Dynamic Real Time Segmentation

What-is-Real-Time-MarketingThe term “real time” is bandied about in the ad technology space almost as heavily as the word “programmatic.”

Years later, the meaning of programmatic is finally starting to be realized, but we are still a few years away from delivering truly real-time experiences. Let me explain.

Real-Time Programmatic

The real-time delivery of targeted ads basically comes down to user matching. Here is a common use case: A consumer visits an auto site, browses a particular type of minivan, leaves the site and automatically sees an ad on the very next site he or she visits. That’s about as “real-time” as it gets.

How did that happen? The site updated the user segment to include “minivan intender,” processed the segment immediately and sent that data into a demand-side platform (DSP) where the marketer’s ID was matched with the DSP’s ID and delivered with instructions to bid on that user. That is a dramatic oversimplification of the process but clearly many things must happen very quickly – within milliseconds – and perfectly for this scenario to occur.

Rocket Fuel, Turn and other big combo platforms have an advantage here because they don’t need to match users across an integrated data-management platform (DMP) and DSP. As long as marketers put their tags on their pages and stay within the confines of a single execution system, this type of retargeting gets close to real time.

However, as soon as the marketer wants to target that user through another DSP or in another channel, user matching comes back into play. That means pushing the “minivan intender” ID into a separate system, but the “real-time” nature of marketing starts to break down. That’s a big problem because today’s users move quickly between channels and devices and are not constrained by the desktop-dominated world of 10 years ago.

User matching has its own set of challenges, from a marketer’s ability to match users across their devices to how platforms like DMPs match their unique IDs to those of execution platforms like DSPs. Assuming the marketer has mapped the user to all of his or her device IDs, which is a daunting challenge, the marketer’s DMP has to match that user as quickly as possible to the execution platform where the ads are going to be targeted and run.

Let’s think about how that works for a second. Let’s say the marketer has DMP architecture in the header of the website, which enables a mom to be placed in the “minivan” segment as soon as the page loads. After processing the segment, it must be immediately sent to the DSP. Now the DSP has to add that user (or bunch of users) to their “minivan moms” segment. If you picture the internet ID space as a big spreadsheet, what is happening is that all the new minivan moms are added to the DSP’s big existing table of minivan moms so they are part of the new targeting list.

Some DSPs, such as The Trade Desk, TubeMogul and Google’s DBM, do this within hours or minutes. Others manage this updating process nightly by opening up a “window” where they accept new data and process it in “batches.” Doesn’t sound very “real-time” at all, does it?

While many DMPs can push segments in real time, the practical issue remains the ability of all the addressable channels a marketer wants to target to “catch” that data and make it available. The good news is that the speed at which execution channels are starting to process data is increasing every day as older ad stacks are re-engineered with real-time back-end infrastructure. The bad news is that until that happens, things like global delivery management and message sequencing across channels will remain overly dependent upon how marketers choose to provision their “stacks.”

The Future Is Dynamic

Despite the challenges in the real-life execution of real-time marketing, there are things happening that will put the simple notion of retargeting to shame. Everything we just discussed depends on a user being part of a segment. I probably exist as a “suburban middle-aged male sports lover with three kids” in a variety of different systems. Sometimes I’m an auto intender and sometimes I’m a unicorn lover, depending on who is using the family desktop, but my identity largely remains static. I’m going to be middle aged for a long time, and I’m always going to be a dad.

But marketers care about a lot more than that. The beer company wants to understand why sometimes I buy an ice-cold case of light beer (I’m about to watch a football game, and I might drink three or four of them with friends) and when I buy a six-pack of their craft-style ale (I’m going to have one or two at the family dinner table).

The soda company is competing for my “share of thirst” with everything from coffee to the water fountain. They want to know what my entry points are for a particular brand they sell. Is it their sports drink because I’m heading to the basketball court on a hot day, or is it a diet cola because I’m at the baseball game? The coffee chain wants to know whether I want a large hot coffee (before work) or an iced latte macchiato (my afternoon break).

This brings up the idea of dynamic segmentation: Although I am always part of a static segment, the world changes around me in real time. The weather changes, my location changes, the time changes and the people around me change constantly. What if all of that dynamic data could be constantly processed in the background and appended to static segments at the moment of truth?

In a perfect world, where the machines all talked to each other in real time and spoke the same language, this might be called real-time dynamic segmentation.

This is the future of “programmatic,” whatever that means.

[This originally appeared in AdExchanger on 8/31/2016]

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Match Game 2015

 

Match game

Ask me what my match rates are. I have no clue, and neither do you.

