Three ways you can supercharge your digital media agency with data

Today’s digital media agency has access to enormous amounts of data, but using it effectively is what is going to make the difference between the shops of the future and the also-rans. Delivering data-driven insights is the key to being a 21st century agency. Here are three ways you should be working with data to secure your future:

Visualize it

How much time are you and your colleagues spending collating data, building reports, and formatting spreadsheets and PowerPoint decks for your clients? Most of the agencies I have worked with over the years admit to dedicating an embarrassingly large amount of (highly expensive) time towards these menial tasks. It’s not that getting your clients the data they need is not worth the time, it’s simply that there are now so many automated ways to deliver the data without burning salary.

To paraphrase former agency head and Akamai leader David Kenny, if you are doing things with people that you can be doing with computers, you have already lost. Why spend time formatting Excel spreadsheets and populating PowerPoint report templates with data, when you can be spending salaried employee time selling more services, optimizing campaigns, and delivering great strategy and creative?  Today’s automated ad management solutions and DMPs offer powerful ways to port both audience and ad serving reporting data into a single interface, to get instant access to key metrics such as frequency to conversion, churn rate, and channel attribution.

Ask yourself if the cost of such a system is more than the cost of the time your employees you have been spending building reports—and, ultimately, more than the cost of your eventual demise, should you ignore the changes afoot in your business.

Aggregate and Activate it

Think of all the data you have access to from a digital media standpoint. If you are helping clients execute a digital media campaign, you have traditional serving data from your demand side server, such as DFA. You probably also have engagement data from your rich media ad server. If you have access to your clients’ website pages (or at least tags there), you have site-side data, including conversion event data. If you are using an audience measurement tool, or are doing audience-specific buying through a demand side platform, you also have audience measurement data. Great. What are you doing with all of it? Moreover, what kind of data does your client have that you can help them add to activate the common advertising data types I have just described?

Let’s take the example of an agency using an audience measurement reporting tool, alongside an ad server report. In this case, it is possible that the analyst knows that the highest frequency converters for his travel campaign belong to a popular PRIZM segment, and he may also know that visitors to a popular travel site are three times as likely to engage with his rich media ad creative. Now what? Obviously, the right move is to buy more of the audience segment and double up with guaranteed advertising on the travel site. But what about audience overlap?

How can the advertiser reduce ad waste by ensuring that members of his audience segment that he is securing for as little as $2.00 CPM on exchanges are not overrepresented on the premium site for which he is paying $18.00 CPM? Plus, how many members of that audience are also already registered as customers? If you are not deploying a DMP to aggregate your clients’ CRM (first-party) data alongside the site-side and ad serving (2^nd party) data and the purchased (3^rd party) data segments, then there is going to lots of duplicated uniques in your audience. Smart data aggregation creates ad activation through waste reduction, lifting conversion rates, while lowering cost per conversion. Getting an effective universal frequency cap across digital channels is very difficult, but every dollar not wasted on duplicate impressions is another dollar that may be spent finding a new audience member. Reducing waste adds reach—and performance, which every client likes.

Compare it

As a digital media agency, you’ve run hundreds, perhaps even thousands of campaigns, producing thousands of data-rich reports for your clients. How much of that knowledge are you leveraging? Although you might know the top travel sites and audience segments to reach “moms of school-age children in-market for a beach vacation,” how readily available is that knowledge? Is it sitting inside your Media Director’s head, or hidden in various documents that don’t talk to one another? How about access to normative campaign data? How quickly can you find out how certain sites performed against similar KPIs without doing hours of research?

Like or not, advertisers want to know how their campaigns are performing against known standards, and it’s gotten a lot more complicated than beating a 0.1% click-through rate lately. Knowing how your last 10 travel campaigns performed—from which guaranteed site buys succeeded, to which audience segments performed, to which creatives elicited the highest CTR—is just step one. Having that data available for quick reference means that every new campaign can start from an advanced performance level, and your media people don’t have to recreate the wheel every time you receive an RFP.

Today’s smart DMPs also feature the ability to leverage your data to an even greater extent, especially for audience buying. Why limit yourself to pre-packaged audience segments that do not include your client’s first-party data? Today’s more advanced DMPs give marketers the ability to create audience segments on the fly, building discrete segments from data that includes available third-party data—but also first-party data, such as registration details, transactional records, and signals from hosted social media listening solutions. It’s the difference between buying from an ad network and creating your own.

Summary

Buying into portals’ site sections was the first phase in the effort to bring contextual and audience relevance to ad buying. Networks followed, offering packaged audiences at scale. Then bidded exchange buying came, offering pre-packaged audience segments at the individual cookie level. Today’s best practices include marrying all available data types to give marketers the ability to create their own targeted buys, and modern data management platforms are helping the largest advertisers automate what they have been doing since the first direct mail piece went out: finding targeted audiences. Leveraging today’s DMP technology can not only help you find those audiences more easily, but help you understand who they are, why they respond, and help you find them again.

Chris O’Hara is head of strategic partnerships for nPario, a DMP with clients that include Yahoo! and Electronic Arts, among others. A frequent contributor to industry publications, this is his first column for The Agency Post. He can be reached through his blog on www.chrisohara.com

[This article originally appeared in The Agency Post on 1/25/12]

Using Audience Measurement Data to Optimize Digital Display Campaigns

These days, advertising and data platforms are giving marketers a wealth of information that can be used to validate their strategies, and optimize their digital campaigns for better performance. There is a lot of data to sort through—some more useful than others. Sometimes, good campaign optimization comes down to the basics: Understanding who your audience is, and why they are doing what they are doing.

