What I Learned Writing Best Practices in Data Management

Today data is like water: free-flowing, highly available, and pervasive. As the cost of storing and collecting data decreases, more of it becomes available to marketers looking to optimize the way they acquire new customers and activate existing ones. In the right hands, data can be the key to understanding audiences, developing the right marketing messages, optimizing campaigns, and creating long-term customers. In the wrong hands, data can contribute to distraction, poor decision-making, and customer alienation. Over the past several weeks, I asked over thirty of the world’s leading digital data practitioners what marketers should be thinking about when it comes to developing a data management strategy. The result was the newly available Best Practices in Data Management report. A few big themes emerged from my research, which I thought I would share:

Welcome to the First Party

Digital marketing evolves quickly but, for those of us working as digital marketers or publishers for the past 10 years, we have seen distinct waves of transformation impact the way we use data for audience targeting. Early on, audience data was owned by publishers, who leveraged that data to control pricing for premium audiences. The Network Era quickly supplanted this paradigm by leveraging tag data to understand publishers’ audiences better than the sites themselves. Buying targeted remnant inventory at scale created new efficiencies and easy paychecks for publishers, who found themselves completely disintermediated. The DSP Era (which we are still in) continued that trend, by completely separating audiences from media, and giving even more control to the demand side. Today, the “DMP Era” promises a new world where publishers and advertisers can activate their first party data, and use it for remarketing, lookalike modeling, and analytics.

The ubiquity of third party data (available to all, and often applied to the same exact inventory) makes activating first party data more valuable than ever. Doing so effectively means regaining a level of control over audience targeting for publishers, and being able to leverage CRM data for retargeting and lookalike modeling for the demand side, as well as a deeper level of analytics for both sides. If there has been one huge takeaway from my conversations with all of the stakeholders in the data-driven marketing game, it is that getting control and flexibility around the use of your own first-party data is the key to success. As a marketer, if you are buying more segments than you are creating, you are losing.

The New Computing Paradigm

In order to successfully activate all of the data your company can leverage for success takes a lot of work, and a lot of advanced technology. Whether you are a publisher trying to score audiences in milliseconds in order to increase advertising yield, or an advertiser attempting to deliver a customized banner ad to a prospect in real-time, you need to store an incredible amount of data and (more importantly) be able to access it at blazing speeds. In the past, having that capability meant building your own enormous technology “stack” and maintaining it.  Today, the availability of cloud-based computing and distributed computing solutions like Hadoop has created a brand new paradigm or what former Microsoft executive and current RareCrowds CEO Eric Picard likes to call the “4th Wave.”

“Being a Wave 4 company implicitly means that you are able to leverage the existing sunk cost of these companies’ investment,” says Picard. That means building apps on top of AppNexus’ extensible platform, leveraging Hadoop to process 10 billion daily transactions without owning a server (as Bizo does), or simply hosting portions of your data in Amazon’s cloud to gain speed and efficiency. As digital marketing becomes more data intensive, knowing how to leverage existing systems to get to scale will become a necessity. If you are not taking advantage of this new technology paradigm, it means you are using resources for IT rather than IP. These days, winning means applying your intellectual property to available technology—not who has the biggest internal stack.

Social Data is Ascendant

One of the most interesting aspects of data management is how it is impacting traditional notions of CRM. In the past, digital marketing seemed to end below the funnel. Once the customer was driven through the marketing funnel and purchased, she went into the CRM database, to be targeted later by more traditional marketing channels (e-mail, direct mail). Now, the emergence of data-rich social platforms had actually created a dynamic in which the funnel continues.

Once in the customer database (CRM), the post-purchase journey starts with a commitment beyond the sale, when a consumer joins an e-mail list, “friends” a company’s page, follows a company’s Twitter account, or signs up for special offers on the company’s site. The next step is an expression of social interest, when the consumer agrees to make public his like for a company or brand by “friending” a company’s page, following a company’s Twitter account. Beyond the “like” is true social activation, wherein the consumer actively (not passively) recommends the product or service, through commenting, sharing, or other active social behaviors. The final step is having the consumer sell on your behalf (directly via affiliate programs or, in the softer sense, as a “brand ambassador”).  This dynamic is why Salesforce has acquired Radian6 and Buddy Media.

For digital marketers, going beyond the funnel and activating consumers through social platforms means understanding their stated preferences, affinities, and that of their social graph. Most companies already do this with existing platforms. They real key is tying this data back into your other data inputs to create a 360 degree user view. That’s where data science and management platforms come in. If you are not ingesting rich social data and using it to continually segment, target, expand, and understand your customers, you are behind the curve.