 

If you work in digital marketing for a brand or an agency, and you are in the market for a data management platform, you have probably asked a vendor about match rates. But, unless you are really ahead of the curve, there is a good chance you don’t really understand what you are asking for. This is nothing to be ashamed of – some of the smartest folks in the industry struggle here. With a few exceptions, like this recent post, there is simply not a lot of plainspoken dialogue in the market about the topic.

Match rates are a key factor in deciding how well your vendor can provide cross-device identity mapping in a world where your consumer has many, many devices. Marketers are starting to request “match rate” numbers as a method of validation and comparison among ad tech platforms in the same way they wanted “click-through rates” from ad networks a few years ago. Why?

As a consumer, I probably carry about twelve different user IDs: A few Chrome cookies, a few Mozilla cookies, several IDFAs for my Apple phone and tablets, a Roku ID, an Experian ID, and also a few hashed e-mail IDs. Marketers looking to achieve true 1:1 marketing have to reconcile all of those child identities to a single universal consumer ID (UID) to make sure I am the “one” they want to market to. It seems pretty obvious when you think about it, but the first problem to solve before any “matching” tales place whatsoever is a vendor’s ability to match people to the devices and browser attached to them. That’s the first, most important match!

So, let’s move on and pretend the vendor nailed the cross-device problem—a fairly tricky proposition for even the most scaled platforms that aren’t Facebook and Google. They now have to match that UID against the places where the consumer can be found. The ability to do that is generally understood as a vendor’s “match rate.”

So, what’s the number? Herein lies the problem. Match rates are really, really hard to determine, and they change all the time. Plus, lots of vendors find it easier to say, “Our match rate with TubeMogul is 92%” and just leave it at that—even though it’s highly unlikely to be the truth. So, how do you separate the real story from the hype and discover what a vendor’s real ability to match user identity is? Here are two great questions you should ask:

What am I matching?

This is the first and most obvious question: Just what are you asking a vendor to match? There are actually two types of matches to consider: A vendor’s ability to match a bunch of offline data to cookies (called “onboarding”), and a vendor’s ability to match a set of cookie IDs to another set of cookie IDs.

First, let’s talk about the former. In onboarding—or matching offline personally identifiable information (PII) identities such as an e-mail with a cookie—it’s pretty widely accepted that you’ll manage to find about 40% of those users in the online space. That seems pretty low, but cookies are a highly volatile form of identity, prone to frequent deletion, and dependent upon a broad network of third parties to fire “match pixels” on behalf of the onboarder to constantly identify users. Over time, a strong correlation between the consumer’s offline ID and their website visitation habits—plus rigor around the collection and normalization of identity data—can yield much higher offline-to-online match results, but it takes effort. Beware the vendor who claims they can match more than 40% of your e-mails to an active cookie ID from the get-go. Matching your users is a process, and nobody has the magic solution.

As far as cookie-to-cookie user mapping, the ability to match users across platforms has more to do with how frequently the your vendors fire match pixels. This happens when one platform (a DMP) calls the other platform (the DSP) and asks, “Hey, dude, do you know this user?” That action is a one-way match. It’s even better when the latter platform fires a match pixel back—“Yes, dude, but do you know this guy?”—creating a two-way identity match. Large data platforms will ask their partners to fire multiple match pixels to make sure they are keeping up with all of the IDs in their ecosystem. As an example, this would consist of a DMP with a big publisher client who sees most of the US population firing a match pixel for a bunch of DSPs like DataXu, TubeMogul, and the Trade Desk at the same time. Therefore, every user visiting a big publisher site would get that publisher’s DMP master ID matched with the three separate DSP IDs. That’s the way it works.

Given the scenario I just described, and even accounting for a high degree of frequency over time, match rates in the high 70 percentile are still considered excellent. So consider all of the work that needs to go into matching before you simply buy a vendor’s claim to have “90%” match rates in the cookie space. Again, this type of matching is also a process—and one involving many parties and counterparties—and not just something that happens overnight by flipping a switch, so beware of the “no problem” vendor answers.

What number are you asking to match?

Let’s say you are a marketer and you’ve gathered a mess of cookie IDs through your first-party web visitors. Now, you want to match those cookies against a bunch of cookie IDs in a popular DSP. Most vendors will come right out and tell you that they have a 90%+ match rate in such situations. That may be a huge sign of danger. Let’s think about the reality of the situation. First of all, many of those online IDs are not cookies at all, but Safari IDs that cannot be matched. So eliminate a good 20% of matches right off the bat. Next, we have to assume that a bunch of those cookies are expired, and no longer matchable, which adds another 20% to the equation. I could go on and on but, as you can see, I’ve just made a pretty realistic case for eliminating about 40% of possible matches right off the bat. That means a 60% match rate is pretty damn good.