Let’s look at a real life example of a digital display campaign, run through the digital ad agency of a popular mattress retailer. The agency wanted to test new inventory sources for the campaign by running broadly on general interest sites, evaluating the demography of audiences that showed purchase intent, and optimize over the course of the campaign to maximize impact.

A theory being tested was that older audiences, who report more difficulty sleeping than younger demographic groups, would respond more favorably to the retailer’s online display ads. Campaigns were initially skewed to sites that over-indexed against audience composed of 50 and older.

Figure 1: Age of Ad Viewer, by Impressions.

As Figure 1 shows, a bulk of impressions during the discovery portion of the campaign were delivered to visitors aged 46-65 years of age, which was the desired demographic. After analysis of those who viewed or clicked on a display ad, and then went on to purchase, the audience composition was remarkably different. As shown in Figure 2, the bulk of conversions came from those aged 18-45.

Figure 2: Age of Mattress Purchaser (Conversions).

The agency adjusted the ad buy to heavy up on sites that over-indexed for a younger audience, and opted out of buys tailored to the older demographic. As wasted impressions were trimmed down in the overall plan, conversion rates increased dramatically. Testing and validating your instincts with data on an ongoing basis is the key to success in digital display advertising. The mattress retailer, who experienced better sales from older store visitors (offline), found a more responsive younger audience online. Although it seems obvious, having the initial data means being able to smartly allocate marketing capital, and having access to ongoing data means not having to rely on old insights in a changing marketplace.

Another offline theory the mattress retailer sought to validate was the mattress life cycle. After collecting brick and mortar sales data for years, the retailer knew that the average life of a mattress was approximately 7 years, and that the single greatest life event influencing the purchase of a new mattress was moving. Therefore, it made sense to target audiences based on length of residence (>7 years), and target content around buying or renting a new home.

Inventory was bought from a wide range of home-specific and moving sites, and measured using Aperture audience measurement populated with data sets from Experian, IXI financial, V12 demographic, and Nielsen PRIZM data.

Figure 3: Length of Residence, by Impressions.

Figure 4: Length of Residence, by Click.

As Figures 3 and 4 amply demonstrate, the mattress retailer was targeting the bulk of impressions towards individuals reporting over seven years residence in a single location, and clicks among that group indexed the highest in aggregate. That data validated the approach of buying into sites with a strong audience of self-reported homeowners. However, a deeper look into audience data revealed a strong distinction between renters and buyers.

Fig 5Comparing Impressions and Conversions by home ownership status.

As noted in Figure 5, although the bulk of impressions in the campaign were served to homeowners, renters were the ones buying the most mattresses. This learning did more than any other data point to drive campaign optimization.

Naturally, the next step in the campaign optimization process was to focus inventory delivery to sites that promised a concentrated audience of home renters. Sites such as ForRent.com, ApartmentGuide.com, and Renters.com were added to the optimization plan.

More insights came as the Aperture data was collected. Despite purporting to have a heavy concentration of renters, two of the more popular sites actually index much higher among homeowners, as shown in Figure 6. It looked as though homeowners that were looking into renting made up the majority audience—a fact that helped the retailer tailor specific messaging to them.

Figure 6: In this example, a media site aimed at renters, over-indexes against current homeowners.

Figure 6: In this example, a media site aimed at renters, over-indexes against current homeowners.

For this particular campaign, the ability for the retailer to validate certain audience assumptions using real demographic data was critical, as well as the ability to leverage the distinction between two types of potential customers: home owners, and renters. Additionally, getting real audience metrics beyond a publisher’s media kit or self-declared audience information enabled the retailer to craft its creative and messaging in a highly specific way that increased conversions.

When it comes to audience validation and campaign optimization, here are three keys:

• Know Your Data: In today’s technology-driven marketing world, knowing how to leverage the data available to you is critical to both understanding and targeting your audience. Make sure your marketing investment decisions are driven through the analysis and usage of 1^st party data, including registration data for demographic modeling; 2^nd party data, such as ad server and search data for behavioral modeling; and 3^rd party data, such as available audience segments from providers like Nielsen and Datalogix, for audience validation, matching, and lookalike modeling. Data is not just about buying audience segments for targeting; it’s about trying to get a 360-degree view of your ideal customer.

• Choose the Right DMP: There are DMPs for every marketer, so be careful to choose the right one. Big Data needs call for pure play DMPs that can stitch together highly disparate data sets that include all data types, and make both insights, audience segments, and lookalike modeling available in real-time. Marketers looking to buy from a variety of 3^rd party audience segment providers should choose a data marketplace such as Exelate, or be willing to access a more limited number of data sources inside a DSP such as AppNexus.

• Leverage Audience Measurement: Finally, there is a lot that audience segments can bring to the table in terms of audience insights. Understanding the audience composition of who saw, clicked on, and converted after seeing your campaign gives you the ability to learn about your target customers, their online behaviors, and (most importantly) find more of them. Your DMP should have the ability to marry audience and campaign data to give you a highly granular level view of your best (and worst) performing audience types—down to the creative level.

Learnings from this case study, and other valuable information, can be found in my upcoming “Best Practices in Digital Display Media,” coming in January 2012 from eConsultancy.com.