[This post originally appeared on the EConsultancy blog. Get the paper here.]

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The RFP is Dead: New Concepts in Audience Discovery

The Programmatic Approach to Media Allocation is Coming Soon to a Platform near You.

Since its inception, advertising has always been about putting the right message in front of the right audience. Back when televisions were really expensive, and people used to gather around them in bars to watch baseball, beer companies started to do a lot of television advertising. While it’s still pretty easy for marketers to find the right beer demographic on sports programming in broadcast, the new world of multiple screens makes finding that audience at scale tougher every day.

The guy who was likely in the pub watching the game back in the 1940s and 1950s is now watching the game at home, but maybe on his iPad. Or perhaps he’s sneaking it in at work on his computer via Slingbox, or following along on his Android phone on the MLB Mobile app. The point is, there’s no easy way to find him, it’s almost impossible to find him at cheaply at scale, and we may have the wrong way of discovering him online.

The traditional method of finding your audience in the digital space is to put together a campaign request for proposal (RFP) that details the nature of your ad campaign, the audience you are looking for, where you want to find them, and the most you expect to pay to reach them. An agency’s trusted inventory suppliers receive and evaluate the RFP, and put together (hopefully) creative strategies that deliver a way to find that audience, and put the agency’s message in front of the user at the right time, in the right place. This approach makes complete sense. Except when it doesn’t.

Here are some ways in which the traditional, single RFP fails:

Multiple Pricing Methodologies: One of the problems in the traditional RFP process is that the agency is often limited to suggesting a single price range they are willing to pay for the media. For example, a typical RFP for a branding campaign looking for contextually relevant, above-the-fold inventory may suggest a price range to publishers of between $8-$12 CPM. This is fine if the proposal is only going to premium publishers with guaranteed inventory. But what if the advertiser is also interested in finding his audience on a cost-per-click basis? Knowing the historical performance of similar past campaigns, he might suggest a range of $1.50 -$3.50 per click. While the agency is comfortable buying using both methodologies (and certainly prefers the latter), the publisher is left wondering how to respond in a way that gives him the best overall price, and best revenue predictability. After evaluating the campaign, he may well decide that he will fare better on the CPC model, but in the absence of the granular past performance data of the demand side client, he will probably opt for the revenue visibility afforded by a CPM campaign.

Markets tend to work most best when both sides of the transaction have access to similar information. That leads to pricing efficiency, which in turn creates long-term sustainable performance results. Unfortunately, the traditional RFP process tends to strongly favor the demand side customer rather than the inventory purveyor. Add in the possibilities of buying on cost-per-lead (CPL) and cost-per-action (CPA), and you have a situation in which the demand side customer has the benefit of greater data visibility, and the supply side opportunity becomes purely speculative, leading to even more pronounced market inequities. These dynamics have largely occurred due to the seemingly unlimited supply of banner inventory (a supply side problem that will be debated in another article), but the fact remains that today’s standard agency RFP process falls far short of accounting for the multiple ways in which digital media can be bought and sold today.

Multiple Buying Methodologies: Along with a new multitude of pricing choices available to both sides, the emergence of real-time-bidding (RTB) makes the traditional RFP process even less relevant in for today’s progressive digital marketer. Say a marketer wants to reach “Upper income men in Connecticut that are in-market for a BMW 5-Series sedan.” That’s a pretty specific target, and I’ll bet that if a marketer could actually identify and find the several dozen guys in Darien, Stamford, and Greenwich that are looking for that specific make and model of car within the time period of the campaign, they might be willing to bid upwards of $500 CPM to reach him. Unfortunately, if you were to restrict the RFP variable to that exact target, you would end up serving a few hundred impressions, and probably fail to even spend $500 altogether. Naturally, the marketer is willing to bid a lot less find all men and women in Connecticut that are in market for a BMW; or just men in Connecticut in market for a car in general; or even just men in Connecticut, whether they need a car or not. Naturally, bids for each segment will vary widely, and can span from single to triple digits. Without a CPM-based pricing cap, it is not uncommon to see bids above $1,000 for certain impressions, although very few of them are won.

