Category Archives: Ad Technology

The Difference Between Programmatic RTB And Direct

By Eric Picard (Originally published on AdExchanger April 1, 2014)

I had the great fortune to moderate a panel called “Programmatic Guaranteed” at AdExchanger’s recent Programmatic.io conference in San Francisco. The prep conversations for this panel, the conversation on stage and the conversations with audience members afterward were very compelling.

Clearly the market wants to figure this out, and the promise of programmatic means different things to different people. This is a complex space that needs more information and definition, which we’ll do today.

As an industry we have two primary “stacks” of technology that drive advertising between the buyer, seller and consumer. One is what I’ll call the “direct” stack, and the other is the real-time bidding (RTB) stack.

Direct Advertising Stack

The “direct” software stack in play supports publishers. This is the first-party ad sever, the publisher’s inventory management system. Examples include DoubleClick for Publishers, Open Ad Stream and Freewheel.

This publisher system enables publishers to manage their advertising businesses – in particular, this is designed around the need to put ads on pages, monitor revenue and manage sales. But one of the primary uses of these systems is for publishers to package their inventory. One of the core uses of this entire technology stack is to find inventory that is available for sale, and package it in order to sell it to advertisers.

The direct stack is a set of tools and technologies for packaging inventory for sale to buyers. Packages are assembled either in advance, or in response to a buyer’s request for proposal and media plan.

The Programmatic Direct Stack

Over the last few years, a variety of companies have launched in the programmatic direct space, which aims to connect the publisher’s direct systems to buyers’ systems – either the traditional or the programmatic tools. Examples here include YieldEx, iSocket, Shiny Ads, Bionic Ads and AdSlot.

The problem with this stack, from the buyer’s perspective, is that the programmatic direct world is an extension of the direct platforms. They are designed to package inventory according to the ways in which publishers want to sell inventory. They aren’t designed to allow the buyer to manage against their own goals. The contract terms for inventory are defined by the publisher, and executed according to a publisher-centric view of the world.

The benefit that buyers get from the direct stacks are that the inventory can be reserved — in other words, the publishers and buyers can agree in advance on not only the price of the inventory, but the volume and budget that the buyer is signing up to spend. And the publisher is willing to guarantee the buy, meaning that if they under-deliver, they will give the buyer a “make-good” on the inventory that was not delivered.

Programmatic RTB Advertising Stack

The RTB software stack is focused primarily from the point of view of the buyer. There are supply side platforms (SSPs) like Rubicon and Pubmatic that are publisher facing, but like their demand-side partners (DSPs), their focus is on enabling the buyer to find inventory according to their definitions, rather than packaging inventory up on the publisher side.

The systems in the RTB world are very flexible and don’t require packaging in advance.  The only problem with this is the inability of these systems to easily offer a guarantee on the buy. There are some mechanisms that can be used, such as the Deal ID standard, which allows a buy-side system to be assigned to a specific ID in the sell-side system. But typically these are supported more by the SSP, and not within the direct stack of software.

There is an immense amount of investment in the ability to forecast and ultimately to sign reserved or even guaranteed deals in the programmatic RTB software stack, but we’re still a ways from this. We may find ourselves supported here in the next year or two – but matching these systems together has proven challenging – and recreating the ability to forecast and give make-goods in the RTB stack has been nearly impossible.

The ‘Holy Grail’

There is another path that some technology companies are exploring, which is the ability to push the advertiser’s demand goals directly into the publisher’s direct ad server. In this model, the buy-side system allows the buyer to specify their goals, and then through integration with the publisher’s direct ad server, can create line items matching the advertiser’s goals. But this is a new approach that has not been fully productized yet in the market. It will be interesting to see how this evolves.

The confusing language of ad exchanges

By Eric Picard (Originally Published on iMedia – March 15, 2014)

Our industry is filled with confusing concepts and equally confusing names. We have constantly done ourselves no favors by trying to simplify the concepts by reusing names from other industries or from parts of our industry that are not quite a match.

The most confusing area of our industry right now is anything touching or associated with advertising exchanges. I’ve heard all sorts of names for “things” in this space, and for whatever reason, we never seem to really get things “right.” The names that cause the most confusion and agitation in our space include ones like programmatic, spot, futures, guaranteed, reserved, etc.

Let me hit the term programmatic first, since this one should be easy enough to nail down. Programmatic media buying and selling really just refers to the fact that the buying and selling is automated. Programmatic buys might make use of the ad exchange (typically these are called programmatic real-time bidding campaigns, or programmatic RTB.) These are buys that use demand-side platforms (DSPs), such as MediaMath, Turn, or AppNexus, and are what most of us think of as ad exchange powered media buys. Programmatic buys might also make use of a toolset like Bionic Advertising Systems or connect to an API like iSocket. This type of buy is typically called a programmatic direct buy because the buyer is accessing inventory sold directly by the publisher, not over an exchange. But it is still an automated buy.

Television terminology

Another point of confusion that I hear about a lot is people trying to apply the concept of “spot” media buys to the exchange. The person using this term equates “guaranteed” media buys with the television upfronts and ad exchange buys with the television spot marketplace. Sometimes the term “scatter” gets used here, but not too often.

The television spot and scatter markets are essentially the same thing: spot applies to broadcast, and scatter applies to cable. These two markets basically cover all the non-upfront buys that happen in television. In broadcast and cable television media sales, the networks try to sell large blocks of ad inventory in bulk — several times a year. These sales extravaganzas are glitzy, involve a lot of money being spent in all directions, and lead to a large number of bulk sales of ad inventory in the television space.

There have been many attempts to replicate this upfront process in digital media, with varying degrees of success. The interesting thing is that the upfront process is really a discount mechanism for the media buyers. Media buyers agree in advance that they’ll pay a certain amount of money per gross-rating point (GRP) for television media inventory in order to get the sellers to give them a discount. The sellers are OK with that discount because it mitigates the risk that they won’t be able to sell that inventory later.

The rest of the television advertising inventory is sold on an ad-hoc basis in advance of the date of the show. Typically the price of inventory in the spot and scatter marketplaces is higher than the upfronts. Non-upfront buys (spot in broadcast, scatter in cable) are sold as far in advance as the buyer is willing to sign up, to as close to the date of the show airing as the seller can support technically (usually a day or two before the show is aired).