[This article originally appeared in ClickZ on 1/4/2012]

The other day, I was updating my Spotify app on my Android device. When it finally loaded, I was asked to log in again. I immediately loaded up a new playlist that I had been building—a real deep dive into the 1980s hardcore music I loved back in my early youth. I’m not sure if you are familiar with the type of music that was happening on New York City’s lower east side between 1977 and 1986, but it was some pretty raw stuff…bands like the Beastie Boys (before they went rap), False Prophets, the Dead Boys, Minor Threat, the Bad Brains, etc. They had some very aggressive songs, with the lyrics and titles to match.

Well, I put my headphones in, and started walking from my office on 6^th Avenue and 36^th street across to Penn Station to catch the 6:30 train home to Long Island…all the while broadcasting every single song I was listening to on Facebook. Among the least offensive tunes that showed up within my Facebook stream was a Dead Kennedys song with the F-word featured prominently in the song title.  A classic, to be sure, but probably not something all of my wife’s friends wanted to know about.

As you can imagine, my wife (online at the time), was frantically e-mailing me, trying to tell me to stop the offensive social media madness that was seemingly putting a lie to my carefully cultivated, clean, preppy, suburban image.

So why, as a digital marketer, would you care about my Spotify Facebook horror story?

Because my listening habits (and everything else you and I do online, for that matter) are considered invaluable social data “signals” that you are mining to discover my demographic profile, buying habits, shoe size, and (ultimately) what banner ad to serve me in real time. The only problem is that, although I love hardcore music, it doesn’t really define who I am, what I buy, or anything else about me. It is just a sliver of time, captured digitally, sitting alongside billions of pieces of atomic level data, captured somewhere in a massive columnar database.

Here are some other examples of data that are commonly available to marketers, and why they may not offer the insights we think they might:

– Zip Code: Generally, zip codes are considered a decent proxy for income, especially in areas like Alpine, New Jersey, which is small and exclusive. But how about Huntington, Long Island, with an average home value of $516,000? That zip code contains the village of Lloyd Harbor (average home value of $1,300,000) and waterside areas in Huntington Bay like Wincoma, where people with lots of disposable income live).

– Income: In the same vein, income is certainly important and there are a variety of reliable sources that can get close to a consumer’s income profile, but isn’t disposable income a better metric? If you earn $250,000 per year, and your expenses are $260,000, then you are not exactly Nordstrom’s choicest customer. In fact, you are what we call “broke.” Maybe that was okay back in the good old days of government-style deficit spending but, these days, luxury marketers need a sharper scalpel to separate the truly wealthy from the paper tigers.

– Self-Declared Data: We all like to put a lot of emphasis on the answers real consumers give us on surveys, but who hasn’t told a little fib from time to time? If I am “considering a new car” is my price range “$19,000 – $25,500” or “35,000 – $50,000?” This type of social desirability bias is so common that reaearchers have sought other ways of inferring income and purchase behavior. When people lie about themselves, to themselves (in private, no less)  you must take a good deal of self-declared data with a hearty grain of salt.

– Automobile Ownership: Want to know how much dough a person has? Don’t bother looking at his home or zip code. Look at his car. A person who has $1,800 a month to burn on a Land Rover is probably the same person liable to blow $120 on mail order steaks, or book that Easter condo at Steamboat. Auto ownership, among other things, is a great proxy for disposable income.

It would be overly didactic to rehearse all of the possible iterations of false data signals that are being used by marketers right now to make real-time bidding decisions in digital media. There are literally thousands—and social “listening” is starting to make traditional segmentation errors look tame. Take a recent Wall Street Journal article that reported that the three most widely socially-touted television shows fared worse than those than shows which received far less social media attention.

Sorry, but maybe that hot social “meme” you are trying to connect with just isn’t that valuable as a “signal.” We all hear the fire truck going by on 7^th Avenue. The problem is that the only people who turn to look at it are the tourists. So what is the savvy marketer to do?

Remember that all data signals are just that: Signals. Small pieces of a very complicated data puzzle that you must weave together to create a profile. Unless you are leveraging reliable first-party data, second-party data, and third party data, and stitching that data together, you cannot get a true view of the consumer.

In my next column, we’ll look at how stitching together disparate data sources can reveal new, more reliable, “signals” of consumer interest and intent.

[This article was originally published in ClickZ on 12/2/2011]

Some of the 40+ apps running on my Facebook account.

How the Power of Platforms is Transforming Ad Technology

Last month, I wrote about my unfortunate experience with Facebook, which took it upon itself to broadcast my entire Spotify listening experience to the world, seemingly without my knowledge or permission. This aggravated me to the point of proclaiming, quite publicly, that I was going to “commit Facebook suicide” and end my relationship with the social media behemoth. It turns out that is easier said than done.

As I was downloading my Facebook file to prepare for the big quit, I went to check in with my Yahoo Sports Fantasy Football league—and logged in using my Facebook credentials. I immediately realized that Yahoo was merely the tip of the iceberg. Facebook suicide wouldn’t only make it nearly impossible for me to hit the waiver wire and grab newly available Green Bay Packers receiver Donald Driver, it would actually create the Internet version of losing your wallet.

Right now I have 41 applications that interact with Facebook, mostly for credentials, but some with deeper integration: Crunchbase, Yahoo, Business Insider, Bing, Foursquare, Spotify, Quora, Klout, CityPath, Slideshare, Eventbrite, LinkedIn, Gist, Xobni, Plaxo, Microsoft Live, Photobucket, TweetDeck, Nintendo DSi, AIM, Yelp, Scribd, Pandora, HootSuite, WordPress, OpenTable, Loosecubes, and TripAdvisor.