Well executed RTB campaigns have multiple segments that bid at different levels, and impressions are won at widely differing prices. While the marketer expects some visibility around what the effective CPM may be for such a campaign, RTB systems work best when agnostic to media cost, and should depend purely on the advertiser’s CPC or CPA goals. While a marketer can be very specific about his ultimate CPA, CPC, or CPL pricing cap, the traditional RFP does not address his tolerance for certain types of risk, his willingness to deploy a large percentage of media budget for data costs, and his willingness to forgo placement and context in exchange for reaching his ultimate demographic targets. This is just one of the reasons that agencies are having difficulty transitioning to the new world of demand side platforms in general.

New Discovery Mechanisms: Finding your audience by creating a well-crafted RFP and working with inventory suppliers to cobble together an effective buying program is still a great way to reach your ultimate goal, mostly because publishers know their audiences really well and have been able to offer new and creative ways to engage them on webpages (and, now, multiple screens). But what if the publisher isn’t really in control of his audience? What if the content an advertiser wants to be associated with migrates and changes constantly, based on user behavior and activity? I am talking, of course, about user generated content. Companies like Buzz Logic measure the “conversational density” around a topic and find where people are talking about, say, “organic food.” You can’t find that audience with a traditional RFP. The prevalence (or downright dominance) of social media outlets has created an explosion of UGC that is creating content almost faster than marketers can discover it. And that those new content areas are highly desirable to advertisers looking to engage consumers in contextually relevant activities. Those audiences are found via technology. How about finding people through the products they own (OwnerIQ) or even based on their occupation (Bizo)?

RTB and data make finding very granular audiences an intriguing option for marketers, but the traditional RFP process makes it hard to describe a marketers willingness to mix traditional, contextual audience buying (finding fantasy football fans on ESPN, for example) from some of the new audience discovery options (finding college students online based on their ownership of mini refrigerators, for example). Both are possible, and probably great to deploy over the course of a single campaign, but the traditional RFP process doesn’t really address this well.

Allocation: In my mind, the most important aspect missing from the traditional RFP process is that it doesn’t bring the demand and supply sides together effectively to suggest proper budget allocation for a campaign. If you have a $100,000 budget, and suggest $10,000 per publisher, every publisher is going to suggest $10,000 in media—regardless of whether or not they have it available. Moreover, you are going to alienate some publishers that may have larger minimums. The real problem is that the traditional RFP process doesn’t easily allow budget allocation across multiple media types (guaranteed display, real-time bidded display, mobile, video, search, and social) or take into account historical performance data. Essentially, the RFP makes a crude guess at budget allocation, with the marketer using his gut and some past performance data (“well, the $40,000 I spent with Pandora last time performed pretty well, so I’ll do that again”). Although the amount of choices today’s digital marketer has have expanded greatly, his form of communicating specific campaign needs is still an essay-length Word document or form-based technology with limited fields that do not capture the breadth of choices available.

So, what is the answer? New platform technologies are helping marketers expand the way they describe their campaign needs-and their willingness to deploy differing pricing and buying methodologies to reach their intended audience. Real time bidding systems are also giving end users hundreds of different levers to control the types of bids they are willing to make, based on the granularity of the audience, and performance of the inventory they purchased. In coming months, technology will not only expand a digital marketer’s ability to better describe his goals, but also use past performance data to suggest more effective media allocations in the beginning—and during—a campaign. Based on granular campaign attributes, knowledge of price points where certain real-time bids are won, and historical campaign performance, systems will be able to tell the marketer: “Allocate this percentage to SEM, this percentage to guaranteed display, and this much to real-time display” while suggesting the most effective bids to place. This three-dimensional discovery technique is where we are headed. While we are getting ready for its arrival, marketers should start thinking outside the traditional RFP box, and begin configuring new ways to ask inventory partners to find their desired audiences.

[This post originally appeared in eConsultancy on 8/19/11]

TRAFFIQ Talks Private Marketplaces and Other Platform Enhancements

ADOTAS – Demand-side digital media management platform TRAFFIQ expands its offerings so much that it’s hard to keep up. Fortunately, we were able to hit Senior Vice President of Sales and Marketing  (and regular Adotas contributor) Chris O’Hara with questions regarding the platform’s latest upgrades (including customized and private publisher portfolios and enhanced financial management tools) as well as the many partnerships the company has formed since the beginning of the year.

ADOTAS: Terence Kawaja’s infamous display ecosystem landscape places TRAFFIQ in “media management systems” with companies like Centro — closer to the supply side than DSPs. Do you think this is a fair placement and why?