Lots of vendors are actually talking about their matchable population of users, or the cookies you give them that they can actually map to their users. In the case of a DMP that is firing match pixels all day long, several times a day with a favored DSP, the match rate at any one time with that vendor may indeed be 90-100%–but only of the matchable population. So always ask what the numerator and denominator represent in a match question.

You might ask whether or not this means the popular DMP/DSP ”combo” platforms come with higher match rates, or so-called “lossless integration” since both the DMP and DSP carry an single architecture an, therefore, a unified identity. The answer is, yes, but that offers little differentiation when two separate DMP/DSP platforms are closely synched and user matching.

In conclusion

Marketers are obsessing over match rates right now, and they should be. There is an awful lot of “FUD” (fear, uncertainty, and doubt) being thrown around by vendors around match rates—and also a lot of BS being tossed around in terms of numbers. The best advice when doing an evaluation?

  • Ask what kind of cross-device graph your vendor supports. Without the fundamental ability to match people to devices, the “match rate” number you get is largely irrelevant.
  • Ask what numbers your vendor is matching. Are we talking about onboarding (matching offline IDs to cookies) or are we talking about cookie matching (mapping different cookie IDs in a match table)?
  • Ask how they are matching (what is the numerator and what is the denominator?)
  • Never trust a number without an explanation. If your vendor tells you “94.5%” be paranoid!
  • And, ask for a match test. The proof is on the pudding!

A Publisher’s History Of Programmatic Media

EvolutionIt’s hard to argue that the banner ad era has been good to publishers. After a brief initial period in which banner inventory matched audience availability, publishers enjoyed double-digit CPMs and advertisers enjoyed unique access to a valuable audience of online “early adopters.” Prognosticators heralded a new golden era of publishing, and predicted the eventual death of print. Fifteen years later, print is barely breathing, but publishers are still awaiting a “golden era” where the promise of online media matches its potential. What happened on the long road of publisher monetization, and how did we arrive in this new “programmatic” era?

It didn’t take long after HotWired sold the first banner ad to AT&T for other online properties to start making banner ads part of every page they put onto the Web. Not immune to Adam Smith’s economic theory, banner CPMs lowered as impression availability rose. Suddenly, publishers were in the single digits for their “ROS” inventory, and had plenty of impressions left over every month. Smart technology companies like Tacoda saw an opportunity to aggregate this unsold inventory, and sell it based on behavioral and contextual signals they could collect. Thus, the Network Era was born. Because networks understood publishers’ audiences better than the publishers did, they were able to sell ads at a $5 CPM and keep $4 of it. That was a great business for a very long time, but is now coming to an end.

While not creating tremendous value for publishers, the Network Era did manage to pave the way for real time bidding, and the start of the Programmatic Era. Hundreds of millions of cookies, combined with a wealth of third-party data on individuals, presented a truly unique opportunity to separate audiences from the sites the visited, and enable marketers to buy one impression at a time. This was great for companies like Right Media, who aggregated these cookies into giant exchanges. For advertisers, being able to find the “auto intender” in the 5 trillion-impression haystack of the Web meant new performance and efficiency. For publishers, this was another way to further segregate audience from the valuable content they created. The DSP Era ensured that only the inventory that was hardest to monetize found its way into popular exchanges. Publishers ran up to a dozen tags at a time, and let SSPs decide which bids to accept. Average CPMs plunged.

Over the last several years, it seems like publishers — at least those with enough truly premium inventory — are fighting back. Sellers have brought programmatic efficiencies in two ways: implementing DMP technology to manage their real programmatic (RTB) channel; and leveraging programmatic direct (sometimes call “programmatic premium”) technologies to bring efficiencies to the way they hand-sell their guaranteed inventory. Let’s look at both:

  • Programmatic/RTB: Leveraging today’s DMP technology means not having to rely on third-parties to identify and segment audiences. Publishers have been trying to take more control of their audiences from day one. The smartest networks (Turn, Lotame) saw this happening years ago and opened up their capabilities to publishers, giving them the power and control to sell their own audiences. With the ability to segment and expand audiences, along with new analytics capabilities, publishers were able to capture back the lion’s share of revenue, previously lost to Kawaja-map companies via disintermediation.
  • Programmatic Direct: Although 80% of the conversation in publisher monetization has revolved around the type of data-driven audience buying furnished by LUMAscape companies, 80% of the display advertising spending has been happening in a very non-real-time way. Despite building enough tech to RTB-enable the globe, most publishers are selling their premium inventory one RFP at a time, and doing it with Microsoft Excel spreadsheets, PowerPoints, PDFs, and even fax machines. RTB companies are trying to pivot their technology to help publishers bring efficiency to selling premium inventory through private exchanges. Other supply-side companies (like iSocket, ShinyAds, and AdSlot) are giving publishers the tools to sell their premium ads (at premium prices) without bidding—and without an insertion order. On the demand side, companies like Centro, Facilitate, MediaOcean, and NextMark (disclosure: I work there) are trying to build systems that make planning and buying more systematic, and less manual.