Facebook is also a place for me to post articles, my database of “friends” (many of whom are schoolmates and acquaintances (as I am to many of them), but ones I like to keep in touch with. You never know when a connection may come in handy. A Facebook desertion would impact my Klout score (heaven forbid!); make me remember by Photobucket password, which I registered for about 5 years ago; and make RSVP’ing to my friend’s Christmas party a lot harder than it needs to be. In short, for the active Web user, life without Facebook is like living in Los Angeles without a driver’s license. It’s weird and it’s hard.

Facebook is the definition of sticky. Not only because there is data in there that’s hard to organize elsewhere, but its basic utility makes the cost of switching extremely difficult. Not to mention the fact that there is little to switch to. Google Plus is great, but a bit too late to the party. Nobody wants to manage two social networks. One is more than enough.

So, how did Facebook become the site that’s impossible to leave? Facebook is a great example of the power of platform technology. My former colleague, a longtime Microsoft employee, taught me a lot about the power of platforms and introduced me to this simple definition, written by Marc Andreessen in 2007.

A “platform” is a system that can be programmed and therefore customized by outside developers — users — and in that way, adapted to countless needs and niches that the platform’s original developers could not have possibly contemplated, much less had time to accommodate

 Andreessen identified three types of platforms (and we can associate these definitions with modern examples):

Level 1: Platform’s apps run elsewhere, and call into the platform via a web services API to draw on data and services (e.g., Google Maps, Flickr)

Level 2: Platform’s apps run elsewhere, but inject functionality into the platform via a plug-in API. Most likely, a Level 2 platform’s apps also call into the platform via a web services API to draw on data and services. (Facebook, Firefox, Adobe Photoshop)

Level 3: Platform’s apps run inside the platform itself—the platform provides the “runtime environment” within which the app’s code runs. (Salesforce.com, Ning, Facebook more recently)

My friend tells me that Microsoft somewhat accidentally created the platform business model, and they continue to nurture the ecosystem of development and innovation around Windows with great success. Microsoft was one of the first companies to support outside developers with financial and intellectual resources, and continues to make what they call “Developer Platform Evangelism” part of their DNA. My colleague also rightly pointed out what a shock it was when Apple took a page from the Microsoft playbook and starting cultivating a developer-driven platform approach. (How many applications are available for the iPhone at the moment? Half a million?) Building a flexible, extensible platform upon which others can build businesses is not about creating a product; it is building a living, breathing, sustainable ecosystem that can grow on its own.

Advertising technology is probably the best example of an industry crying out for open platform technology. The now familiar Kawaja map has become the rallying cry for integration, and marketers are looking for smart technologies that can bring disparate systems and point solutions together in a way that actually offers efficiency and performance (rather than being yet another tool to log into). Whether it’s managing digital advertising workflow, or wrangling a mess of 1^st and 3^rd party data, the answer can be found in a new breed of “open” platforms. When choosing a partner to work with, ask yourself these questions:

• Security: Is the platform safe? It may seem counterintuitive, but the most open platforms require the greatest levels of security. Look no further than Facebook’s recent deal with the Justice Department to see just how serious platform security is to its ultimate ability to succeed. This is important for all platforms, but most critical when it comes to data management, where a great deal of 1^st party data is stored and aggregated.

• Extensibility: Does my platform solution enable me to extend it’s utility via API (application programming interfaces)? In other words, how easy is it to plug in my billing numbers into my ad management platform, to make the reconciliation process more manageable? Your platform should provide clean, well-written API documentation, and support the access to wide variety of data and services.

• Adoption: How viable is the platform? A good yardstick of long-term viability is the acceptance rate from the development community. Is there an active and passionate community of businesses and/or individual users developing applications against the platform’s web services?

These are great starting points when considering leveraging a platform technology for your business, but you should also ask yourself how your company can leverage the principles of platform technology to be more successful. This is happening every day, as companies leverage Saleforce.com’s awesome platform technology and cloud infrastructure to create new internal or client-facing applications. How about online publishers? Instead of constantly putting together reports for their advertisers, what if they leveraged a platform that enables their biggest advertisers to build their own reports, and mix them with internal data to get new customer insights? The possibilities are endless.

I recently found out that is was impossible to quit Facebook. Understanding platform economics may inspire you to leverage technology to generate an ecosystem that your customers can’t leave either.

[This article was published in eConsultancy blog on 12/12/11 ]

The right DMP solution can be golden for finding audiences.

What big marketers should look for in a next generation data management platform

“Big Data” is all the rage right now, and for a good reason. The other day, I was switching computers, and wanted to move about five gigabytes of photos and videos unto my new laptop, and my largest thumb drive was a measly 1 gig. I ended up getting an 8GB thumb drive for about $8 at the K-Mart in Penn Station. Think about how cheap that is. That’s less than half a cent per song, if you consider the typical 8GB MP3 device can hold about 2,000 high-quality recordings. Two terabyte drives are selling for about $130 from Western Digital. I don’t know about you, but I am not at the point where I need 2TB of data storage, and I hope I never get there. The point is that storing tons and tons of data has gotten very inexpensive, while the accessibility of that data has increased substantially in parallel.

For the modern marketer, that means having access to literally dozens of disparate data sources, each of which cranks out large volumes of data every day. Collecting, understanding, and taking action against those data sets is going to make or break companies from now on. Luckily, an almost endless variety of companies have sprung up to assist agencies and advertisers with the challenge. When it comes to the largest volumes of data, however, there are some highly specific attributes you should consider when selecting a data management platform (DMP).