For some reason in digital, some people think of upfront as the equivalent of guaranteed and spot as the equivalent of ad exchange buys. The really interesting thing is that every “guaranteed” buy we do in digital is exactly the equivalent of a spot buy (or scatter buy) in TV. Spot buys are essentially guaranteed (reserved), and they’re bought anywhere from one day to months in advance. So we shouldn’t use the term “spot” to describe the ad exchange; this is technically incorrect. There is no traditional media equivalent to digital media ad exchanges — at least not yet.

Spot and scatter buys are reserved in advance, with make-goods and all the other nifty things expected in “guaranteed” digital buys once the contract is committed. The only minor difference here is that most buys are “preemptible.” That means that if another buyer comes along after the contract is signed, and the new buyer is willing to pay a high enough price to get the inventory, the seller can preempt the existing contract (usually this involves a penalty that the seller has to pay) and can substitute the new buy for the old one. Take note digital media folks: This is actually desirable to the buyers, and they’d love to be able to do this in digital. We just don’t support it because we didn’t design our systems that way. It would be great to really offer reserved buys instead of guaranteed buys.

Financial market terminology

The other thing we screw up in our space is trying to use stock exchange or commodity marketplace language to describe what happens in the digital media exchanges. But there isn’t an exact equivalent of most of these concepts. While the term “guaranteed” is used to describe “reserved” buys that are sold in advance in digital media, when people in our space want to discuss selling reserved buys over the ad exchange infrastructure, they try to talk about it in terms of “futures.” The problem is that a futures contract is not the same thing — not even remotely — as a guaranteed media buy.

In the financial markets, a futures contract is a very specific thing. It implies a whole lot of infrastructure and implementation that simply isn’t supported anywhere in the digital media infrastructure today. The biggest problem with trying to implement a “futures contract” mechanism in digital media is that the unit of inventory we sell — an ad impression — only exists for milliseconds. There isn’t an equivalent in the physical world that matches this scenario in which “futures” are sold for shares of a company or of a commodity that will exist and continue to exist after the contract expires.

Of course, I’m not an expert in the mechanisms used in the financial markets, and there might well be some more esoteric mechanisms I’m not aware of that more closely match what we do in digital media. But the danger here is that we push too far forward on something that isn’t a close match to what we actually need in order to have a healthy business. I don’t think it would be a healthy business decision for us to build marketplaces where “futures contracts” on ad inventory could be resold, for instance. There are plenty of reasons that this would be a bad idea.

How (and why) emerging media should plan for scale

By Eric Picard (Originally Published on iMedia – January 18, 2014)

People in emerging media spaces frequently ask me how they can get advertising into their content experiences or how they can use their technology to create value for advertising technology companies. Recently someone asked me about using bitcoin in advertising. In the past, I’ve spent hours working with clients who have hired me to help them figure out advertising models for their new emerging media products, despite my telling them early on that it’s unlikely that there’s a “there, there” related to their situation due to scale.

This is apparently hard for people to wrap their heads around, so let’s talk about this specific issue — the issue of scale in advertising. At its heart, the issue of scale is possibly the biggest and most fundamental issue in advertising — and it is frequently misunderstood. Here are my three rules of scale in advertising:

  • Advertisers need to be able to spend relatively significant budgets efficiently at a low cost per impression.
  • Advertising campaigns need to be able to reach relatively large audiences without significant complexity in managing them.
  • Return on advertising spend (ROAS) needs to be able to be calculated in some form (including, in many cases, very simple key performance indicators).

Let’s talk first about the difference between marketing and advertising. I’ll give you my definitions, as the dictionaries don’t do justice to the concepts:

Marketing is about communication; it is a commercial message to a potential or existing customer, and increasingly it is a two-way conversation with potential or existing customers. Marketing includes one-on-one conversations between employees and prospects, mail and email communications, advertising, public relations, and more.

Advertising is about reaching the largest possible audience, with the best available message, as effectively, inexpensively, and efficiently as possible, generally through distribution over a large media channel. Advertising is a subset of marketing, but it has unique properties and rules that one needs to be aware of in order to apply it as a revenue source.

The most important concept that defines advertising as opposed to marketing is scale of reach at a reasonable cost. Advertising generally requires that a very large audience can be reached at a low cost per impression. Not only must the cost to reach the audience be relatively low, but the cost to manage the buying of the advertising media must also be relatively low. In addition, the ROAS must be somewhat measurable. That said, ROAS is a fairly squishy way of discussing a variable and varied set of metrics that are generally constructed on a per-advertiser — or even per-campaign — basis to gain an understanding of results.

At this point, a few of you are probably getting ready to argue with me about some of the things I just said. The likely argument revolves around some high-CPM inventory that is bought by some advertisers for some campaigns at a very high rate. And while this does happen, my points above still hold true. The cost of the inventory is relative based on the goals of the campaign and an analysis of its results.

For instance, some inventory that is highly targeted or highly effective can sell for a high CPM, but it can still meet the ROAS goals of the campaign. This can be due to high performance or a relatively rare target audience (perhaps extremely high income or very niche interests, such as pilots, airplane owners, or sky divers). It can also be due to a highly competitive media set (e.g., auto-intenders or people who manage investments).

ROAS is a superset of all the various means of calculating performance because ROAS can be based on brand metrics as well as performance metrics. It can be as laser-focused as a tightly bound formula including cost per acquisition (CPA) and the margin on the product that the “A” drove. Or it can be as broad as understanding that for every dollar of advertising spent (using some kind of analysis that could be sophisticated or simple) gross sales increased by some amount.

The ROAS calculations can also be derivative. For instance, there may be a very clearly understood metric that has very clearly understood value that can be used as the primary goal of a campaign. For instance, in the automotive space, the value of a test drive is very clearly understood; most car companies know exactly what the conversion rate is between test drives and purchases of their cars. It’s common to use test drives as a campaign goal, which is not really the goal of the advertiser, but it is fairly measurable and clearly understood in secondary value in sales.

For those trying to roll out a new (or emerging) advertising medium — one that is based on new content models, new distribution models, or new devices or technologies — this concept of scale is critical. Until a media type can provide enough reach to be of value, it’s hard to use advertising as a mechanism to fund it. That number varies based on the makeup of the audience using the media.

