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.

Why dynamic creative has bounced back from failure

By Eric Picard (Originally published on iMediaConnection October 14th, 2013)

Back in 1999 (when the moon did not have a moonbase Alpha, nor did an explosion send the moon rocketing across the cosmos — a reference for old-timers like me) while at my last startup, Bluestreak, we started experimenting with dynamic creative.

The idea was that there were e-commerce companies with thousands of products available online, and that based on location we should be able to test and optimize which products led to the most clicks and purchases. Over the next few years, we worked with several customers to experiment with this. We ultimately ran ads with several publishers that would rotate through a list of products, and we used our creative optimization technology to determine which combination of offers was getting the best results (based on clicks, interactions, or conversions).

It turned out that there were various combinations of location (publisher) and product that worked much better than others, and the tests were successful. But the question was really about matters of degrees. We saw significant improvements in results, and we developed great technology that supported all this. But after the bottom dropped out of the market in 2000 and 2001 and the price of inventory dropped significantly, the improvements in performance stopped mattering as much.

Essentially, the price of inventory was so low that it was cheaper to just run much higher volumes of unoptimized ads than to pay for optimization service.

But I knew that creative optimization and dynamic creative would have its time and place. Either the impact of the creative optimization would drive significantly better results, the price of inventory would come back up, or we’d be able to optimize the offers based on user targeting rather than just by publisher.

Creative optimization and dynamic creative dropped out of the industry for eight to 10 years, but it came screaming back. As I guessed, the major driver was targeting based on user data. And over the past few years, the growth of real-time bidding and audience targeting has led to significant improvements in dynamic creative and optimization.

There are now several significant companies that have built their business around the idea of optimizing the offer shown to users based on their profiles, including a lot of retargeting. They build advertising campaigns that are driven by databases — ones that pull together the creative in ways that include hundreds or thousands or even millions of possible combinations. The best offer is selected based on a variety of criteria, including audience targeting attributes such demographics, behavioral data, and retargeting data. This information is extensively available and can be used to drive significantly better optimization than just location.

We all know that with real-time bidding and ad exchanges, ads can be targeted based on this kind of data. And we all know that with basic tracking of impressions, clicks, and conversions, bid prices in ad exchanges can be adjusted to optimize results based on the number of clicks or conversions. But dynamic creative optimization can take things to the next level. Using all of these technologies and techniques in combination can significantly drive up ROI. The only question is how many different products, offers, or options are available for optimization purposes.

The more opportunities to adjust the creative — especially if those products or offers can be somehow predicted to match against different audiences’ preferences or interests — the more likely the user is to act.
Read more at http://www.imediaconnection.com/content/35170.asp#sxRJhl1kvggxUiAe.99

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.

Why the local ad opportunity remains unsolved

By Eric Picard (Originally published on AdExchanger.com, September 3, 2013)

Local advertising is the largest pool of dollars in the US advertising industry, but is also by far the most fragmented and complex marketplace.

EMarketer’s numbers below are fascinating. They show clearly that local advertising is massively larger than digital media overall, and while traditional local ad spending, at $109 billion in 2012, seems to be stagnating (I’m not sure I buy that by the way – I’ve seen charts like this before that expect local traditional to stagnate but it hasn’t), that pool of dollars is double the next largest media. This chart expects local digital to double in size by 2017, where it would sit in the same magnitude as the big-league spending areas, including display ads, search and television.

graph1

The problem with local as a category is that it’s a cross-section of every other media, including television, radio, print, digital and a variety of other media types. And the spending is wildly sliced up across many more advertisers than national media. In national media, roughly 9,000 advertisers make up more than 90% of spending across all media. In local, there are millions of businesses spending money. This points to a significant problem scaling spending, especially on the supply side of the market.

Local Advertising Eludes Large Players

Many companies over the years have taken a run at local in the digital space. They range from companies feeding the paid search listings with local business ads to local offers through companies like Groupon and media efforts like Patch that push digital news at the local level while driving ad sales at the national level. There have been hundreds, if not thousands, of companies dashed upon the shores of digital local for every company that’s had some measure of success. This isn’t shocking – startups have spectacular flameout rates – but it is clearly a space with unique hurdles that few have figured it out. Even those we could consider successful, such as Groupon, are widely scrutinized and criticized when it comes to how they’ll scale their business.

There are few models in digital that have scaled across large numbers of media buyers. The rule has been for the most part that other than paid search, there have been only marketplaces that scale on the supply side. Paid search has roughly 500,000 active advertisers participating in the various marketplaces – the main players today are Google and Bing. Google has done a great job of leveraging that advertiser set to apply their combined demand across other marketplaces, but even adSense is a comparatively small pool of spending compared to paid search. So the biggest game in town hasn’t conquered local advertising yet – and they seem far from doing so still, although much closer than in the past.