Collection and Storage: It’s all About Scale, Cost, and Ownership

First of all, before you can do anything with large amounts of data, you need a place to keep it. That place is increasingly becoming “the cloud” (i.e., someone else’s servers), but it can also be your own servers. If you think you have a large of data now, you will be surprised at how much it will grow. As devices like the iPad proliferate, changing the way we find content, even more data will be generated. Companies that have data solutions with the proven ability to scale at low costs will be best able to extract real value out of this data. Make sure to understand how your your DMP scales and what kinds of hardware they use for storage and retrieval.

Speaking of hardware, be on the lookout for companies that formerly sold hardware (servers) getting into the data business so they can sell you more machines. When the data is the “razor,” the servers necessarily become the “blades.” You want a data solution whose architecture enables the easy ingestion of large, new data sets, and one that takes advantage of dynamic cloud provisioning to keep ongoing costs low. Not necessarily a hardware partner.

Additionally, your platform should be able to manage extremely high volumes of data quickly, have an architecture that enables other systems to plug in seamlessly, and whose core functionality enables multi-dimensional analysis of the stored data—at a highly granular level. Your data are going to grow exponentially, so the first rule of data management is making sure that, as your data grows, your ability to query them scales as well. Look for a partner that can deliver on those core attributes, and be wary of partners that have expertise in storing limited data sets. There are a lot of former ad networks out there with a great deal of experience managing common 3^rd party data sets from vendors like Nielsen, IXI, and Datalogix. When it comes to basic audience segmentation, there is a need to manage access to those streams. But, if you are planning on capturing and analyzing data that includes CRM and transactional data, social signals, and other large data sets, you should look for a DMP that has experience working with 1^st party data as well as 3^rd party datasets.

The concept of ownership is also becoming increasingly important in the world of audience data. While the source of data will continue to be distributed, make sure that whether you choose a hosted or a self-hosted model, your data ultimately belongs to you. This allows you to control the policies around historical storage and enables you to use the data across multiple channels.

Consolidation and Insights: Welcome to the (Second) Party

Third party data (in this context, available audience segments for online targeting and measurement) is the stuff that the famous Kawaja logo vomit map was born from. Look at the map, and you are looking at over 250 companies dedicated to using 3^rd party data to define and target audiences. A growing number of platforms help marketers analyze, purchase, and deploy that data for targeting (BlueKai, eXelate, Legolas being great examples). Other networks (Lotame, Collective, Turn) have leveraged their proprietary data along with their clients to offer audience management tools that combine their data and 3^rd party data to optimize campaigns. Still others (PulsePoint’s Aperture tool being a great example) leverage all kinds of 3^rd party data to measure online audiences, so they can be modeled and targeted against.

The key is not having the most 3^rd party data, however. Your DMP should be about marrying highly validated 1st party data, and matching it against 3^rd party data for the purposes of identifying, anonymizing, and matching third party users. DMPs must be able to consolidate and create as whole of a view of your audience as possible. Your DMP solution must be able to enrich the audience information using second and third party data. Second party data is the data associated with audience outside your network (for example, an ad viewed on a publisher site or search engine). While you must choose the right set of 3^rd party providers that provide the best data set about your audience, your DMP must be able to increase reach by ensuring that you can collect information about as many relevant users as possible and through lookalike modeling.

For example, if I am selling cars and I find out that my on-site users who register for a test drive are most closely matched with PRIZM’s “Country Squires” segment,  it is not enough to buy the Nielsen segment. A good DMP enables you to create your own lookalike segment by leveraging that insight—and the tons of data you already have. In other words, the right DMP partner can help you leverage 3^rd party data to activate your own (1^st party) data.

Make sure your provider leads with management of 1^st party data, has experience mining both types of data to produce the types of insights you need for your campaigns, and can get that data quickly. Data management platforms aren’t just about managing gigantic spreadsheets. They are about finding out who your customers are, and building an audience DNA that you can replicate.

Making it Work         

At the end of the day, it’s not just about getting all kind of nifty insights from the data. I mean, it’s big to know that your visitors that were exposed to search and display ads converted at a 16% higher rate, or that your customers have an average of two females in the household. It’s making those insights meaningful.

So, what to look for in a data management platform in terms of actionability? For the large agency or advertiser, the basic functionality has to be creating an audience segment. In other words, when the blend of data in the platform reveals that showing 5 display ads and two SEM ads to a household with 2 women in it creates sales, the platform should be able to seamlessly produce that segment and prepare it for ingestion into a DSP or advertising platform. That means a having an extensible architecture that enables the platform to integrate easily with other systems. Moreover, your DMP should enable you to do a wide range of experimentation with your insights. Marketers often wonder what levers they should pull to create specific results (i.e., if I change my display creative, and increase the frequency cap to X for a given audience segment, how much will conversions increase)? Great DMPs can help built those attribution scenarios, and help marketers visualize results. Deploying specific optimizations in a test environment first means less waste, and more performance. Optimizing in the cloud first is going to become the new standard in marketing.