As programmatic technology gains broader acceptance among publishers, they will find that they have turned the monetization wheel 180 degrees back in their favor. DMP technology will enable them to segment their audiences for targeting and lookalike modeling on their own sites, as well as manage audience extension programs for their clients via exchanges. They will, in effect, crate a balanced RTB playing field where DSPs and agency trading desks have a lot less pricing control. Programmatic Direct (or, more correctly, “systematic reserved”) technologies will help them expose their premium inventory to selected demand side customers at pre-negotiated prices, and execute deals at scale.

The Programmatic Era for publishers is about bringing power and control back into the hands of inventory owners, where it has always belonged. This will be good for publishers, who will do less to devalue their inventory, as well as advertisers, who will be able to access both channels of publisher inventory with greater efficiency and pricing transparency.

This article originally appeared on 3/14/13 in AdExchanger.

Why 2013 will be the Year of Premium Guaranteed

guaranteed_stampFairfax Cone, the founder of Foote, Cone, and Belding once famously remarked that the problem with the agency business was that “the inventory goes down the elevator at night.” He was talking about the people themselves. For digital media agencies, who rely on 23 year-old media planners to work long hours grinding on Excel spreadsheets and managing vendors, that might be a problem.

For all of the hype and investment behind real-time bidding, the fact is that “programmatically bought” media will only account for roughly $2B of the anticipated $15B in digital display spending this year, or a little over 13% depending on who you believe. Even if that number were to double, the lion’s share of digital display still happens the old fashioned way: Publishers hand-sell premium guaranteed inventory to agencies.

Kawaja map companies, founded to apply data and technology to the problem of audience buying, have gotten the most ink, most venture funding, and most share of voice over the past 5 years. The amount of innovation and real technology that has been brought to bear on audience targeting and optimization has been huge, and highly valuable. Today, platforms like The Rubicon Project process over a trillion ad bids and over 100B ad transactions every month. Companies like AppNexus have paid down technology pipes that bring the power of extensible platform technology to large and small digital advertising businesses alike. And inventory? There are over 5 trillion impressions a month ready to be purchased, most of which sit in exchanges powered by just such technology.

All of that bring said, the market continues to put the majority of its money into premium guaranteed. They are, in effect, saying, “I know I can buy the ‘sports lovers’ segment through my DSP, and I will—but what I really want is to reach sports lovers where they love to go: ESPN.com.”

So, while RTB and related ad technologies will grow, they will not grow fast enough to support all of the many companies in the ecosystem that need a slice of 2013’s $2B RTB pie to survive. NextMark founder and CEO, Joseph Pych, whose company focuses on guaranteed reserved software, has been calling this the great “Sutton Pivot,” referring to the famous remark of criminal Willie Sutton , who robbed banks “because that’s where the money is.”

In order to better inderstand why this is happening, I have identified several problems with RTB that are driving companies focused on RTB to need to pivot:

  • There’s a Natural Cap on RTB Growth: I think today’s RTB technology is the best place to buy remnant inventory. As long as there are low-value impressions to buy, and as long as publishers continue to festoon their pages with IAB-standard banners, there will need to be a technology solution to navigate through the sea of available inventory, and apply data (and algorithms) to choose the right combination of inventory and creative to reach defined performance goals. While the impressions may grow, the real cap on RTB growth will be the most important KPI of them all: Share of time spent. Marketers spend money where people spend their time, whether it’s on television, Twitter, radio, or Facebook. When people spend less time on the inventory represented within exchanges, then the growth trend will reverse itself. (Already we are seeing a significant shift in budget allocation from “traditional” exchanges to FBX).
  • The Pool is Still Dirty: It goes without saying, but the biggest problem in terms of RTB growth is brand safety. The type of inventory available in exchanges that sells, on average, for less than a dollar is probably worth just that. When you buy an $850 suit from Joseph A. Bank—and receive two free suits, two shirts, and two ties—you feel good. But it doesn’t take much figuring to understand that you just bought 3 $200 suits, two $75 shirts, and two $50 ties. Can you get $15 CPM premium homepage inventory for $3 CPM? No…and you never will be able to, but that type of inventory is just what the world’s largest marketers want. They would also like URL-level transparency into where their ads appeared, a limit on the number of ads on a page (share of voice), and some assurance that their ads are being seen (viewability).  Inventory will continually grow, but good, premium inventory will grow more slowly.
  • It’s Not about Private Exchanges: Look, there’s nothing wrong with giving certain advertisers a “first look” at your premium inventory if you are a publisher.  Auto sites have been pursuing this concept forever. Big auto sites guarantee Ford, for example, all of the banner inventory associated with searches for Ford-branded vehicles over the course of a year. This ensures the marketer gets to his prospect when deep in the consideration set. Big auto sites may create programmatic functionality around enabling this type of transaction, but private exchange functionality isn’t going to be the savior of RTB, just necessary functionality. Big marketers want control of share of voice, placement, and flexibility in rates and programs that extend beyond the functionality currently available in DSPs. As long as they are spending the money, they will get—and demand—service.