For instance, if a new hand-held device for hedge-fund managers were launching, the audience size needed to be ad supported would be much lower than a hand-held device for the homeless. For a mixed-audience scenario, one that’s by nature more affluent (since most emerging media scenarios tend to appeal to early adopters, who tend to be affluent), the magic number seems to be at least in the hundreds of thousands, but it can range into the millions.

The more information available about the audience that is adopting the emerging media, the more likely early ad funding is to occur. This audience data must be collected up front. The task cannot be left until later. If it is, there likely won’t be a “later.”

 

Enterprise Adoption Of Ad Tech Will Supercharge The Market

By Eric Picard (Originally published on AdExchanger 11/5/2013)

The appetite for ad technology is just beginning to appeal to new markets in new ways. Expect to see significant growth in the sector over the next five years as marketers and large publishers invest significantly in technology at a scale we’ve never seen.

The context for this shift: Ad technology is moving from a marketing or sales and operations expense to an enterprise-level IT investment. We’re now seeing very significant interest in this space by CIOs and CTOs at major corporations – beyond what we’ve seen in the past, which mainly came from the “digital native” companies, such as Google, eBay, Amazon, Yahoo, Facebook and Microsoft. Now this is becoming much more mainstream.

Historically, digital media was a very small percentage of advertising spending for large advertisers, and a small percentage of revenue for large, traditional media publishers.  But in the last two years, we have passed the tipping point. Let’s handle the two areas separately – starting with the marketer.

Marketers

First, let’s call the marketer by a slightly different name: the enterprise.

Large corporations, or enterprises, have invested massive amounts of money in IT over the last 30 years. Every major function within the enterprise has been through this treatment – from HR to supply chain, finance, procurement and sales to internally driven traditional direct marketing (the intersection of CRM and direct-marketing channels, such as mailing lists and even email marketing).

The great outlier here has been the lack of investment in advertising, which mainly has been driven by the fact that advertising is managed for the most part by agencies. Most marketing departments have allowed their media agency partners to take on the onus of sorting out how to effectively and efficiently spend their marketing budgets. And up until the past few years, digital marketing was a small percentage of spending for most major marketers.

Since there really hasn’t been much value in investing in advertising technology at the enterprise level for marketers on the traditional side, there was little driving change here. But as the percentage of the marketing budget on digital advertising has grown, and as the value of corporate data to digital advertising has grown, a significant shift in thinking has taken place.

Now we’ve got a way, through the RTB infrastructure – and, ultimately, through all infrastructure in the space – to apply the petabytes of corporate data that these companies own to drive digital advertising right down to the impression level. And we have mature infrastructures, bidders, delivery systems, third-party data and data pipelines,and mature technology vendors that can act on all this. None of this existed five years ago at scale.

Publishers

Just as the large marketers are enterprises, so are the large media companies that own the various online and offline publications that create advertising opportunities.

Until the last few years, the very largest of the traditional publishing conglomerates were still not paying much attention to digital media since it was a tiny fraction of overall revenue. But over the last few years there has been a significant shift as executives finally realized that despite the lack of revenue from digital as a channel, from a distribution standpoint, digital media is experiencing explosive growth. And ultimately all the traditional distribution channels – from print to television to radio – are all being subsumed into the digital channel.

You need to look no further than the people who have been hired into the major media companies in the last few years with titles like VP of revenue platforms, GM of programmatic and trading, director of programmatic advertising and VP of yield operations. These senior positions didn’t exist at these companies two years ago, and generally were areas reserved within the digital natives.

The fact that we’re seeing new focus on digital media, with both senior roles and significant investments in people and technology, means that we’re likely to see additional significant investment by these media enterprises over the next few years. I expect to see the shift happen here quickly since the consulting companies upon which they and most enterprises rely to lead these initiatives already have media and entertainment practices.

Suddenly major advertisers and publishers – who are all major enterprises – are looking at the opportunity to apply their significant IT expertise to marketing in a new way. So let’s talk about the way that IT evolved in other channels historically to try to understand what’s about to happen here.

The Evolution Of IT

A major corporation will typically hire large consulting firms with a vertical practice in the area they want to modernize. Note that the biggest consulting firms – we’ll use IBM and Accenture as examples here – have developed vertical practices around nearly every department, large initiative or focus area within an enterprise. Also note that wherever these consulting firms step in to build a practice, they assemble a recommended “stack” of technologies that can be integrated together and create a customized solution for the enterprise. One interesting thing: In nearly every case, there are significant open-source software components that are used within these “stacks” of technology.

When we look carefully at where they’ve developed practices that smell anything like marketing, they’re typically assembled around big data and analytics. There are obvious synergies between all the other vertical practices they’ve created and the intersection of using big data to inform marketing decisions with analytics, based on detailed analysis of other corporate data. So this isn’t a surprise. It also isn’t shocking that there are many major open-source software initiatives around big data, ranging from staples such as Hadoop to startups like MongoDB.

But nowhere in the digital advertising landscape do we see major open source initiatives. Instead we see the massively complex Lumascape ecosystem map, with hundreds of companies in it.

So when we look at the shift to enterprise IT for digital marketing, there are plenty of companies to plug into a “stack” of technologies and build a practice around. But there is very little in the way of open source, and no clear way to actually bind together all the vendors into a cohesive stack that can be used in a repeatable and scalable fashion.

We are seeing some significant consulting firms come into existence in this space, including Unbound Company and 614 Group. I’m certain we’ll see the big players enter the fray as they sniff out opportunity.

Who Will Win The Digital Media War?

By Eric Picard (originally published in AdExchanger October 17th, 2013)

Lately I’ve had many conversations about the digital advertising market and how it’s evolving.

The most-asked question: “Who will win the battle over digital advertising – Google, Facebook or Twitter?”

I’ve also recently been asked about other companies, such as LinkedIn and Adobe, and how well they’re positioned to beat “whomever.” And by “whomever,” everyone almost always means Google. But more often lately, I’m hearing about Facebook, too.

So, who’s going to win?