Final Thoughts

There are a lot of great data management companies out there, some better suited than others when it comes to specific needs. If you are in the market for one, and you have a lot of first party data to manage, following these three rules will lead to success:

• Go beyond 3^rd party data by choosing a platform that enables you to develop deep audience profiles that leverage first and third party data insights. With ubiquitous access to 3^rd party data, using your proprietary data stream for differentiation is key.
• Choose a platform that makes acting on the data easy and effective. “Shiny, sexy” reports are great, but the right DMP should help you take the beautifully presented insights in your UI, and making them work for you.
• Make sure your platform has an applications layer. DMPs must not only provide the ability to profile your segments, but also assist you with experimentation and attribution–and provide you with ability to easily perform complicated analyses (Churn, and Closed Loop being two great examples). If your platform can’t make the data dance, find another partner.

[This post was originally published in ClickZ on 11/9/11]

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]

MediaOcean: So Wrong, yet So Right!

A “platform” is a system that can be programmed and therefore customized by outside developers — users — and in that way, adapted to countless needs and niches that the platform’s original developers could not have possibly contemplated, much less had time to accommodate.  – Marc Andreessen, 2007

Last week’s news of the merger between DDS and MediaBank was certainly exciting. In digital media management terms, it’s kind of akin to rooting for the Yankees; only their fans want to see them grow more powerful, because it sure ain’t good for baseball. These two behemoths have been fighting over agency budgets for the last four years, and have managed to steal a bit of market share from one another, while advancing the cross-media efficiency agenda slightly. The stated hope for this merger is that the corporate combination will give them enough firepower to finish the golf swing and solve the insanely complicated digital media puzzle, making cross media management possible in a real way.

Is this merger good for the digital media ecosystem? Maybe. Here are the three factors that will determine whether MediaOcean will become the digital media industry’s defacto system:

Standards are good: First off, it helps when everybody is reading from the same sheet of music, and there isn’t an industry that hasn’t benefitted from a common, accepted set of standards. The IAB has done a great job in terms of helping standardize ad sizes and out clauses, and some of the systems and procedures that help oil digital business transactions. An argument could be made that having 80% of agency dollar volume running through the same system brings efficiencies to the entire media buying landscape, but I’m not sure anyone in the industry would say that this was the case when DDS had larger market share.

For digital marketers, a significant hassle has been bill/pay and reconciliation, and that has been an area of focus for DDS and MediaBank across digital and traditional media. There is no doubt they can help standardize the process by which advertisers and publishers reconcile delivery even just by being the largest player – they can bring a de facto standard to bear, but how quickly can they really react to a rapidly evolving space with myriad nuances in ideal workflows for almost every customer? If they can change their DNA, they will be a force to be contended with.

– Platforms are good:  Secondly (and most importantly),  the right approach to solving this problem is an open platform approach. But none of the leaders in this space have shown any predisposition for opening things up.  This is in large part because the technology landscape has evolved so fast that the legacy companies haven’t been able to adapt their systems to keep up.  The market needs an open, extensible platform approach to solve its numerous problems, the question is can any of the existing leaders in the space, including MediaOcean, provide that?

My colleague, Eric Picard, learned about the power of platform effects while working at Microsoft over the last several years. He recently educated me on the varieties of platform approaches that could be taken in our space, and has offered to let me publish that here:

*  Systems vs. Platforms: The first thing to discuss is that most companies in our space have built systems – not platforms (despite everyone using the word platform for everything.)  A system simply exists on its own, is proprietary and closed – it doesn’t allow third parties to build on top of it.  This describes almost all the offerings in our industry today.

*  Simple Platforms – or Mashups: Most of us have experienced a ‘mashup’ in one shape or another by now. This is where a tool or web site is built that calls to numerous remote services (APIs or Web Services) to build one cohesive interface.   In this case, the platform is really all the multiple different systems used ‘behind the scenes’ to create one simple application that you could use.  Many web sites use this technique, using various content management systems, ad servers, etc… A lot of the SEMs and DSPs use this approach, building their own interface that hits each of the Paid Search providers or Ad Exchanges via API.

*  Consumable Back-End Platforms: Lots of companies now offer API access to their systems.  This kind of ‘back-end’ access is then used by third parties to ‘mash-up’ the functionality with either their own or other third party functionality.  AppNexus, Right Media Exchange, Atlas, DoubleClick, and numerous others provided this kind of back-end access by API.  Some of the more sophisticated providers, like AppNexus and RMX even enable third parties to extend their functionality to some degree – but they don’t make that extension generically consumable.

*  Ecosystem-like Platforms: A great example of this is Salesforce.com – which has built out a platform that really begins to live up to the market opportunity that the industry should be looking for.  Salesforce enables numerous services that can be consumed, like the platforms and mashups we discussed above.  But they also let third party vendors come in and extend the functionality of the core Salesforce platform.  They even provide an App marketplace, similar to iTunes, that allows third party vendors to distribute their applications to existing Salesforce customers.  This is a powerful approach, but requires a whole new set of skills that most companies in the ad technology space are not quite able to pull off.

Within this overall context of platforms verses systems, you can see the variety of approaches being taken by the various parties in the ad ecosystem:

Google offers third parties APIs to write against, but keeps the vendors playing in the search ecosystem on their toes by frequently changing the APIs, and it’s fairly clear that their goal is to be both the platform and the applications that run the advertising ecosystem.  They support third parties, but only as it furthers their end-game. 

The ad servers understand that their value is in the engine, much more-so than their workflow.  And they’ve opened up APIs to let other workflows plug in and become mashups that ultimately are powered by the smarts of the ad servers behind the scenes.   

Donovan Data Systems has brought one mashup workflow to market, their iDesk product.  It interfaces with DDS’s other applications fairly well, and can integrate with the dominant ad servers.  MediaBank has done somewhat similar things with their application suites, but has taken a more “Google-like” approach when it comes to their business – investing in their own DSP and automated media buying systems. This investment in products that compete directly with the very vendors that would need to integrate into the combined system causes me to pause a bit.

