and how do they attempt to make things more efficient? So there are really two basic strategies for these ad tech companies. is one is to make the process faster, to present ads faster to eyeballs that are willing to view them, and gain a sort of latency arbitrage edge. The second strategy is to gather as much information as possible from all these different aggregate sources and as quickly as possible match it up to the visitor that's trying to view the ad. Most ad tech companies focus on the second strategy. They're in the business of gathering tremendous amounts of data,

correlating it all very, very quickly, and presenting a two. you quicker than the page will load. I'm curious about the data gathering aspect. So let's say you and I or the three of us here, we're like, okay, we want to start a new ad tech company. And how do we start gathering that data? Like, where are there wholesale brokers of it or can we collect it ourselves? Like, what's the process there?

So first we were probably partnered with several publishers, like Bloomberg, for example, to go back to the beginning. Yeah. We would also partner with third-party data providers. We would want a combination of raw, fresh data coming in from new visits so we can build our own database, and we'd want to have the ability to correlate it with as many pre-existing data sources. You probably don't want to reinvent the wheel.

There are plenty of public databases and four pay databases out there where you can find out, for example, from your email address or from your IP address, what country you're in, what city you're in, what sites you've signed up for in the past, what URLs you've visited in the past, what time zone you're in, what language you speak, all that sort of stuff. So what's the most lucrative area when it comes to this ecosystem of online ad selling? Is it the data collection? Is it, you know, the underlying technology of the bidding system? Is it if you're, you know, arbitraging big blocks of potential eyeballs to sell to people? What makes the most money?

So judging from the market cap of the ad tech companies out there today, I'm going to It's a combination of selling the ad and also taking a bit of the cut of every ad that's sold. A good example here might be Google, which most publishers use as a demand side partner. So Google gets their money two ways if you're using their product, DFP, double-click for publishers. If you're connecting to Google through DFP, they get a cut of every ad that is served through DFP, but also they have the option of serving ads from their own inventory through their

exchange, AdEx. So for an analogy, think if, for example, on the Comex, you both ran the exchange and also ran a gold mining company and offered a gold ETF on the exchange. You not only get a cut of every trade, but you're sourcing inventory. That seems to be the most profitable. So Google not only runs the exchange, they also are participants on the exchange and are selling a raw commodity on that same exchange. And so they make money multiple ways from that trade or from that environment. Exactly. In fact, they even... See, it sounds like Google's a pretty good

business. Yeah. I wish I thought of that. Is Facebook similar in that respect? They have a similar business. It's slightly different for social media, but similar. So I'm curious about the matching of the right ad to my interest, because maybe I'm interested in buying a yacht or a new car, some very lucrative thing or if I clicked on the ad, someone could make a ton of money. But I might also be interested in buying a book from Amazon that, you know, probably the margins are small. So how does it balance those disparate potential outcomes to figure out which one is the best to serve me? Well, the best way to describe it would be the free market. The DSP is connected to several advertisers. Each one of them is willing to bid on your impression. So it really comes down to is the yacht seller advertiser and

the bookseller advertiser, how much do they both value your eyeballs. Maybe the yacht seller thinks you're not really going to convert on an ad because he's looked up your date and says, oh, well, you know, you live here in this time zone. I've never bought a yacht before. Yeah. So it's a safe bet you probably won't in the future, but you've probably bought plenty of books. So maybe the yacht seller is not going to fight as harder for you using the price mechanism than the bookseller would. So if in one case, let's say the yacht seller bids 50 cents for your eyeballs and the bookseller bids a dollar, the bookseller win and they'll end up paying 51 cents, just enough to beat the yacht sellers bid.

Got it. So the bookseller might end up bidding 51 cents and on a transaction that maybe we'll make them 55 cents or a dollar or something like that. Right. And the idea is you will probably lose money on most of these in aggregate, but the winners are real winners. And the yacht seller occasionally is going to get that ad and is probably going to serve thousands and thousands of ads that don't turn to anything, maybe millions, but then when they do, those are huge jackpot. Yes, and I'll add one more wrinkle.

We're talking about ads, but ads come in many different forms. This isn't just a race for eyeballs. It could be racing for video ad views or application installs even. So I have a sort of related question, sort of maybe even a philosophical question, but so much of the online advertising world seems to be about talking. targeted advertising. So does anyone just, you know, throw stuff out there nowadays just on the off chance that someone might see a good product and want to buy it? To Joe's Yacht example, you know, what if someone has a really, really nice yacht and they think people will buy it,

if only they were aware of it? Sure, that does happen. It's also pretty rare because in order to actually get a high enough conversion ratio for this to be worth the advertisers' time, you really have to buy a tremendous amount of volume if you're not doing any targeting on who your customer is. An analogy might be putting up a billboard versus sending a direct mail flyer. If you don't know much about the person who's engaging on the other side of the buy, who knows if they're going to buy it. Is there though, like sometimes you see like a huge site takeover, like on the New York Times or something like that. You'll see some massive, they'll buy every ad on the website or on the front page or something like that, it's clearly not particularly targeted.