What does all of this mean? RTB-enables ad technology is not going away, but some of the companies that require real time bidding to grow at breakneck speed to survive are going to pivot towards the money, developing technologies that enable more efficient buying of premium guaranteed inventory—where the other 85% of media budgets happen.  I predict that 2013 will be the year of “programmatic guaranteed,” which will be the label that people apply to any technology that enables agencies and marketers to access reserved inventory more efficiently. If we can apply some of the amazing technology we have built to making buying (and selling) great inventory easier, more efficient, and better performing, it will be an amazing year.

[This post originally appeared in ClickZ on 1/22/12]

Best Practices in Digital Display Media (Interview)

Digital display is remarkably complex. Standard campaigns can involve multiple vendors of different technologies and types of media.

Today, eConsultancy launches Best Practices in Digital Display Advertising, a comprehensive look at how to efficiently manage online advertising. We asked the author, Chris O’Hara, about the report and work that went into it.

Why did you write Best Practices in Digital Display Media?

In my last job, a good part of my assignment was traveling around the country visiting with about 500 regional advertising agencies and marketers, large and small, over three years. I was selling ad technology. Most advertisers seemed extremely engaged and interested to find out about new tools and technology that could help them bring efficiency to their business and, more importantly, results to their clients. The problem was that they didn’t have time to evaluate the 250+ vendors in the space, and certainly didn’t have the resources (financial or time) to really evaluate their options and get a sense of what’s working and what isn’t.

First and foremost, I wanted the report to be a good, comprehensive primer to what’s out there for digital marketers including digital ad agencies. That way, someone looking at engaging with data vendors, say, could get an idea of whether they needed one big relationship (with an aggregator), no data relationships, or needed very specific deals with key data providers. The guide can help set the basis for those evaluations. Marketers have been basically forced to license their own “technology stack” to be proficient at buying banner ads. I hope the Guide will be a map through that process.

What was the methodology you used to put it together?

I essentially looked at the digital display ecosystem through the lens of a marketer trying to take a campaign from initial concept through to billing, and making sure I covered the keys parts of the workflow chain. What technologies do you employ to find the right media, to buy it, and ultimately to measure it? Are all of these technologies leading to the promised land of efficiency and performance? Will they eventually? I used those questions as the basis of my approach, and leveraged the many vendor relationships and available data to try and answer some of those questions.

What’s the biggest thing to take away from the report?

I think the one thing that really runs through the entire report is the importance of data. I think the World Economic Forum originally said the “data is the new oil” [actually, the earliest citation we can find is from Michael Palmer in 2006, quoting Clive Humby] and many others have since parroted that sentiment. If you think about the 250-odd technology companies that populate the “ecosystem,” most are part of the trend towards audience buying, which is another way of saying “data-driven marketing.” Data runs through everything the digital marketer does, from research through to performance reporting and attribution. In a sense, the Guide is about the various technologies and methodologies for getting a grip on marketing data—and leveraging it to maximum effect.

There’s an explosion of three letter acronyms these days (DSP, DMP, SSP, AMP, etc) that marketers are still trying to sort out. Do we need all of them? Is there another one around the corner?

I am not really sure what the next big acronym will be, but you can be certain there will be several more categories to come, as technology changes (along with many updates to Guides such as these). That being said, I think the meta-trends you will see involve a certain “compression” by both ends of the spectrum, where the demand side and supply side players look to build more of their own data-driven capabilities. Publishers obviously want to use more of their own data to layer targeting on top of site traffic and get incremental CPM lift on every marketable impression. By the same token, advertisers are finding the costs of storing data remarkably cheap, and want to leverage that data for targeting, so they are building their own capabilities to do that. That means the whole space thrives on disintermediation. Whereas before, the tech companies were able to eat away at the margins, you will see the real players in the space build, license, or buy technology that puts them back in the driver’s seat. TheBest Practices in Digital Display Advertising Guide is kind of the “program” for this interesting game.

To learn more about the Best Practices in Digital Display Advertising Guidedownload the report here.