At the end of the day – it’s hard to understand who might have the right DNA among these constituents to actually roll out the right platform to solve the industry’s needs.

–Creativity is good: Finally, I think a development like this is excellent, if it actually creates an environment that transforms where digital media people spend their time. Right now, digital agencies spend most of their time and effort trying to wrangle an “ecosystem” of nearly 300 technology, data, and media providers. They spend the bulk of their time trying to execute media plans, rather than coming up with creative strategies to engage consumers. The mess of systems, lack of standards, multiple log-ins, and unmanageable hoards of data that each system throws off has created the ultimate irony: digital media is becoming the least creative, least profitable, and least measurable channel for marketers. If the merger brings us one step closer to making the digital execution piece easier, and gets the conversation back to creative, than I think it’s a step in the right direction.

After being out in the field, and talking to over 400 agencies about their digital media needs, I know that a standardized platform is what everybody wants. Whether or not MediaOcean is going to be nimble and creative enough to deliver a system that meets the needs of our growing ecosystem is very much in question. Technology has always thrived on choice, flexibility, and open standards. I believe that the company that can deliver on all three will end up winning.

[This commentary appeared in Adotas on 9/29/11]

Media management software firm Traffiq has partnered with audience measurement company The Nielsen Co. to provide advertisers access to Nielsen’s target-marketing platform @Plan. The integration will go live on Sept. 21 for all roughly 400 registered customers of Traffiq’s display ad-buying platform, said Chris O’Hara, SVP of sales and marketing at Traffiq.

Customers “are able to come into Traffiq, throw on a campaign and get @Plan data appended by Nielsen [which is] really great demographic information and do decisioning on whether they should advertise based on that information,” O’Hara said.

Nielsen’s @Plan platform will display websites’ number of monthly unique visitors as well as site visitors’ demographic information, such as gender, age, education level, household income, ethnicity and marital status.

Previously, Traffiq customers only had access to publishers’ self-reported data, which was “not that accurate,” said O’Hara. In addition to supplementing site audience data for the 3,000 publishers available on Traffiq’s platform, the partnership adds data for 7,000 publishers collected by Nielsen, he said.

O’Hara said the partnership marks the first time Nielsen has made the @Plan platform available to non-@Plan customers.

[This post appeared in Direct Marketing News on 9/21/11]

The 300,000-channel world of digital marketing is exponentially more complicated than the not-so-distant past when radio, broadcast, and out-of-home advertising were the only games in town. “Most clients expect some level of digital services from their agency,” according to Tammy Harris, the media director of Neathawk Dubuque & Packett, a leading healthcare marketing firm based in Richmond, Va.

This makes it much harder for agencies to deliver impeccable plans, provide great analytics, and continually ensure better rates and performance. Plus, clients want to use analytics to uncover how their products are selling in a new, connected age. The old black box of television offered a model that worked for a long, long time; if you had enough money to feed it, the television produced an audience broad enough to justify the marketing expense. Agencies fed the beast with commercials and earned market share. Now, with an audience splintered into hundreds of cable and satellite channels, and with 25 percent of the audience fast-forwarding through the commercials with their DVRs, that model is broken. Radio is better off, but even that is being corroded by pay-to-play models. Besides, it has always been hard to build a brand verbally.

So, agencies are faced with the need to build client brands online through websites and Facebook pages. They have to get customers to those pages via search marketing and display ads. Is it that hard to figure out where the digital audience for a product lives? Of course not. Agencies that want to reach young men can find themselves on ESPN or Break.com’s media kit within the space of 60 seconds. Want to reach people with hyperhydrosis (excessive sweating)? There’s a whole section of WebMD dedicated to it, and the site would be delighted to sell you a sponsorship. Want to build a Facebook page and stock it full of fans you can constantly tweet to? A few recent college graduates can have that up and running and packed full of content in a week or two.

The problem isn’t executing a digital marketing strategy or finding an audience. The problem for agencies is that is really hard to do it at scale — and even more difficult to make any money doing it. A recent study by AAAA cited that the cost of servicing digital campaigns averages 30 percent of an agency’s media cost, as opposed to 2 percent for television buys. That sounds hard to believe, but not when you think about the back-end an agency needs to be truly successful in the digital space.

As Harris puts it, “The bulk of the time required to plan and place traditional media happens up-front, while digital media requires attention throughout the run. The ability to track, optimize, and report so many metrics requires many hours, and because digital media often costs less than traditional, it means agencies are doing more work for less money.”

Even if you are just a media shop, you need some serious tools to get the job done. First off, you need to be able to build and maintain cutting-edge websites, and that capability encompasses a lot of expensive, technical personnel. Researching sites with any credibility means having access to expensive Nielsen or comScore subscriptions. Doing SEO and SEM? You better have a young employee to head up your search and analytics practice, and these folks aren’t cheap. If you want to serve ads with any volume, and have access to your own data, you will need your own ad server. How about tracking website activity? Enter Omniture, or other analytics software. What about optimizing campaigns, tracking conversions, putting up and taking down ad tags? Get ready to hire and maintain a serious ad operations team. And it doesn’t end with the campaign.

After all of this, in even the most successful online marketing effort, the billing and reconciliation game is just beginning. A client might ask, “My server says you served 100,000 impressions, and you are charging me for 125,000?” To which the agency might respond, “Who pays, based on whose numbers, and when am I getting paid anyway?” It goes on and on. In some ways, it’s hard to imagine how agencies make any money on digital advertising at all.