Well, it’s not so simple. I take a very different view of the market. I don’t believe there will ever be one winner in this space. Even from an ad-technology perspective, I don’t think all roads point to Google owning it all – although there’s little question that they dominate. And from a publisher perspective, Google is dominant in paid search but not in other areas.

I can hear your brain spinning right now. You’re thinking, “Wait – did you say Google is a publisher?”

Yes, I did. Google has leveraged a massive market share in paid search, and grown into other forms of advertising as well. But for some reason, people in our space don’t seem to think of Google as a publisher.

Google happens to be the biggest publisher of search – but, somehow, calling Google a search engine seems to mask for many people that Google is a publisher. They also are a publisher of maps with Google Maps. They publish video via YouTube. And they publish all sorts of other content related to the results of various vertical searches, including restaurant reviews and travel information.

Google’s also a technology company, and yet – amid all the excitement about various office applications, self-driving cars, balloon-based Wi-Fi and all the other efforts – they are primarily a publisher, one that makes almost all of its money from the sale of advertising. Even their massive DoubleClick business is in many ways really about building opportunities for more ad revenue flowing through their ad exchange and back to Google, tied to a percentage of media spending.

But even though they can almost legally be considered a monopoly, they are not the only publisher in search. Microsoft certainly hasn’t given up there. And beyond the two major publishers of search, there’s an entire ecosystem around paid search that Google can’t and won’t own. That opens up other opportunities.

A Range Of Opportunities – For Many Players

I see the market as a series of opportunities. Even if Google continues to be the dominant player across all forms of digital advertising, from a publisher or an ad-technology perspective, I don’t think that matters from a market perspective because the publisher space is far too fragmented for any one publisher to gain control. Any one publisher may dominate in one area, but won’t be a complete monopoly – not even in search. It’s even much less likely in other forms of media.

So when people talk about who’s going to “win” in advertising, I think it’s more complex than one winner and many losers. There are many opportunities to win here. And many of these markets are more than big enough for the “second-place” player to have a very big business indeed. In many cases, there will be a large number of big businesses in various verticals. Television is a great example of a market where there are many big players and no one player that has significantly dominated the market, at least not in the way we think of Google dominating search.

So what are the other areas we should be paying attention to? These areas could be very large – potentially as large as paid search – but at least as large as display ads or radio.

1. Consumer-Facing Social Media

Publishers: Obviously Facebook will dominate here. This means Twitter has the backup position in this market. Facebook is too far ahead for Twitter to come close any time soon. I think that Google+ is an outlier and could blow up at some point if Google keeps at it and really invests heavily, maybe in advertising Google+ rather than trying to gain share more organically.

Technology: There are tons of players, but nobody is dominant yet. And every major player wants to be the big gun here. I expect that, eventually, Google, Adobe and Salesforce will dominate, either through organic growth or acquisition. There are a lot of smaller players who could rise quickly depending on how innovative they prove and how good they are at executing.

Secondary Marketplaces: I think AppNexus will win. Others will play.

2. B2B Social Media

Publishers: Clearly, this belongs to LinkedIn. Google+, Facebook and Twitter will also play here, but it’s uncertain how much market penetration they’ll achieve. I’d guess that Twitter has a good opportunity to be bigger here than in the consumer space as a secondary player.

Technology: Again – too early to know. I like Rallyverse quite a lot, although they’re playing in several places here.

Secondary Marketplaces: Too early to be certain.

3.  Video / TV over IP

Publishers: Obviously Hulu is a standout. You can’t ignore YouTube, either. Netflix and Amazon are very focused, and Microsoft’s Xbox is super interesting. But video and television content over the Internet is very fragmented, and I don’t see one strong winner.

Technology: Freewheel seems to be getting tons of traction (quietly, too).

Secondary Marketplaces: Clearly Google’s got a good foothold because of its anchor-tenant relationship with YouTube. Tremor had a great IPO, and there are many players like TubeMogul, YuMe and Brightroll – but this space looks to be about as fragmented as the television ecosystem, or even display ads. Part of the reason is just that there’s a lot of demand and money floating out there looking to be spent on video advertising.

4. Mobile

Publishers: Mobile is not a media type. Well, sorta. But it’s not a media type that so far is significantly differentiated as one. I suppose you could point at Apple and Google (as leaders?) for their app and content marketplaces.

Technology: This part of the market is super fragmented.

Secondary Marketplaces: I’m looking forward to Google and AppNexus duking it out over this marketplace from the exchange point of view – but there are many ad networks in this space as well, including Millennial Media, which is clearly the powerhouse of the market.

5. Cross-Media Plays

Let me break out of my model for a moment and say that while the market has certainly fragmented into players focused on each of the various channels, I think we’re now starting to see a lot of investment in cross-media initiatives. These range from publishers to technology companies and marketplaces.

But the real interesting thing to me is that in the ad-technology space we’ve rarely seen the ability for companies to support multiple media types simultaneously and become a dominant player. That is changing.

Publishers: Google, Yahoo – yes, I said Yahoo – Microsoft, Amazon, Apple, AOL and a plethora of others are starting to gain real cross-media traction. I don’t see any one publisher dominating across media, but certainly there will be publishers who stand out because of their cross-media footprint.

Technology: Obviously Google stands out here. But watch out for AppNexus, which is really investing heavily in video, mobile and social to extend beyond its display roots.

Secondary Marketplaces: Again – I think it’s Google and AppNexus that are really poised to win here.

When will digital take over traditional media?

By Eric Picard (Originally published on iMediaConnection.com, September 12, 2013)

In 2005 I worked on a project to map the infrastructure used for all traditional media advertising and determine if there was an opportunity to inject the new modern infrastructure of online advertising into the mix. This was a broad look at the space — with the goal to see if any overlap in the buying or selling processes existed at all and if there was a way to subtly or explicitly alter the architecture of online advertising platforms to drive convergence.

If you think about it, this is kind of a no-brainer. Delivering tens or hundreds of billions of ads a day in real time with ad delivery decisions made in a few milliseconds is much harder than getting the contracts signed and images off to printing presses (print media) or ensuring that the video cassettes or files are sent over to the network, broadcaster, or cable operator by a certain deadline. And the act of planning media buys before the buying process begins isn’t very different between traditional media and digital.