Down and Dirty Platform Guide

What’s powering your agency’s black box?

Currently, Donovan Data Systems and MediaBank own the advertising platform space, with more than 80% market share among agencies, which use the platforms extensively for buying offline media, and use their systems to bill digital media campaigns. Neither have a very sophisticated digital offering, which may be why the two companies teamed up to create MediaOcean (a merger currently pending approval from the government). They will have the best shot at aggregating all the workflow for media planning, buying, and billing—across all media types. Ultimately, their ability to succeed will depend upon their willingness to build the type of “ecosystem-like” platform described below—and the appetite of ad agencies to work with one, dominant provider. Many agencies continue to leverage their legacy platform for offline media, and are looking at new solutions for managing digital media.

Quite a few start-ups have arisen to try and answer the digital media gap left by MediaOcean. Advertisers and agencies are currently using a mix of various resources to meet campaign needs. They can be broken down into the following categories:

Workflow Platforms: Workflow platforms aim to consolidate the process of discovering, buying, serving, and reporting on digital display campaigns in one interface. By leveraging this technology, agencies can eliminate some of the rote planning processes (collating Excel spreadsheets, faxing insertion orders, and compiling ad serving reports) and take action against data they see in the dashboard, enabling faster optimization. Platforms like TRAFFIQ also include robust planning data, appended by third party demographic data from Nielsen, as well as the ability to access audience measurement data (from PulsePoint’s Aperture tool). Centro’s Transis offering is more of a lightweight management tool, while Facilitate Digital provides a big agency approach that marries ad serving with global currency and language support, and sophisticated tools for generating insertion orders and bills. As mentioned previously, MediaOcean will try and build a next generation digital platform that enables all of that functionality—and tie it to their widely adopted offline media management tools. This is really the future of digital media planning. You should be testing multiple workflow platforms and making sure that you are letting systems perform the menial tasks in digital media management, rather than expensive account and media personnel.

—  Trading Desks: Large holding companies have all universally created teams that handle real time audience buying. In an effort to distintermediate ad networks, and thus recapture lost media margins, agency “trading desks” have popped up to handle reach and performance campaigns for their clients. Many leverage existing DSP technology, such as Turn or MediaMath (see below), and all of them are focused on leveraging their media buying volume to capture audience data at scale. WPP’s Xaxis, launched in June 2011, is an example of how holding companies are aggregating their technology assets to do this:

In forming Xaxis, WPP brings together a broad portfolio of audience buying capabilities that have been independently developed and optimized in various parts of GroupM and WPP Digital over the past three years in businesses including B3, targ.ad, GoldNetwork, GroupM DSP and the GroupM Marketplace.  In 2010 alone, the businesses that have combined to form Xaxis executed approximately 4,000 campaigns for more than 400 GroupM clients. Xaxis will be led by CEO Brian Lesser, who previously served as global general manager of the Media Innovation Group (MIG), WPP’s digital marketing technology company.

Undoubtedly, they will seek to leverage other data insights from Kantar and SEM technologies to deliver performance marketing across multiple digital channels at scale. Other holding company Trading desks include Accuen (Omnicom), VivaKi (Publicis), and Cadreon (IPG). Smaller media groups also have their own desks, including Adnetik (Grupo ISP) and Varick Media Management (MDC Partners).

Obviously, if you are part of an agency holding company with access to the technology tools and services offered by a trading desk, you have the potential to leverage these assets, but must weight them against the (often high) costs. All of the trading desks execute buys on a managed service basis, rather than exposing a user interface, which does not enable individual agency planners/buyers to get real-time buying expertise. Additionally, many of the services the holding company trading desk offers are available directly through DSPs and their managed service teams.

The inherent conflict of interest in agency trading desks must also be taken into account when deciding the best approach to audience buying for your agency. As Mike Shields recently wrote in Digiday in his article entitled, “The Trouble with Trading Desks”:

According to multiple industry sources, some prominent brands are growing increasingly uncomfortable with their digital agencies funneling money to sister company trading desks (the holding company divisions that purchase ad inventory on exchanges). They are asking questions about how these trading desks earn revenue and whether clients are being charged more than once for executing the same media plan. The shift to programmatic audience-based ad buys through exchanges is undeniably an important advance to the online ad model, but agency holding companies have also taken it as an opportunity to update their own outdated business models in ways that are likely to leave some procurement chiefs scratching their heads.

The questions are murkier when it comes to the issue of “mandates.” There has long been talk that orders have come from the highest levels of agency holding companies for its agencies to redirect spot ad buys through the in-house trading desk rather than ad networks. Holding company and agency reps rebuff questions on this, but their words don’t always match up with reality. In some cases, holding companies are incentivizing their individual agencies’ media planning teams through revenue goals and even bonuses, according to several sources.

