Category Archives: Online Media

The Digital Advertising Industry Needs An Open Ecosystem

By Eric Picard (Originally published on AdExchanger Tuesday, November 4th, 2014)

Thanks to amazing new offerings from Facebook, Google, Amazon and others on deeply connected identity and tracking solutions, we are seeing two major developments. For the first time, connected identities across entire populations are available for targeting, tracking, reporting and analytics. But these identity pools exist within walled gardens, siloed to just one provider.

From a tactical and strategic point of view, I completely understand why companies create these walled-garden identity solutions. And to some extent, they will open their walls – metaphorically allowing outside vendors and partners to enter through checkpoints, accompanied by security and wearing clearly labeled badges. Nobody can fault a company like Facebook or Google for being careful about allowing entrée to their walled gardens. The potential for a PR backlash is significant, and that could cause the overall value of their offering to decline. So yes – it’s good to be cautious.

But it does create a significant issue for every publisher outside the top five or so because their first-party data pool is limited to the activity on their own site or apps. They don’t get access to cross-site activity, nor do they have a way to compete with the efforts of the biggest players on their own. It will be hard for publishers – even the large ones – to resist the momentum that will build to plug into these walled gardens, forcing publishers to effectively commoditize themselves in exchange for access to identity, targeting and analytics data.

I’ve long been a proponent of open approaches in the ad-tech space, including open source, open architecture or open APIs. I also am a big fan of well-considered and coordinated industry or consortium efforts. I believe that efforts like OpenRTB, which is pushing for an open API standard for real-time bidding, will be key to helping the industry grow.

Open efforts like this help ensure that the biggest players don’t create huge competitive moats like we saw with paid search, where Google AdWords’ creative, functionality and APIs became the effective industry standard. As a result, any time Google makes any change, all other paid search players must immediately copy Google because of its massive dominance in this area.

Even the biggest players should support these open initiatives because regardless of any disproportionate boost one or two players may get, we’re in a massive growth phase and an open approach has proven a better way to expand industries and sectors. Building significant traction is easier with scale – and by pooling scale, the whole space has the opportunity to accelerate growth.

That said, it’s highly unlikely that Google and Facebook will take a completely open approach on their key initiatives. For one, they have enough scale to catalyze efforts and markets on their own. But more importantly, it’s not in their self-interest to be open. Remaining closed gives them opportunity to maintain control and position in the market while marginalizing smaller players in the ecosystem.

I predict that we will see more industry consortiums created around areas like identity, directly in response to the very large walled gardens that are being built now. It’s really the only way that everyone else in the industry can protect against commodification and ensure a level playing field.

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Programmatic’s place at the top of the marketing funnel

By Eric Picard (Originally Published in iMedia – October 11, 2014)

For decades, modern marketers have developed significant marketing plans with detailed analysis of target audiences. Often before products are designed, significant amounts of market research have been developed and applied against the product or service development process.

When a brand decides to spend millions of dollars to create a product or service, it typically then spends tens to hundreds of thousands of dollars on market research and product planning to get ready to launch it.  And then hundreds of thousands to millions of dollars to market the product.

Most of that market research and product strategy folds over into the marketing plan. And as part of that process, typically very detailed marketing personas are created — sometimes a handful, sometimes more than a dozen. These marketing personas are decomposed into the marketing plan and drive many of the media mix decisions that are used to divvy up budget among channels. And often these do get distributed to the media agency as part of the marketing plan’s translation into media planning and strategy.

But in my experience, it is fairly common that by the time the media buyer gets the media plan from the planners, the marketing personas have been stripped off. And this is even more true when we bring programmatic media into view. As an example, consider a conversation I had this past year with a media buyer at a major trading desk.

This trading desk handles the media buying for a major home improvement retailer. And when I talked with the trading desk buyer about how the company approaches this customer’s media buys over its DSP partner, the buyer looked a little puzzled. To that person, it was about only two things:

  • Buying the “home improvement” segment
  • Setting the rest of the budget to optimize spend against CPA on its web pages and letting the DSP figure the rest out

The problem with this approach is that it’s extremely one dimensional — and loses much of the value that exists within the systems used. It’s like using an F-16 to commute to work. Or an aircraft carrier to run to the store.

I haven’t seen the marketing plan for the client, but I can imagine (having seen a lot of them over the years) that the retailer has several different ones. I’ll make up a few that probably exist in part, and explain how I’d have approached the campaign using a DSP.

Persona 1: Reggie is a 28-year-old single male who lives in a major metropolitan area in a condo that he owns. He makes more than $50,000 a year and mostly shops at the client’s stores to buy décor items, fans, DIY project materials, and probably will buy things like air conditioners, painting supplies, hand tools, etc.

Personas 2 and 3: Sophie is a 35-year-old stay-at-home mother who lives in the suburbs of a major metropolitan area and is married to Tim, a 35-year-old executive who works in the city and commutes. Together they own a house that is more than 4,000 square feet and has at least half an acre of land. Tim is a weekend DIY warrior, who takes on various home improvement projects. He’s likely to take on light construction projects, buying building materials, painting materials, plumbing and electrical, and lots of landscaping tools such as riding mower, blowers, etc. Sophie is an avid gardener who buys numerous plants and gardening materials, and takes frequent courses on design and gardening at the store.