I went and interviewed media planners and buyers who worked across media. I talked to publishers in print, TV, radio, out-of-home, etc. And I went and talked to folks at the technology vendor companies who supported advertising in all of these spaces. It was clear to me that converging the process was possible, and as I looked at how the various channels operated, it was also clear that they’d benefit significantly from a more modern architecture and approach.

But in 2005, the idea of digital media technologies and approaches being used to “fix” digital media was clearly too early. It would be like AOL buying Time Warner…Oh yeah, that happened. In any case, the likelihood of getting traditional folks to adopt digital media ad technology in 2005 was simply ludicrous.

And despite progress, and clearly superior technical approaches in digital (if lower revenue from the same content due to business model differences), there’s little danger of traditional and digital media ad convergence in the near term. This is actually a real shame because digital media now is stepping into a real renaissance from an advertising technology perspective.

Programmatic media buying and selling is clearly the future of digital, and I believe they will extend into traditional as well. And within programmatic, RTB is a clear winner (although not the only winner) in the space. The value proposition of RTB for the buyer is incredibly strong.  Buyers get to deliver ads only to the specific audiences they desire and on the specific publishers (or group of publishers) they want their ads associated with. While still mostly used for remnant media monetization, this is changing very fast.

Television is the obvious space to adopt digital media ad technology, and with terms like “Digital Broadcast,” “Digital Cable,” “IPTV,” and others, it would seem on the surface that we’re moments away from RTB making the leap from online display ads and digital video to television.

That’s not quite the case. While great strides are being made in executing on targeted television buys by fantastic companies like Simulmedia, Visible World, and others, this space is still not quite ready to make the transition to real-time ad delivery (what we think of as ad serving in the online space) at large, let alone RTB.

This is because the cable advertising industry is hamstrung by an infrastructure that is designed for throughput and scale of video delivery, which was absolutely not designed with the idea of real-time decisions at the set-top-box (STB) level in mind. Over the years we’ve seen video on demand (VOD) really take off for cable, but even there, where the video content is delivered via a single stream per STB, they didn’t design the infrastructure around advertising experiences. Even the newer players with more advanced and modern infrastructures and modern-sounding names like IPTV, such as Verizon’s FIOS solution, haven’t built in the explicit hooks and solutions needed to support real-time ad delivery decisions across all ad calls. That basically means that for the vast majority of ads, there’s no targeting whatsoever.

Some solutions like Black Arrow and Visible World have done the work to drop themselves into the cable infrastructure for ad delivery, but nobody has seen massive adoption at a scale that would let something happen at the national level. And the cable industry’s internally funded advanced advertising initiative — The Canoe Project — laid off most of its staff last year and has focused on delivering a VOD Clearinghouse to get VOD to scale across cable operators. So in 2013, we’re still not to the point where dynamic video advertising can be delivered on any television show during its broadcast, and even VOD doesn’t yet have a way to easily, cohesively, and dynamically deliver video advertising — let alone providing an RTB marketplace.

On the non-RTB side of programmatic buying and selling, I think we’ll see a lot of progress here in traditional media. Media Ocean has been doing their own flavor of programmatic for quite some time — in fact the Media Ocean name of the post-merger company was a product name within the Donovan Data Systems (DDS) portfolio that helped bind together the DDS TV Buying Product with a Television Network selling product and allowed buyers and sellers to transact on insertion orders programmatically for spot television. With Media Ocean’s new focus on digital media (which is getting rave reviews from folks I’ve talked to who have seen it), there’s little doubt in my mind that these products will extend over to the traditional side of the market and ultimately replace (or be the basis of new versions of) the various legacy products that allowed DDS to dominate the media buying space for decades.

If our industry can get to the point where executing media buys across traditional and digital share a common process until the moment where they diverge from a delivery perspective, I think the market overall will make great headway. And I’m bullish on this — I think we’re not far away but it won’t happen this year.

Programmatic Platforms vs. “Standard” Digital Platforms

By Eric Picard (Originally published on AdExchanger.com August 5th, 2013)

I’ve been struggling lately with some oddities in how the “programmatic” media space functions. Ad-tech infrastructure — both the “standard” digital infrastructure made up of publisher’s ad servers (DoubleClick for Publishers24/7 Open AdStreamAdtechOpenX, etc.) and the real-time bidding platforms that run alongside those legacy platforms — has drawn huge investment. But misunderstandings and false assumptions abound about how these technologies operate, their limitations and what types of businesses should use them.

My friend, Jed Nahum, wrote a great article last week about programmatic buying and selling, including the sometimes confusing ways in which we use the word “programmatic” because of the complexity we’ve created. What I loved about Jed’s article is that he laid out a taxonomy of four different ways the “programmatic advertising world” operates (or will soon operate):

  1. RTB/programmatic spot: The RTB world we all know and love.
  2. Deal ID/private marketplaces: Using the “RTB pipes” to execute buys that are similar to direct buys, but that aren’t guaranteed.
  3. Programmatic direct: Using non-RTB “pipes” to buy directly from publishers, including guaranteed buys previously supported only via a direct human sales relationship.
  4. Programmatic forward: The (still-to-come) extension of the Deal ID/private marketplace world to guaranteed/reserved buys over the RTB “pipes.”

I really like Jed’s taxonomy because it calls out the very real differences in how various constituents in our space operate. If I do a quick mapping of vendors to their various spaces here (and I’m bound to forget a few), you can see that the players are siloed in their approaches. Full disclosure: My company, Rare Crowds, sits across all of these boxes today – although we don’t have a bidder or an ad server. We sit above that layer and push into each of those various platforms, so in a sense we don’t compete with any of these companies, but would partner with any of them.

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The problem I have with this is that the vehicles to programmatically buy media are locked to the plumbing (technology layer) that supports them. And yet they’re all programmatic. That would be fine if we didn’t have this “programmatic forward” component at the bottom — the one that all the RTB folks are working toward.

I still stand my definition of programmatic as any method of buying or selling media that enables a buyer to complete a media purchase without human intervention from a seller. I’ll push forward by saying that — contrary to popular belief –the technology layer, the plumbing, is irrelevant to the channel.