But there is already a huge amount of money spent on local advertising – with millions of participating companies and thousands of competing publishers. It’s a business that’s been in place for hundreds of years, but only in the last decade has it really suffered. In basic media theory we see that where audiences concentrate, media dollars will flow. Generally the theory is that media dollars flow in some proportion to the amount of time spent with those media. And where those things are out of whack, analysts talk about “upside opportunity.” Mary Meeker’s frequently updated deck talks about the disproportionate time spent on digital media vs. the dollars spent as an example of the opportunity in digital (lately she focuses a lot on mobile).

graph2

What I love and hate about this analysis is that while TV has always been a fairly even match against time and dollars spent and, until the last 10 years, radio was similarly matched, there’s always been a strange outlier on this deck. Print media has always looked basically like it does on this chart. This disparity is generally used by analysts to suggest that print media is doomed.

The problem with that analysis is that it’s deeply flawed and doesn’t take into account the reasons why print has such a disparity. When you dig into newspapers, this disparity is even greater. And the more locally you dig in, the greater the disparity – with local newspapers disproportionally getting more dollars than time spent.

The Art Of Selling Media

The reason for this is so simple that it’s rather shocking. My friend Wayne Reuvers, who founded LiveTechnology (a company most have never heard of because it focuses on local traditional media creative production and operates behind the scenes) is the most expert person I know on local media.

One of my favorite quotes of his: “National media is bought, local media is sold.”

What he means is that local advertising dollars are spent mostly by non-professionals, usually someone working within the local business. And as any local business owner will tell you, local media providers trying to sell advertising and marketing opportunities inundate them with sales calls.

National media salespeople generally don’t go out and pitch ad opportunities to media buyers, they respond to RFPs. While there’s plenty of outreach from sell side to buy side, it’s mainly evangelical – making sure the buyers understand what the publisher has to offer, often not a direct business pitch with an expectation of dollars on the line. This is maybe not so true for ad networks, but for publishers it’s generally true.

Newspapers are a category that has been around for hundreds of years, and are the oldest of the local media. The models are mature and extremely efficient. When I’ve talked to local businesses about how they spend advertising dollars and why they spend so much on newspapers compared to the other forms of media, they’ve generally said, “My sales rep at the paper is great, he or she knows me and knows what I need. It’s super easy to execute a buy there, they do almost all the work for me. They’ll even do the creative for me. I just need to pay them money.” Changing the offer or creative in newspaper buys is also easy, so if the buyer needs to focus sales on a loss leader product or have a new promotion, an ad change can be made in a day or two.

Local businesses often find the costs of television spots so high that they can’t be justified. And when they’ve tried to buy display advertising from big publishers, nobody returned their calls. Paid search works well for some businesses, but not so much for others. The only other place where local businesses consistently spend money is on yellow pages. Not surprisingly, this is another place where they are sold ad space constantly with reps who are frequently in touch and educating them on new ways listings are being pushed to digital media.

Reuvers believes that newspapers have dropped the ball in the move to digital. He calls newspapers the first local search engines, and has been so evangelical about their opportunity that he published a manifesto about five years ago to push local newspapers toward a winning model. It is a fascinating read – if a bit out of date – and basically says newspapers should own the space.

Tackling The Local Digital Conundrum

I believe a successful local play for digital dollars must include the following:

1. Local Salespeople

These salespeople should focus on the community and form relationships with local businesses, meaning both small and medium-sized mom-and-pop businesses and local locations or branches of national or regional companies. These national/local companies spend 80% of local ad dollars but have wide discretion about where they spend those dollars. When companies try to run at local with a national sales force, they often fail.

2. Self-Service

Local business owners without a lot of technical skills need streamlined ways to spend dollars in a self-service and lightly assisted way. Scale will come for those who figure out self-service, but finding a way for scalable assisted buying is critical to success.

3. Easy Updating

Local businesses need simple ways to update their advertising or offer based on what works for them. This may take the form of updating the creative message or changing the format. While not deeply analytical on what advertising works, most local businesses are surprisingly astute at understanding what works.

National digital folks tend to discount how well these local businesses understand the effectiveness of their ad dollars. Few local businesses can afford to waste ad dollars, so they are pretty careful about their spending.

That said, they have limited venues to spend money on so they generally can figure it out without much work. Groupon figured out the hard way that local businesses are not stupid about the economics of marketing. There has been a lot of backlash among businesses toward any sense of being taken advantage of, strong-arm tactics or salespeople who don’t understand their business.