Persona 4: Arthur is 65 years old. He is retired, lives in a modest home in the suburbs, which he owns outright. He is in the process of getting ready to sell the house as he and his wife are looking to move to a smaller place or a retirement community. But he has three adult children who own homes nearby, and he frequently putters and does projects around their houses. He’s likely to buy building and painting materials.

Although I just made up these personas, they’re fairly typical of the kinds of personas I have seen over my career — if anything, they’re a bit light. Additional information that would typically accompany a persona includes the numbers of each of these personas that exist in each DMA in the U.S., perhaps even broken down by ZIP code within each DMA. And then marketing teams typically will use whatever tools are at their disposal to begin matching against mechanisms like PRISM clusters and do some media mix modeling about how to reach these audiences.

At the handoff to media agency partners for digital media, the planners at that point begin using various tools to determine what sites have traffic that matches their target audiences, and an overall media plan and strategy is devised.

Once the plan is handed off to media buyers and their trading desk partners, the thinking is usually quite distilled. Buyers going directly to publishers will send over an RFP that simplifies the media plan (they may also send the media plan) for sending to publishers. They then wait to hear back regarding what inventory is available. The trading desk partners typically decide what audience attributes align against available data segments for their goals.

Now let’s go back to the example I used above about the trading desk with a major client in the home improvement retail space. Given its customer personas, I’d have recommended a few other ways to engage and find audiences.

Perhaps it could target users who own homes of a certain size or homeowners who have been in their home for a certain number of years. It could target each of these segments by age and geography. It could differentiate both creative and offer by each of these. It could vary what products to highlight in its advertising based on some of the criteria, such as age, gender, and other elements. It could target households with children differently than households with adult children not living in the home. It could even target based on the age of children, assuming parents of college age students might be moving kids into apartments or dorms at the end of summer or fall. Or it could target urban apartment dwellers with fans in the summer and suburban homeowners with leaf blowers in the early fall, snowblowers in the late fall, and lawnmowers in the early spring.

In programmatic, we far too often fall into the trap of only feeding the portion of the purchase funnel that is focused only on CPA at low costs of media plus data. As a market, we need to expand how we see programmatic media and really try to dig into the market for data and the use of sophisticated DSP platforms.

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.

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.”

 

The fundamental disconnect between buyers and sellers

By Eric Picard (Originally Published on iMedia – November 20, 2013)

If we break down the way that buyers and sellers view the world from an advertising perspective, the buyer wants to reach a specific audience on quality publications. And the seller wants to sell as much inventory as possible at the highest price.

To these ends, each party has built their own set of processes, technologies, and methodologies. Historically, media buyers would come up with a plan for reaching ideal target audiences, identify publishers that match brand goals and have access to the target audiences, and then send RFPs over to those publishers. Once buyers passed along the RFP, control was largely out of their hands. Buyers could say yes or no to things, they could ask for clarification, and they could negotiate price. But the control over exactly which audience they reach or what pages their ads land on have not been in their control. That has reverted back to the publisher’s sales, account, and operations teams.

Publisher sales organizations, meanwhile, have spent an immense amount of time and effort coming up with methods of “packaging” inventory to ensure the most sales, at the highest price. They have created significantly complex packages — with combinations of highly desirable and aligned inventory to an RFP — with less aligned and less desirable inventory that they require the buyer to take in order to get the inventory they really want.

In conversations with media buyers, I’ve been told that they see their job as “forcing publishers to blow up packages and unbundle the bad stuff from the good stuff.” This tension between buyer and seller can be quite intense — because their goals are generally not seen as aligned. There is a problem of “information asymmetry” in this world, meaning that publishers have all the information about both the buyer’s goals and the publisher’s own inventory and audiences. Ultimately they package that inventory without much input from the buyer other than the original RFP and media plan. Buyers have very little information in this world and rely on the publisher to interpret the buyer’s goals properly and to deliver what they’ve agreed to.

Over in RTB land, media buyers have much more control. In this world, the “information asymmetry” goes in the other direction. Within a DSP or other buying tool, the media buyers specify the audiences they want to reach and the kinds of inventory that are acceptable — even down to creation of a white list of which publishers are acceptable. They use inventory quality vendors, verification vendors, data providers, and all sorts of techniques to gain control over the buying process.

In this world, publishers add very little value (basically none) to the buying process, and they exist with absolute data asymmetry. Not only do they not know why their inventory is being bought (they don’t get an RFP or media plan), but they also often don’t even know who is buying their inventory. They maintain very little control over the selling process in this circumstance, which rightly makes them nervous about RTB.

As the technologies and markets evolve, a new process needs to be developed where publishers and buyers can collaborate. This process must allow publishers to gain insight into the goals of the buyers such that they can make good decisions about where to invest in building content — content that attracts the kinds of audiences that buyers want to reach. And buyers need access to data that publishers have about their audiences (which they don’t normally make available to generic ad exchange buys) that can be bound together with inventory via private exchanges or even programmatic direct technologies. So between the buyer and the seller, we can come together with a strong handshake that drives the right kind of symmetry of information — one that drives the right business outcomes for everyone involved.

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.

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.

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.