 

O’HARA: I don’t think we should put too much emphasis on placement in the landscape chart. Many companies belong in one or more buckets—and some of the logos should appear much larger than others, based on overall impact within the landscape itself. TRAFFIQ, for example, could appear in many of the categories (DSP and Ad Serving being two of them), but I believe there is a revenue threshold to be met before LUMA will place you in multiple buckets.

That being said, I think TRAFFIQ is in the right category. Eventually, the notion is that TRAFFIQ would appear as an overlay to multiple sections of the map, providing dashboard level access to an advertiser’s entire vendor toolset.

How does a media management system differ from a DSP? Confused agency people want to know.

Mostly, it’s nomenclature. I think the term “demand-side platform” is a great term for a technology tool that helps advertisers manage their media. The reality is that now “DSP” means “technology tool for real time managing exchange buying.” Agencies have every right to be confused, as companies within the landscape are changing from network to “platform” and from data provider to “DMP.”

The difference is simply that a “management system” should provide tools that cover inventory discovery, vendor negotiation, offer management, contracts, ad serving, analytics, and billing; DSPs handle a sliver of the overall media buy. For example, TRAFFIQ customers will be able to manage several DSPs within our platform at once.

It seems like the new Private Marketplaces tool allows advertisers to customize publisher and exchange lists — fair assessment, or is there more, so much more?

Right now, TRAFFIQ private marketplaces enables advertisers to buy outside of our curated list of 3,000 guaranteed inventory sources, which is especially important in terms of giving agencies the control they need over media. Publishers increasingly want the convenience and efficiency of exchange buying…without exposing their quality inventory to the world.

Demand side customers like the reach and price efficiency they can achieve with exchange-buying—but still struggle with brand safety and transparency. Our next-generation system will offer both sides a lot more control over who they work with, and that is sorely needed in our business right now.

Can this tool also offer hookups into the increasingly popular private exchanges, such as The Weather Channel’s Category 5 and Quadrant One?

Yes, as long as the demand-side partner has a business relationship in place with the inventory supplier, TRAFFIQ will be able to enable the connection.

Why are agencies going gaga over your new finance management tools?

If agency CFOs could actually go “gaga,” they may be doing so over our new tool for the simple reason that most digital platforms don’t take the vagaries of agency pricing into account. At TRAFFIQ, we have to manage several different pricing scenarios at once.

What is the agency’s margin, and how do they want that margin reflected in the pricing (baked into the media cost, or shown transparently)? How about data and technology fees? Those can be added to the gross media cost, or shown separately as well. Also, handling net and gross costs with publishers has always been challenging.

Smart systems should recognize these fundamental business needs, and expose the correct pricing to everyone within the system, eliminating confusion and duplicative work.

Can you explain how the multiple user permissions work? Why is this important for your agency clients and how can they best be deployed?

For the demand side, multiple user permissions means giving access to a subset of clients for an individual account team. On the supply side, it means having the ability to put the right publisher rep with the right demand side customer.

For example, an individual agency account team may buy from Fred at ESPN for one client, and Joe at ESPN for another. It is also necessary for agencies to be able to manage which of their end-clients gets to view certain reports. Multiple user permissions adds the layer of flexibility that enables TRAFFIQ users to expose the right data to the right set of customers.

What kind of agencies are you working with these days and what kind do you hope to add to your client base? Are you working with brands directly as well?

For the past several years, our focus has been getting total product adoption from the small to mid-sized agency market. Some are the types of shops that have a thriving traditional media practice, but not necessarily the right tools to tackle digital media. Still others are strong in digital, but are struggling with multiple tools, and having a hard time putting all of the pieces together efficiently.

We partnered with some of the great agency groups like TAAN, Magnet Global, AMIN and Worldwide Partners to reach these shops, and have been quite successful. We have also done some work with the holding companies, but mostly on a campaign-by-campaign basis, rather than getting the large shops to adopt our solution fully.

The product features we are working on now will actually enable big agencies to adopt TRAFFIQ by enabling API connections to their existing systems (ad serving, billing, etc). You can’t walk into an agency and ask them to drop all of their vendor relationships at once… You have to be able to work seamlessly with what they have.

What sets apart your attribution services from your media management peers as well as other attribution providers? What kind of extra insight do you provide?

Right now, a lot of our customers are working with our embedded Aperture audience measurement reports. Unlike other platforms, we make it fairly easy to take those demographic campaign  learnings and take action against them. So, it’s not just click- or view-based data; it’s using third-party data to understand who is seeing your campaign, clicking on it, and ultimately converting against it.