For example, Digiday was shown an email from a planner at a top Publicis agency stating that her team was not allowed to work with any networks and exchanges. “We are not authorized to buy networks and exchanges,” read the email from a buyer at a major media agency. “We are required to use [Publicis trading desk] Audience on Demand.” One prominent agency executive explained that over the past year her planning team was given quarterly goals to allocate more client budgets to exchanges, which she ignored. Other agencies compensate their teams for shifting more spending to trading desks; it’s actually in some planners’ contacts, she said. This is causing major friction in some cases between planning agencies and their trading desk partners, said a source.              

 —  Demand Side Platforms: An increasingly common part of the modern digital marketer’s toolset is the DSP, or demand side platform. Obviously, if you are working within one of the holding companies, you would be encouraged to deploy your audience-targeted media through the preferred Trading Desk, all of which leverage one or more independent DSPs. The top DSPs in the space at this time are Invite Media (acquired by Google), Turn, MediaMath, DataXu, X+1, and Triggit. Invite recently raised their minimum pricing to reportedly $50,000 per brand, per month, putting their services out of reach for the typical mid-sized agency. Among the rest, MediaMath has a reputation for having the most proprietary trading strategy, and unique optimization algorithms, with Turn not far behind. Most DSPs provide a blended service approach to trading, offering a mix of self-service tools and managed service support. Almost all of them utilize similar algorithms—and all of them have access to a wide variety of data providers for audience targeting. In considering your business’ approach to leveraging currently available DSP technology, the best strategy is to test as many as possible alongside each other. Most offer trial periods with discounted monthly minimums.

Choosing the right DSP partner has a lot to do with the amount of display volume you anticipate running on an annual basis. Larger providers can charge anywhere between $2,500 and $10,000 per month in minimum fees. Triggit and XA.net offer more competitive pricing for small and mid-sized agencies. For those agencies and advertisers that plan on having trading expertise in-house, and just want to leverage DSP technology, AppNexus is a great choice. Appnexus has built a fully-featured self-service platform (called the “AppNexus” Console, formerly called “DisplayWords”) on top of a broad ecosystem of exchange inventory and data, to create a veritable Sam’s Club for real time buyers. With over 800+ inventory sources available (Google, MSN, OpenX, Admeld, PubMatic, Rubicon) and a good amount of embedded data providers (eXelate, TargusInfo, Datonics, Bizo, Proximic, Peer39, etc.), AppNexus aims to be a one-stop shop for demand side customers looking for their own DSP solution. In addition, they make APIs available to prospective partners interested in building their own media UI on top of their bidding and ad serving technologies. AppNexus has great product support, but is designed for the customer that wants to have total control. For those who want AppNexus capabilities with a managed service layer, Accordant Media would be a great place to start.

Many agencies and advertisers are still struggling with whether or not they should deploy DSP technology to drive display media buying—and with their choice of provider. I think that Nat Turner, Invite Media’s CEO probably summed it up best in his 2010 AdExchanger article, which offered a list of key characteristics that define a “true DSP:”

  • The DSP must provide a fully self-service interface.  Clients should be able to have complete control via the interface and build an expertise around its use.
  • If the DSP provides managed services help to the agency, the DSP should be using the same interface that the agency would be using.  The technology should not require any manual work behind the scenes to activate or “set live” a change or a campaign.
  • The DSP must remain neutral and have zero allegiances to any publishers, exchanges, data providers or other vendors.  A true DSP should embody the word “platform” and not just be conduit or pretty interface to a pre-existing business.
  • The DSP must be fully transparent, starting with pricing and fees.  All fees that the DSP earns should be exposed in the interface, and every penny that the DSP makes should be known and visible to the agency.
  • The DSP should not mark-up media cost without the agency knowing.
  • The DSP should not mark-up data cost without the agency knowing.
  • If the DSP works with a publisher directly, it should be in an effort to make that publisher’s inventory “biddable.”  The DSP should not earn any additional margin from revenue sharing with the publisher or arbitraging the inventory.
  • The DSP must allow the agency to use its own exchange seats.  This allows the agency to always have visibility into the exact cost of media to ensure the DSP is not taking any additional margin.
  • Just like media, the DSP must allow the agency to buy or negotiate data cost directly, but flow through a common integration.  Data should be treated like media, it’s another part of the “supply side” that is purchased by the agency and thus should be transparent in cost.
  • The DSP should not, under any circumstances, own or operate an ad network.  This is in direct conflict with the neutrality aspect.
  • The DSP’s goal should be to expose any feature or tool that a supply source provides (either ad exchange or data provider) and not to try and obfuscate/hide or re-brand certain components (ex. “DSP Auto Segment #1”, with no transparency into what that means).  If a supply source provides it, the DSP should expose it for the agency self-service and let the agency decide whether to use it or not.
  • The DSP should not “bulk buy” media in order to re-sell to its clients.  This could either be a function of another way to make margin, a lacking of technology, or a combination of the two.
  • Related to the above, the DSP should not take on media risk.  Every impression should be purchased on behalf of a platform user at that time based on an active campaign that that platform user has created targeting that impression.