There is still some sort of like brand advertising on the internet, right? Yes, those are private auctions, and those are great, but they're really only great for publishers who can demand that sort of leverage. For Bloomberg.com in this example, that'd be a great example of a site that would have enough cachet to pull in a private auction. I could imagine plenty of brands would want to have exclusive access to the eyeballs at visiting bluebara.com. personal blog, probably not so much. I'm probably not going to be able to land that big deal with

Pepsi or Coca-Cola to have them take over my site for the next 30 days. And that's something that would be negotiated among humans and there would be a deal. Maybe like there was just the big ad conference in canned or people like partied on yachts and stuff like that. And those are the kinds of deals that get negotiated there rather than through some sort of like algorithmic matching engine. Right. And think about it if you will, as a little, as a little, the difference between buying at the market price on an exchange versus setting up an OTC trade. We like to talk about changes to market structure quite a lot on the Oblots podcast. Are there any

big changes or big pressures or disruptions on the horizon for the current structure of the way these online ads are sold? Oh, I'm glad you asked. Let's talk about header bidding. Heter bidding. Hedder bidding is what seems to be what's going to come next after real-time bidding. And let's explain what it is and what the motivations are behind it. I mentioned Google's DFP, double-click for publishers before. It has an interesting feature. First off, most people most the time use Google for advertising, just in the same way that most the time use Google for search.

And most publishers are content to just trust Google to sort of drive the process and they don't really dig too much into it because Google wouldn't always serve an ad that seems to be seems to satisfy both the advertisers and the publishers. The reason, in part, that Google is able to do this, besides the fact that they're so great at aggregating data, is what's known as the waterfall. Here's how it works. You call out to Google.

You ask them if they can give an ad to you so you can serve it to your visitors. Google goes through their inventory to see who the best ad is and where it's coming from. They have the option of serving it from another exchange or their own exchange adex. So they have the ability to front run basically any other advertising exchange if you allow them to. And because Google is where all the publishers show up to, all the other exchanges sort of put up with it or forced to. Heter bidding is meant to change that. Heter bidding is different from real-time bidding, in that instead of where in real-time bidding, where a publisher calls out to a DSP and waits for a response, header bidding allows the publisher to call out to multiple DSPs all at the same time

and select the best bid incoming themselves. So you lose the convenience of just letting Google drive, but you gain the price competition between all of these different bidders. It sounds obviously better for the publisher, so why is that not already the norm? Well, because Google doesn't like it that way. Most people, most of the time, are actually not as enamored with his market market market Mike's structure as you and I are, a publisher is probably in the business of publishing content and doing whatever their core business is. Actually, managing and driving this process yourself

is really tricky. In order to, for example, for head-de-beating to be really profitable for you, you'd have to actually, you know, care about those bids and put some thought into whether you might prefer one partner over another. Would you need to build your own technology to determine if you're getting multiple bids from multiple exchanges, then I guess it's on you to actually determine which one is the best, whereas if you're just on one exchange, then that determines what's best. And so I imagine to take some more supply-side infrastructure to build that up. Exactly. It's the difference between, you know, setting up effectively your own prop shop for ads versus just trusting your broker to supply you with what you're asking for.

Well, that has been an absolutely fascinating discussion. And I just love the fact that the kind of market structure that topics that Tracy and I talk about frequently on this show are actually at the root of how the entire internet works. And I didn't even realize that. So, I'm Sheen Badele. Thank you very much for joining us. Thank you for having me, Jill. So, Tracy, you said that you've been thinking about online ads and you've been wondering about how they get served up to you. Do you feel that your questions have been answered? I mean, I definitely have a better sense of it now, but I will never look at a web page loading the same ever again.

You know, every time I go someplace, I'm going to be thinking about the intense auction process that's currently happening in the background with a bunch of people trying to bid on my specific profile. It is pretty amazing. I mean, sometimes websites or apps load a little bit slower than you would like. But even with that, it is pretty amazing how much has to happen in that short period of time. you don't even notice it, but all this information goes out, it's analyzed, it's put into some profile, there's a bidding habit, a bidding war happens, and an ad is served to you

basically in an instant. I don't know if it's exactly a miracle because it's kind of... Creepy. It's kind of creepy, right? But it is kind of amazing, isn't it? Yeah. I guess it gets to a point that we've talked about before on the show, which is also about inequality and the ability of algorithms to sort of reinforce a certain position that a person is already in. So, for instance, you know, if when you're 24 years old, you need a payday loan to survive until your next month's paycheck comes in and you search online for payday loans, those ads might follow you around for years and years to come when other people who have never needed a payday loan might see, you know, advertisements for 401.

or things like that. I'd never really thought of it like that before, but I've been thinking... We had a whole episode on this, Joe. No, no, no, no, absolutely. I'd never thought about that with regards to online ads specifically. But I have been thinking about how, like, I went through a phase where I needed to buy some clothes I need to buy some shoes. And then I got served tons of ads for weeks and months on end on similar stuff.

And then I started worrying that, wait, am I buying more than I need to now? on these things because I went through this period where I made these purchases. And so thinking about the sort of lasting impacts of a certain behavior on the type of ads we're inclined to see for a long time is really fascinating. And it absolutely does speak to that discussion we had earlier about the influence of algorithms on our lives. Yeah, you cannot escape your internet history no matter how hard you try. All right. Well, this has been another episode of the Odd Lots podcast. I'm Tracy Alloway. You can follow me on Twitter at Tracy Alloway.

And I'm Jill Weisothal. You can follow me on Twitter at The Stallwart. And you should follow our producer, Tofer Forges, on Twitter at Forthes T, as well as the Bloomberg head of podcasts, Francesca Levy, at Francesca today. Thanks for listening. The news doesn't stop on the weekends. Context changes constantly. And now Bloomberg is the place to stay on top of it all. Hi, I'm David Gura. Join us every Saturday and Sunday for the new Bloomberg this weekend. I'm Christina Ruffini. We'll bring you the latest headlines, in-depth analysis, and big interviews. All the stories that hit home on your days off.

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