When I talk to people from the programmatic-direct world, they argue they’re the logical path for managing guaranteed direct-media buys because they’re directly plugged into publishers’ platforms. But when I talk to the RTB folks, they make a very good argument about how they can expose publisher inventory “directly” between a buying platform and the publisher’s ad server with a check-box configuration setting — and that it’s better for buyers because they can apply all their first-party data to the buys and get the best of all worlds.

The reality is this: Both sides are “sort of” right. But, in the end, it just doesn’t matter. All the vendors will ultimately plug into each other and liquidity will flow. The programmatic-direct vendors, though, need to make sure that they don’t miss the value proposition of all the various partnerships they should be creating.

One of the most significant developments in our space in the last few years was the DoubleClick Ad Exchange’s rollout of dynamic allocation, the next-generation technology that replaces the previous AdMeld product. Essentially it’s a switch that sits between the exchange and DoubleClick for Publishers and makes real-time decisions about how to allocate inventory to the exchange and for guaranteed buys. Maxifier offers a very similar product that will work with other exchanges (which is also super important, but I give the nod to Google because of its scale).

The reason this matters is that publishers need a dynamic-allocation technology that regulates the decision about which line items get the impression. The yield increases are significant, especially those coming through the exchange.

Dynamic-allocation technologies level the playing field between the RTB players and the programmatic-direct players. Buyers will ultimately need to be able to support both channels. This is critical for decision-makers at agency trading desks or large technical advertisers with their own platforms, such as eBay or Amazon.

They need a way to rationalize when they should be doing dynamic buys, controlled at the impression level (RTB), and when they should be doing direct buys in advance.  Ideally, they need a system that sits above all of these various channels and allocates budget to them in advance, but that also monitors and optimizes how those budgets are allocated throughout the life of a campaign.

Regardless of what any one vendor will tell you, all the functionality of the current set of “legacy” ad-server technologies will be replicated in the RTB stack over the next few years. And the current lines that sit between those stacks will get blurrier. Anyone preaching any kind of secularism here is a bit suspect.

How arbitrage works in digital advertising today

By Eric Picard (Originally published on iMediaConnection.com July 11, 2013)

The idea that ad networks, trading desks, and various technical “traders” in the ad ecosystem are “arbitraging” their customers is fairly well understood. The idea that an intermediary of some kind sells ad inventory to a media buyer, but then buys it somewhere else for a lower price is a pretty basic reality in our industry. But what most of us don’t understand is how it gets done and especially how technically advanced firms are doing it.

So let’s talk about this today — how arbitrage is enacted by various constituents, and I’d love to hear some reactions in the comments about how marketers and media buyers feel about it, especially if they weren’t aware of how it was done. Note: There are many ways to do this; I’m just going to give you some examples.

Old school networks

Back in the day, ad networks would go to large publishers and negotiate low price remnant buys (wholesale buys) where they’d buy raw impressions for pennies on the dollar, with the rule being that the network could only resell those impressions without identifying the publisher (blind inventory resale).

The networks that have done this well traditionally apply some targeting capabilities to sell based on context/content and also audience attributes. But even this is all very old school. The more advanced networks even back in the old days employed a variety of yield optimization technologies and techniques on top of targeting to ensure that they took as little risk on inventory as possible.

RTB procurement

Many networks now use the exchanges as their primary “procurement” mechanism for inventory. In this world there’s very little risk for networks, since they can set each individual campaign up in advance to procure inventory at lower prices than they’ve been sold. There is a bit of risk that they won’t be able to procure inventory — i.e. there isn’t enough to cover what they’ve pre-sold. But the risk of being left holding a large amount of inventory that went unsold is much lower and saves money.

Once you mitigate that primary risk and then add in the ability to ensure margin by setting margin limits, which any DSP can do “off the shelf,” the risk in managing an ad network is so low that almost anyone can do it — as long as you don’t care about maximizing your margins. That’s where a whole new class of arbitrage has entered the market.

Technical arbitrage

There are many different ways that companies are innovating around arbitrage, but I’ll give you the baseline summarization so you can understand why many of the networks (or networks that advertise as if they’re some kind of “services based DSP”) are able to be successful today.

Imagine a network that has built an internal ad platform that enables the following:

  • Build a giant (anonymous) cookie pool of all users on the internet.
  • Develop a statistical model for each user that monitors what sites the network has seen them on historically on a daily/day-of-week basis.
  • Develop a historical model showing how much inventory on each site tends to cost in order to win the inventory on the exchange, perhaps even each individual user.
  • When you run a campaign trying to reach a specific type of user, the system will match against each user, then in the milliseconds before the bid needs to be returned, the network’s systems will determine how likely they are to see this user that day — and if they will find them on sites where historically they’ve been able to buy inventory for less money than the one they’re on at the moment.
  • If the algorithm thinks it can find that user for less money, it will either bid low or it will ignore the bid opportunity until it sees that user later in the day — when it probably can win the bid.

This kind of technology is now running on a good number of networks, with many “variations” on this theme — some networks are using data related to time of day to make optimization decisions. One network told me that it finds that users are likely to click and convert first thing in the morning (before they start their busy day), in mid-morning surfing (after they’ve gotten some work done), after lunch (when they’re presumably trying to avoid nodding off), and in the late afternoon before going home for the day. They optimize their bidding strategy around these scenarios either by time of day or (in more sophisticated models) depending on the specific user’s historical behavior.

You shouldn’t begrudge the networks based too much on this “technical arbitrage,” since all that technology requires a significant upfront investment. They’re still giving you access to the same user pool — but one question that nags at me is that they may be giving you that user on sites that are not great.

It also begs the question that if these very technical networks are buying their inventory on a per-impression basis, all the stories about fraud get me a little worried. A truly sophisticated algorithm that matches a unique ID should be able to see that those IDs are getting too many impressions to be human. But I haven’t done any analysis on this — it’s just a latent concern I have.

Life after the death of 3rd Party Cookies

By Eric Picard (Originally published on AdExchanger.com July 8th, 2013)

In spite of plenty of criticism by the IAB and others in the industry, Mozilla is moving forward with its plan to block third-party cookies and to create a “Cookie Clearinghouse” to determine which cookies will be allowed and which will be blocked.  I’ve written many articles about the ethical issues involved in third-party tracking and targeting over the last few years, and one I wrote in March — “We Don’t Need No Stinkin’ Third-Party Cookies” — led to dozens of conversations on this topic with both business and technology people across the industry.