We are the only platform that can help marketers react to that data through guaranteed buying—and RTB. In the near future, we will be able to show how our efforts in initial media budget allocation and optimization are driving performance. We also see a great opportunity to get some key attribution metrics out of search and display, once out customers are doing both types of media in the platform at scale.

How does TRAFFIQ integrate first-party and third-party data into audience buying efforts?

Right now we have over 15 data segmentation partners. Some of them work directly with our Trading Desk (we apply those segments to exchange buys), and some of our partners provide both targeting and media execution. We see our role as a platform as provisioning our advertising clients with the right best-of-breed partners, no matter what the targeting need.

That means Proximic and Peer39 for semantic; AlmondNet (now Datonic) for search keyword retargeting; Media6Degrees and 33Across for social targeting; Nielsen, Lotame and eXelate for demo targeting, etc. We also have the ability to match any first-party data with available audience within our real-time bidding system, and find that audience as well.

Do you foresee more mobile partnerships in TRAFFIQ’s future or is Phulant your one and only?

TRAFFIQ is an open platform, and that means we must be willing to integrate partners based on our clients’ needs. We see Phluant as a key TRAFFIQ partner for mobile ad serving, and have plans to work closely with them to define and grow our mobile capabilities. We want to see more standardization around mobile workflow, and that means making it easier for marketers to allocate budgets across different media types (social, search, mobile, video, and display) in one system.

Phluant has developed amazing technology to help marketers take rich media for display  and bring it to mobile devices. That’s a great starting point… and something that can be leveraged across multiple mobile inventory vendors.

Regarding your partnership with Bizo, what kind of opportunities lie in the realm of targeted B2B display?

Bizo is doing an amazing job of bringing the power of B2B to display advertising. Until recently, B2B marketers stayed away from display advertising (or struggled to get online reach with smaller, niche business publishers). Now, they can take the success that they are used to having with targeted direct mail in B2B, and apply that in real time display.

We believe that there are some real opportunities to make both B2B and local display digital advertising more manageable, scalable, and accountable.

Besides its “interesting” name, what about Oggifinogi (recently acquired by Collective Media) attracted TRAFFIQ to make it your video and rich media network partner?

Our customers use Pointroll, Mediamind, Spongecell, and all kinds of third-party rich media vendors, but we needed a reliable “go-to” partner that could help our registered demand-side client base tackle rich media and video more easily. We saw that “Oggi” had a strong commitment to both technology and customer service, and we felt that we could work with their team well. I think Collective media validated what a great partner choice we made there!

TRAFFIQ appears to have spread itself out pretty well across digital marketing channels, so what area is next on the agenda? Social?

The first big channel we are going to tackle after display is search. In a few months, TRAFFIQ will feature bid management tools for search engine marketing right in the platform—along with access to the Facebook self-service ad inventory. This means that, for the first time, guaranteed display, real-time display, search, and social can be managed within the same “media management system.”

It’s going to be exciting, but the real challenge will be making it seamless for marketers—and getting some great insights out of all the data that such an integrated platform will produce. That’s what we’ll be working on over the next several months.

[This interview appeared on 7/2711 in Adotas]

The Problem of Ubiquity

Is Your Technology Offering Differentiated Enough to Win in the Digital Media Advertising Landscape?

Media buying desks are so 2009. I mean, who doesn’t have access to 800+ exchange inventory sources and 30 different 3rd party data providers?  In a world where well-heeled demand side customers have all of the tools to buy audience efficiently, how do internet marketers effectively communicate?

At this moment in time, digital display advertisers love the idea of audience buying because it seems unique. The concept of buying an audience, rather than the site it is on, is truly revolutionary and will be a continuing part of the digital media conversation for a long time to come. However, many technology companies are being funded, started, and run on the foolish misconception that audience buying vs. site-specific buying is a binary choice. It is not. Large holding company shops are trying to migrate client budgets over to their media buying desks, demand side platforms are trying to displace ad networks, and ad “platforms” are attempting to skim the media cream on all real time transactions by promising better performance through centralization. All of these tactics are doomed to fail.

Context

Unless you are going cheap and deep by buying remnant inventory at under $0.50 CPMs—or going data-heavy and spending upwards of $5.00 CPMs using segmentation to find highly specific premium audience—you are going to need context. In the former case (running wild with sub-$0.50 bids across exchanges) you face the issue of low CTR and the accompanying issue of low brand safety. Your ad is getting out there, but God knows where it’s serving. Then again, at $0.50, why not “spray and pray?” With machine learning, you can easily optimize against a conversion pixel, and let your bidding technology find all the performance that a cheap CPM can yield.