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.

tableforpicardstory

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.

Why no one can define “premium” inventory

By Eric Picard (Originally published on iMediaConnection.com on June 17th, 2013)

What is premium inventory? The simple answer is that it’s inventory that the advertiser would be happy to run its advertising on if it could manually review every single publisher and page that the ad was going to appear within.

When buyers make “direct” media buys against specific content, they get access to this level of comfort, meaning that they don’t have to worry about where their media dollars end up being spent. But this doesn’t scale well across more than a few dozen sales relationships.

To address this problem of scale, buyers extend their media buys through ad networks and exchange mechanisms. But in this process, they often lose control over where their ads will run. Theoretically the ad network is acting as a proxy of the buyer in order to support the need for “curation” of the ad experience, but this clearly is not usually the case. Ad networks don’t actually have the technology to handle curation of the advertising experience (i.e., monitoring the quality of the publishers and pages they are placing advertising on) at scale any more than the media buyer does, which leads to frequent problems of low quality inventory on ad networks.

Now apply this issue to the new evolution of real-time bidding and ad exchanges. A major problem with buying on exchanges is that the curation problem gets dropped back in the laps of the buyers across more publishers and pages than they can manually curate, which requires a whole new set of skills and tools. But the skills aren’t there yet, and the problem hasn’t been handled well by the various systems providers. So the agencies build out trading desks where that skillset is supposed to live, but the end results of the quality are highly suspect as we’re seeing from all the recent articles on fraud.

So the true answer to this conundrum of what is premium must be to find scalable mechanisms to ensure that a brand’s quality goals for the inventory it is running advertising against are met.
The market needs to be able to efficiently execute media buys against high-quality inventory at media prices that buyers are comfortable paying — if not happy to pay.

The definition of “high quality” is an interesting problem with which I’ve been struggling. Here’s what I’ve come up with: Every brand has its own point of view on “high quality” because it has its own goals and brand guidelines. A pharma advertiser might want to buy ad inventory on health websites, but it might want to only run on general health content, not content that is condition specific. Or an auto advertiser might want to buy ad inventory on auto-related content, but not on reviews of automobiles.

Most brands obviously want to avoid porn, hate speech, and probably gambling pages — but what about content that is very cluttered with ads or where the page layout is so ugly that ads will look like crap? Or pages that are relatively neutral — meaning not good, but not horrible?

Then we run into a problem that nobody has been willing to bring up broadly, but it’s one that gets talked about all the time privately: Inventory is a combination of publisher, page, and audience.

How are we defining audience today? There’s blended data such as comScore or Nielsen data, which use methodologies that are in some cases vetted by third parties, but relatively loosely. There’s first-party data such as CRM, retargeting, or publisher registration data, which will vary broadly in quality based on many issues but are generally well understood by the buyer and the seller. And there’s third-party data from data companies. But frankly, nobody is rating the quality of this data. Even on a baseline level, there are no neutral parties evaluating the methodology used from a data sciences point of view to validate that the method is defensible. And as importantly, there is no neutral party measuring the accuracy of the data quantitatively (e.g., a data provider says that this user is from a household with an income above $200,000, but how have we proven this to be true?).

When we talk about currency in this space, we accept whatever minimum bar that the industry has laid down as truth via the Media Rating Council, hold our nose, and move forward. But we’ve barely got impression guidelines that the industry is willing to accept, let alone all of these other things like page clutter and accuracy of audience data.

And even more importantly, nobody is looking at all the data (publisher, page, audience) from the point of view of the buyer. And as we discussed above, every buyer — and potentially every campaign for every brand — will view quality very differently. Because the skillset of measuring quality is in direct competition with the goal of getting budgets spent efficiently — or what some might call scale — nobody wants to talk about this problem. After all, if buyers start getting picky about the quality of the inventory on any dimension, the worry is that they might reduce the scale of inventory available to them. The issues are directly in conflict with each other. Brand safety, inventory quality, and related issues should be handled as a separate policy matter from media buying, as the minimum quality bar should not be subject to negotiation based on scale issues. Running ads on low-quality sites is a bad idea from a brand perspective, and that line shouldn’t be crossed just to hit a price or volume number.

So instead we talk about the issue sitting in front of our nose that has gotten some press: fraud. The questions that advertisers are raising about our channels center around this concern. But the advertisers should be asking lots of questions about the broader issue — which is, “How are you making sure that my ads are running on high-quality inventory?” Luckily there are some technologies and services on the market that can help provide quality inventory at scale, and this area of product development is only going to get better over time.

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.

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