The basic tenor of those conversations was frustration. More interesting to me than the business discussions, which tended to be both inaccurate and hyperbolic, were my conversations with senior technical leaders within various DSPs, SSPs and exchanges. Those leaders’ reactions ranged from completely freaked out to subdued resignation. While it’s clear there are ways we can technically resolve the issues, the real question isn’t whether we can come up with a solution, but how difficult it will be (i.e. how many engineering hours will be required) to pull it off.

Is This The End Or The Beginning?

Ultimately, Mozilla will do whatever it wants to do. It’s completely within its rights to stop supporting third-party cookies, and while that decision may cause chaos for an ecosystem of ad-technology vendors, it’s completely Mozilla’s call. The company is taking a moral stance that’s, frankly, quite defensible. I’m actually surprised it’s taken Mozilla this long to do it, and I don’t expect it will take Microsoft very long to do the same. Google may well follow suit, as taking a similar stance would likely strengthen its own position.

To understand what life after third-party cookies might look like, companies first need to understand how technology vendors use these cookies to target consumers. Outside of technology teams, this understanding is surprisingly difficult to come by, so here’s what you need to know:

Every exchange, Demand-Side Platform, Supply-Side Platform and third-party data company has its own large “cookie store,” a database of every single unique user it encounters, identified by an anonymous cookie. If a DSP, for instance, wants to use information from a third-party data company, it needs to be able to accurately match that third-party cookie data with its own unique-user pool. So in order to identify users across various publishers, all the vendors in the ecosystem have connected with other vendors to synchronize their cookies.

With third-party cookies, they could do this rather simply. While the exact methodology varies by vendor, it essentially boils down to this:

  1. The exchange, DSP, SSP or ad server carves off a small number of impressions for each unique user for cookie synching. All of these systems can predict pretty accurately how many times a day they’ll see each user and on which sites, so they can easily determine which impressions are worth the least amount of money.
  2. When a unique ID shows up in one of these carved-off impressions, the vendor serves up a data-matching pixel for the third-party data company. The vendor places its unique ID for that user into the call to the data company. The data company looks up its own unique ID, which it then passes back to the vendor with the vendor’s unique ID.
  3. That creates a lookup table between the technology vendor and the data company so that when an impression happens, all the various systems are mapped together. In other words, when it encounters a unique ID for which it has a match, the vendor can pass the data company’s ID to the necessary systems in order to bid for an ad placement or make another ad decision.
  4. Because all the vendors have shared their unique IDs with each other and matched them together, this creates a seamless (while still, for all practical purposes, anonymous) map of each user online.

All of this depends on the basic third-party cookie infrastructure Mozilla is planning to block, which means that all of those data linkages will be broken for Mozilla users. Luckily, some alternatives are available.

Alternatives To Third-Party Cookies

1)  First-Party Cookies: First-party cookies also can be (and already are) used for tracking and ad targeting, and they can be synchronized across vendors on behalf of a publisher or advertiser. In my March article about third-party cookies, I discussed how this can be done using subdomains.

Since then, several technical people have told me they couldn’t use the same cross-vendor-lookup model, outlined above, with first-party cookies — but generally agreed that it could be done using subdomain mapping. Managing subdomains at the scale that would be needed, though, creates a new hurdle for the industry. To be clear, for this to work, every publisher would need to map a subdomain for every single vendor and data provider that touches inventory on its site.

So there are two main reasons that switching to first-party cookies is undesirable for the online-ad ecosystem:  first, the amount of work that would need to be done; second, the lack of a process in place to handle all of this in a scalable way.

Personally, I don’t see anything that can’t be solved here. Someone needs to offer the market a technology solution for scalable subdomain mapping, and all the vendors and data companies need to jump through the hoops. It won’t happen in a week, but it shouldn’t take a year. First-party cookie tracking (even with synchronization) is much more ethically defensible than third-party cookies because, with first-party cookies, direct relationships with publishers or advertisers drive the interaction. If the industry does switch to mostly first-party cookies, it will quickly drive publishers to adopt direct relationships with data companies, probably in the form of Data Management Platform relationships.

2) Relying On The Big Guns: Facebook, Google, Amazon and/or other large players will certainly figure out how to take advantage of this situation to provide value to advertisers.

Quite honestly, I think Facebook is in the best position to offer a solution to the marketplace, given that it has the most unique users and its users are generally active across devices. This is very valuable, and while it puts Facebook in a much stronger position than the rest of the market, I really do see Facebook as the best voice of truth for targeting. Despite some bad press and some minor incidents, Facebook appears to be very dedicated to protecting user privacy – and also is already highly scrutinized and policed.

A Facebook-controlled clearinghouse for data vendors could solve many problems across the board. I trust Facebook more than other potential solutions to build the right kind of privacy controls for ad targeting. And because people usually log into only their own Facebook account, this avoids the problems that has hounded cookie-based targeting related to people sharing devices, such as when a husband uses his wife’s computer one afternoon and suddenly her laptop thinks she’s a male fly-fishing enthusiast.

3) Digital Fingerprinting: Fingerprinting, of course, is as complex and as fraught with ethical issues as third-party cookies, but it has the advantage of being an alternative that many companies already are using today. Essentially, fingerprinting analyzes many different data points that are exposed by a unique session, using statistics to create a unique “fingerprint” of a device and its user.

This approach suffers from one of the same problems as cookies, the challenge of dealing with multiple consumers using the same device. But it’s not a bad solution. One advantage is that fingerprinting can take advantage of users with static IP addresses (or IP addresses that are not officially static but that rarely change).

Ultimately, though, this is a moot point because of…

4) IPV6: IPV6 is on the way. This will give every computer and every device a static permanent unique identifier, at which point IPV6 will replace not only cookies, but also fingerprinting and every other form of tracking identification. That said, we’re still a few years away from having enough IPV6 adoption to make this happen.

If Anyone From Mozilla Reads This Article

Rather than blocking third-party cookies completely, it would be fantastic if you could leave them active during each session and just blow them away at the end of each session. This would keep the market from building third-party profiles, but would keep some very convenient features intact. Some examples include frequency capping within a session, so that users don’t have to see the same ad 10 times; and conversion tracking for DR advertisers, given that DR advertisers (for a whole bunch of stupid reasons) typically only care about conversions that happen within an hour of a click. You already have Private Browsing technology; just apply that technology to third-party cookies.