On the other end of the spectrum (using expensive V12 or Bizo segments, for example), you have a highly targeted audience—but a problem achieving scale against such specific targeting goals. Also, while you may be hitting your desired segment, you may be hitting them at the wrong time. As a frequent traveler, I have been frequently targeted with exactly the right ad (Cheap JetBlue flight to SFO) at exactly the wrong time (during my Yahoo! fantasy baseball draft).  Context does matter. Reaching premium surfers when they are engaged in consuming premium content is still relevant. That’s why people pay what they do for full page ads on the Wall Street Journal and that’s why WebMD will never accept “3rd party” advertising. Context matters, intent matters, and a user’s mindframe matters. When I am reading an article about Carmelo Anthony on ESPN.com, and I am in the market for basketball sneakers, I am simply more likely to buy them…because I am in a basketball mindset. Catch me with the same sneaker ad when I am replying to my friend on Hotmail, and it’s highly unlikely that I will break task and respond.

Engagement Methodology

Almost as important as context, is the way that an ad is served.  The majority of online audiences visit about three sites a day—and one of them is Facebook. It’s kind of tough to get into the media mix for the average site. There are two approaches the modern digital publisher can take can deal with this reality. The first is to SEO the hell out of their site, and drop enough tags to ensure an automatic, steady flow of exchange and network advertising. Another method is to firewall their exclusive content and only serve guaranteed advertising. Hybrid models are the norm, but publishers must manage the inevitable channel conflict and data leakage that come from opening up premium ad slots to networks and exchanges. Getting this blend right for websites is step one.

Modern publishers also have to go beyond the website. Today’s publishers are not only offering a blended approach to solving these marketing needs in modern RFPs—they are going beyond the typical RFP response to craft unique digital offerings that reach users that are engaged with digital content on multiple screens. You can’t effectively target pure audience yet on iPads, iPhones, or Android devices. Buy that’s where a lot of content consumption is rapidly shifting, Companies like Phluant (adapting online rich media ads of mobile browsing) are on the forefront of adapting display advertising to the new, mobile environment where they will be seen.

If your development plans do not include interoperability with the multiscreen media world we live in currently, then you are already becoming irrelevant. In the near future, there will be no such thing as “mobile networks” and “in-app” advertising. There will be platform solutions which enable cross-platform messaging (and accompanying analytics) in real time.

Price

A lot of the biggest mistakes modern media buyers make can be attributed to pricing. Todays’ digital media options do not lend themselves to a single RFP, with a static pricing range. The typical marketer looking to find high-income middle-age men who are “auto-intenders” may top out at $12 CPM. This is ridiculous. Marketers (especially old school direct mail marketers), know the value of finding their exact audience may be in the $100 CPM range (if they know they are reaching that exact, qualified customer), or it may be in the $1.00 CPM range (if they simply want to blanket my message to “men” in certain geotargeted area). Audiences are variable—but buying methodologies are not. In the near future, media buying will become programmatic, enabling marketers to populate a more robust RFP template with data—and receive systematic buying templates that span both buying methodologies (guaranteed and real-time) and pricing methodologies as well (CPM, CPC, CPA).

Choice

Today’s world is about choice. The modern digital marketer doesn’t have to face the straw man argument between choosing guaranteed vs. real-time audience buying; neither should he make the false choice of deciding between rich media and standard banners, when both can be deployed seamlessly across a single campaign. Moreover, it is now simple to leverage broadcast creative digitally, and run video advertising units on television, on the web, and on mobile devices simultaneously. As technology rapidly enables interplatform operability, marketers will be able to focus more upon the (all important) creative, than the delivery methodology itself.

As digital delivery systems evolve, marketers will live or die by the power of their creative to captivate. When technology companies finally enable marketers to broadcast their advertising across multiple digital channels at once (online display, video, mobile, DOOH, and cable set-top), the challenge will once again turn to creativity. In a technology-driven media world that enables marketers to produce and stream an advertising message seamlessly into the ether—it’s all about the ad, rather than where it is seen.

Up until now, the conversation in the space has been about delivering ads (by “DSPs” and RTB systems). As digital advertising delivery systems evolve, and every marketer has near ubiquitous access to platforms that enable scale and cross-platform delivery, the conversation is going to shift back to who is producing the best creative.

That’s a conversation I am looking forward to.

[This post originally appeared on 5/12/11 in eMarketing & Commerce]