These DSP “principles” have not changed since 2010, and continue to be a great set of guidelines for choosing your real-time bidding technology provider. Ultimately, you want to be able to have total control over your bids, insights into the type of traffic available in the platform, and expect complete transparency with regard to your vendor’s pricing model. The right DSP relationship should reduce your dependence upon ad networks, lowering your overall media costs, and increasing campaign performance.

[This is an excerpt from the upcoming “Best Practices in Digital Display” whitepaper, available soon from eConsultancy]

Ad Tech’s Walking Dead Startups (DigiDay Interview)

Chris O’Hara is svp of marketing and sales for Traffiq, a digital media optimization company. He has referred to the clutch of ad tech companies with sizable bank accounts from VC investment, not profits, as the walking dead. O’Hara believes that it’s only a matter of time before a massive fire sale begins in the industry.

Explain the idea of a walking-dead company?

Walking dead companies are venture-funded companies that are sort of stumbling along revenue wise, making enough money to stay afloat or surviving on their financing by having a relatively low burn rate. They’re not going to have a super successful exit anytime in the future. They may be very exciting, innovative companies, but they have a hard time getting VCs pumped up. Venture funds tend to place a lot of bets and hope that they get big wins from a small percentage of them. Like any investment vehicle, a VC’s portfolio has its mix of winners and losers, although the typical VC portfolio tends to be less diversified in terms of its industry focus. When I heard Jon Soberg of Blumberg Capital — it is a backer of Legolas, HootSuite, and DoubleVerify, among others — use the phrase “the walking dead,” it felt extremely appropriate. A lot of companies in the digital display landscape are running out of capital after 3 or 4 years and several rounds of financing—and most of them will exit at low or zero multiple of valuation. Then again, smart investors like Grotech Ventures find a Living Social to invest in every now and again, and that is the kind of deal that can propel the value of an entire portfolio.

 

Are VCs beginning to cool in regards to investing in ad tech and social, in light of the economy?

On the contrary. I think the valuations of LinkedIn, Facebook, and Living Social have the VC community excited, maybe even overexcited, to be honest. The recent Buddy Media announcement is just one example, raising $54 million to plump its valuation to $500 million, and there are sure to more such valuations coming soon. I think what VCs aren’t too excited amount is the amount of companies within the display landscape that are going to flame out, or exit at fire sale prices. Unfortunately, according to Luma Partners banker Terence Kawaja, over half of the 35 deals in the last year didn’t produce a return on capital, and he expects that number to increase over time.

 

What are VCs doing right, or wrong, in ad tech?

If their funds make a decent return on investment, then they aren’t doing anything wrong! It may seem like that to company insiders working for some of the less fortunate companies, but VCs are not in business to keep ad-tech executives in panel discussions at cocktail-soaked industry conferences. They are in business to build companies to sell them, or put them into a public offering. I think certain well-heeled VCs may be making the venture capital business a lot harder by over-inflating the valuations of some of the larger companies in our business, but I think that’s due to the flight of money from increasingly unstable capital markets to other investment vehicles. There is a lot of cash on the sidelines right now, and venture funds are starting to look like a surprisingly safe haven. While that should scare the average investor, it makes for a very fun, frothy environment for ad technology!

 

So how should an investor, in this market, value a Demand Side Platform (DSP) company?

I would give them a 1x-3x valuation, similar to a successful digital media agency — and only if they were showing strong profitability and something unique about their process which was repeatable. The problem with the current landscape is that the excitement has been driven in large part by many of the companies that I have just described — companies with more hype than real technology with a unique IP.

 

What should ad tech Investors look out for?

I think investors have to watch out for a rapidly collapsing landscape, due to the social factor. You have an entire ecosystem built around audience targeting using 3rd party data. The problem? The companies with better and deeper first-party data have a lot more audience — like 750 million profiles for Facebook alone — than all of the companies in our landscape put together. And Facebook, LinkedIn, and Google have just started to define their display advertising strategy. If audience targeting is as easy as it seems to be now, via Facebook, then what is the real value of many of those little logos in the Kawaja map?

 

[This interview was originally published in Digiday on 8/25/11]