Which Type Of Fraud Have You Been Suckered Into?

By Eric Picard (Originally published by AdExchanger.com on May 30th, 2013)

For the last few years, Mike Shields over at Adweek has done a great job of calling out bad actors in our space.  He’s shined a great big spotlight on the shadowy underbelly of our industry – especially where ad networks and RTB intersect with ad spend.

Many kinds of fraud take place in digital advertising, but two major kinds are significantly affecting the online display space today. (To be clear, these same types of fraud also affect video, mobile and social. I’m just focusing on display because it attracts more spending and it’s considered more mainstream.) I’ll call these “page fraud” and “bot fraud.”

Page Fraud

This type of fraud is perpetrated by publishers who load many different ads onto one page.  Some of the ads are visible, others hidden.  Sometimes they’re even hidden in “layers,” so that many ads are buried on top of each other and only one is visible. Sometimes the ads are hidden within iframes that are set to 1×1 pixel size (so they’re not visible at all). Sometimes they’re simply rendered off the page in hidden frames or layers.

It’s possible that a publisher using an ad unit provided by an ad network could be unaware that the network is doing something unscrupulous – at least at first.  But they are like pizza shops that sell more pizzas than it’s possible to make with the flour they’ve purchased. They may be unaware of the exact nature of the bad behavior but must eventually realize that something funny is going on. In the same way, bad behavior is very clear to publishers who can compare the number of page views they’re getting with the number of ad impressions they’re selling.  So I don’t cut them any slack.

This page fraud, by the way, is not the same thing as “viewability,” which involves below-the-fold ads that never render visibly on the user’s page.  That fraudulent activity is perpetrated by the company that owns the web page on which the ads are supposed to be displayed.  They knowingly do so by either programming their web pages with these fraudulent techniques or using networks that sell fake ad impressions on their web pages.

There are many fraud-detection techniques you can employ to make sure that your campaign isn’t the victim of page fraud. And there are many companies – such as TrustMetrics, Double Verify and Integral Ad Science – that offer technologies and services to detect, stop and avoid this type of fraud. Foiling it requires page crawling as well as advanced statistical analysis.

Bot Fraud

This second type of fraud, which can be perpetrated by a publisher or a network, is a much nastier kind of fraud than page fraud. It requires real-time protection that should ultimately be built into every ad server in the market.

Bot fraud happens when a fraudster builds a software robot (or bot) – or uses an off-the-shelf bot – that mimics the behavior of a real user. Simple bots pretend to be a person but behave in a repetitive way that can be quickly identified as nonhuman; perhaps the bot doesn’t rotate its IP address often and creates either impressions or clicks faster than humanly possible. But the more sophisticated bots are very difficult to differentiate from humans.

Many of these bots are able to mimic human behavior because they’re backed by “botnets” that sit on thousands of computers across the world and take over legitimate users’ machines.  These “zombie” computers then bring up the fraudsters’ bot software behind the scenes on the user’s machine, creating fake ad impressions on a real human’s computer.  (For more information on botnets, read “A Botnet Primer for Advertisers.”) Another approach that some fraudsters take is to “farm out” the bot work to real humans, who typically sit in public cyber cafes in foreign countries and just visit web pages, refreshing and clicking on ads over and over again. These low-tech “botnets” are generally easy to detect because the traffic, while human and “real,” comes from a single IP address and usually from physical locations where the heavy traffic seems improbable – often China, Vietnam, other Asian countries or Eastern Europe.

Many companies have invested a lot of money to stay ahead of bot fraud. Google’s DoubleClick ad servers already do a good job of avoiding these types of bot fraud, as do Atlas and others.

Anecdotally, though, newer ad servers such as the various DSPs seem to be having trouble with this; I’ve heard examples through the grapevine on pretty much all of them, which has been a bit of a black eye for the RTB space. This kind of fraud has been around for a very long time and only gets more sophisticated; new bots are rolled out as quickly as new detection techniques are developed.

The industry should demand that their ad servers take on this problem of bot fraud detection, as it really can only be handled at scale by significant investment – and it should be built right into the core campaign infrastructure across the board. Much like the issues of “visible impressions” and verification that have gotten a lot of play in the industry press, bot fraud is core to the ad-serving infrastructure and requires a solution that uses ad-serving-based technology. The investment is marginal on top of the existing ad-serving investments that already have been made, and all of these features should be offered for free as part of the existing ad-server fees.

Complain to – or request bot-fraud-detection features from – your ad server, DSP, SSP and exchange to make sure they’re prioritizing feature development properly. If you don’t complain, they won’t prioritize this; instead, you’ll get less-critical new features first.

Why Is This Happening?

I’ve actually been asked this a lot, and the question seems to indicate a misunderstanding – as if it were some sort of weird “hacking” being done to punish the ad industry. The answer is much simpler:  money.  Publishers and ad networks make money by selling ads. If they don’t have much traffic, they don’t make much money. With all the demand flowing across networks and exchanges today, much of the traffic is delivered across far more and smaller sites than in the past. This opens up significant opportunities for unscrupulous fraudsters.

Page fraud is clearly aimed at benefiting the publisher but also benefitting the networks. Bot fraud is a little less clear – and I do believe that some publishers who aren’t aware of fraud are getting paid for bot-created ad impressions.  In these cases, the network that owns the impressions has configured the bots to drive up its revenues. But like I said above, publishers have to be almost incompetent not to notice the difference in the number of impressions delivered by a bot-fraud-committing ad network and the numbers provided by third parties like Alexa, Comscore, Nielsen, Compete, Hitwise, Quantcast, Google Analytics, Omniture and others.

Media buyers should be very skeptical when they see reports from ad networks or DSPs showing millions of impressions coming from sites that clearly aren’t likely to have millions of impressions to sell.  And if you’re buying campaigns with any amount of targeting – especially something that should significantly limit available inventory such as Geo or Income– or with frequency caps, you need to be extra skeptical when reviewing your reports, or use a service that does that analysis for you.