For Marci De Vries, former head of media of Baltimore-based IMRE, and now a small-agency owner herself (MDV Interactive), digital marketing can quickly become a zero-sum game. “If the developer of these tools can make money on expensive tools, then good for them,” she says. “What I’ve seen lately is that those expensive tools are bought by 10 percent or less of their market, and then are underutilized because only a few license seats are purchased. The overall value to an agency of expensive software is close to zero. Meanwhile, the web community is copying the functionality, databases, and ability to provide meaningful information and distributing it for free or almost free. The overall value to agencies is very high, although it also levels the playing field between small shops and big shops. The web community likes to level the playing field.”

Kent Kirschner, the owner of The Media Maquiladora, a Latin American specialty agency with offices in Sarasota and Mexico City, says the problem is starting to get even more pronounced as multicultural agencies begin to come to the digital party. “Margin compression is a phenomenon affecting all aspects of the industry,” he says. “The rise of CPC, CPA, and other performance-based pricing has compelled all marketers to think that our profession now should be held to a different measure. Our creative and strategic work is now almost inevitably met with skepticism if there isn’t some direct and easily identifiable performance metric attached to it. So clients value what we do less and drive us to wring more and more out of our media partners and our teams. In many cases, they don’t pull their own weight in developing appropriate data measurement systems to identify the impact of our work.”

It’s not only measurement that impacts an agency’s margin and daily workflow. Real in-house innovation must continue to be what differentiates agencies from each other — and the host of widely available tools on the market. “The internet continues to drive the price point for traditional agency materials down to zero every day,” De Vries says. “There is a community on the web that is in favor of sharing repeatable work so that more money can be spent on real innovation. To help eliminate what they consider mundane tasks, they offer free design templates, CMS platforms with extreme performance, and in some cases even free logo work.”

Peter Gerritsen, well-known ad man and now Transworld Advertising Agency Network (TAAN) head, feels the same way. “The squeeze of economic conditions on the advertising community, and on marketing budgets, has created an environment of cost-control at any price, even to the detriment of quality,” he says. “While this is short-sighted, it has become the lead in negotiating compensation. In many areas, it has become not about the value of doing it best, but how little it will take to just get it done. The advertising industry has commoditized many of the steps required to produce communications. A commodity is measured by cost, not by quality. Expertise is measured on outcomes and value. The experts command premiums for their work. Agencies need to position themselves as experts in defined businesses. Deep expertise is better than commoditized capabilities.”

Agencies are now forced to do what they always do when it comes to margin compression: share the pain with their publishing partners. The good shops send out a brief to 20 sites, collect creative ideas from them, and collate the best five into a plan that fits from the standpoint of budget and practicality. Usually, the largest sites get on those plans simply because the agency wants to create the least amount of friction when closing a deal. Want to reach young men? Look no further than ESPN.com.

Agencies that are charged with performance simply go to networks, which find them the cheapest “targeted” inventory they can. Agencies don’t know where their clients’ ads are running, but how else do you get geo-targeted, contextually targeted, user-targeted, and re-targeted inventory for less than a $10 CPM? But what have the agencies really done? They don’t know how they got the performance, or how to find it again. They don’t own any part of the value chain of that process: the sites, the targeting, the data, or the analytics. Scary. Sounds like something the client can get directly — for 15 percent less.

Gerritsen values the media mix more on performance than delivery. “The value is in the insights and the delivery of successful outcomes,” he says. “How this is delivered may not be through internal resources, but as a trusted method of information exchange between media, agent, and marketer. It’s not necessarily about who owns the data, but rather, about the creative use of the information to produce success. I don’t like the term ‘aggregator.’ It doesn’t demonstrate any value, just the ability to cobble together a pile of stuff. The value of the best networks and exchanges is the shared responsibility to balance costs and benefits to all participants.”

For agency owners like Kirschner, there is no question about maintaining control of publisher relationships. “Despite the fact that there is such a proliferation of options in the digital space today, it has never been more important for agencies to maintain direct relationships with publishers,” he says. “While networks and exchanges offer convenience and supposedly compelling pricing, the reality is that the publisher at the end of the loop ultimately wants to see a campaign succeed, and he or she has the direct experience and audience knowledge to ensure that happens. There are many tools available that allow these personal relationships to scale within a large media department, so the appeal of networks and exchanges diminishes.”

I currently work for a company that is trying to help small to mid-sized agencies tackle some of the technology aspects of buying and selling digital media. In most sales jobs, it takes a while to get a meeting with a decision-maker. Frankly, I was surprised at how quickly CEOs, CFOs, and digital media VPs agreed to meet with our company at first. Sure, we have a captivating sales pitch, but the reason we get so much uptake is that there is real pain out there on the agency side.

The online media industry is far from being sorted out. Until a standard set of practices and tools gets established (which might never happen), agencies are going to need reliable, trusted partners to help them profitably navigate the digital landscape. Agencies will forever be evaluating new platforms, networks, exchanges, ad servers, data providers, and myriad other tools and services. But, for the agencies we talk to every day, it’s not the tools that make the agency — it’s how the tools are used that ultimately makes the agency successful.

As De Vries says, “Agencies that were built on a manufacturing model (paying inexperienced employees to send mailers all day long) now need to focus on innovation instead because that’s where the money is now. It’s hard to innovate every day in an agency.”

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]