The Identity Based Data Platforms of the Future

Today’s disparate traditional databases and connected devices make “people-based” marketing as difficult and awkward as this interaction. 

Currently, marketers don’t have a single source of truth about their consumers. Tomorrow, there must be a single place to build consumer profiles with rich attribute data, and provisioned to the systems of engagement where that consumer spends their time.

At a recent industry event, we heard a lot about the upcoming year in marketing, and how data and identity will play a key role in driving marketing success.

As a means to master identity, some companies have heralded the idea of the customer data platform (CDP), but the category is still largely undefined. For example, many Salesforce customers believe that they already have a CDP. The reason? They have several different ways of segmenting known and unknown audiences between a data management platform (DMP) and CRM platform.

In an article I wrote here last year, I introduced a simple “layer cake” marchitecture, describing the three core competencies for effective modern marketing. In such a fast moving and evolving industry, I have since refined it to the core pillars of identity, orchestration and intelligence:

With this new marchitecture, brands have the ability to know consumers, engage with them through each touchpoint and use artificial intelligence to personalize each experience.

Mastering each layer of complexity is difficult, requiring an investment in time, technology and people. Lets focus on perhaps the most important – the data management layer where the new CDP category is trying to take hold.

The next wave of data management

By now, it’s safe to say marketers have mastered managing known data. A few years ago, when I was working for a software company that also managed postal mailing lists, I was astonished at the rich and granular data attached to mailing lists. There is a reason direct mail companies can justify $300 CPMs – it works, because direct marketers truly know their customers.

After joining Salesforce, I was similarly awed by the power to carefully segment CRM data, and provision journeys for known customers spanning email, mobile, Google and Facebook, customer service interactions and even community websites.

How can we get to this level of precision in the world of unknown (anonymous) consumer data?

As marketing technology and advertising technology converge, so must the identity infrastructure that underlies both. Put more simply, tomorrow’s systems need a single, federated ID that is trust-based. Companies must have a single source of truth for each person, the ability to attach various keys and IDs to that unified identity, as well as have a reliable and verifiable way to opt people out of targeting.

Let’s take a look at what that might look like:

This oversimplification looks at the various identity keys used for each system and the channels they operate in. Today, the CRM is the system of record for engaging consumers directly in channels like direct mail, email campaigns and service call centers. The DMP, on the other hand, is the system of record for more passive, anonymous engagement in channels like display, video and mobile.

When consumers make themselves known, they “pull” engagement from their favorite brands by requesting more information and opting into messaging. At the top of the funnel, we “push” engagements to them via display ads and social channels.

As a marketer, if you have the right technologies in place, you can seamlessly connect the two worlds of data for more precise consumer engagement. The good news is that, martech and adtech have already converged. Recent research from Salesforce shows that 94% of marketers use CRM data to better engage with consumers through digital advertising, and over 91% either already own or plan to adopt DMP over the next year.

So, if mastering consumer identity is the most important element in building tomorrow’s data platform then what, exactly, are the capabilities that need to be addressed? There are three:

1. A single data segmentation engine

Currently, marketers don’t have a single source of truth about their consumers.

Here’s why: Brands build direct mail lists and email lists in their CRM. Separately, they build digital lists of consumers in a DMP tool. Then, they have lists of social handles for followers in various platforms like Facebook and Twitter. Consumer behaviors like browsing and buying that happen on the ecommerce platforms are often not integrated into a master data record. And distributed marketing presents a challenge because a big mobile company or auto manufacturer may have thousands of franchised locations with their own, individual databases.

Segmentation is all over the place. Tomorrow, there must be a single place to build consumer profiles with rich attribute data, and provisioned to the systems of engagement where that consumer spends their time.

2. Data pipelining and governance capabilities

This identity layer must also have the ability to provision data, based on privacy and usage restrictions, to systems of engagement.

For example, when a consumer buys shoes, they should be suppressed from promotions for that product across all channels. When a consumer logs a complaint on a social channel, a ticket needs to be opened in the call center’s system for better customer service. When a person opts out and chooses to be “forgotten,” the system needs to have the ability to delete not only email addresses, but hundreds of cookies, platform IDs and other addressable IDs in order to meet compliance standards with increasingly restrictive privacy laws and, more importantly, giving consumers control over their own data.

Finally, marketers need the ability to ingest valuable DMP data back into their own data environments to enrich user profiles, perform user scoring, as well as build propensity models and lifetime value scores. This requires granular data storage, fast processing speeds and smart pipelines to provision that data.

3. Leaping from DMPs to holistic data management

Ad technology folks are guilty of thinking of cross-device identity (CDIM) as the definition of identity management. Both deterministic and predictive cross-device approaches are more important than ever, but in a world where martech and adtech are operating on the same budgets and platform, today’s practitioner must think more broadly.

Marketers can no longer depend solely on another party’s match table to bridge the divide between CRM and DMP data. A more durable, and privacy-led connector between known and unknown ID types is required. Moreover, when they can, marketers need the ability to enrich email lists with anonymous DMP attributes to drive more performance in known channels—now only possible when a single party manages the relationship.

These three tenets of identity are the starting point for building the data platform of the future. The interest and excitement around CDPs is well placed, and a positive sign that we are evolving our understanding of identity as the driving force behind the changes in marketing.

[This article originally appeared in Econsultancy’s blog on 2/1/2018]

Five controversial predictions for programmatic advertising in 2016

 

This picture is as bad as my prediction that beacons would provide marketers with scaled, closed-loop attribution in 2016. Didn’t happen. Not even close.  

Programmatic advertising continued to creep into the generalist marketer’s consciousness in 2015.

 

If you’re interested, we recently wrote up a handy digest of some of 2015’s programmatic trends.

But enough of looking backwards, let’s look in the crystal ball and ask ‘What’s in store for 2016?’

Yet again, I’ve recruited two experts to help. Chris O’Hara, VP Strategic Accounts at Krux Digital (and Econsultancy’s programmatic guru – see his articles and research here), and James Bourner, Head of Display at Jellyfish.

Here’s what they had to say…

Real-world attribution may become… well, a reality

Chris O’Hara, VP Strategic Accounts at Krux Digital

One of the biggest gaps with digital media, especially programmatic, is attribution. We still seem to have the Wannamaker problem, where “50% of my marketing works, I just don’t know which 50%.”

Attitudinal “brand lift” studies and latent post-campaign sales attribution modeling have been the defacto for the last 15 years, but marketers are increasingly insisting on real “closed loop” proof. e.g. “Did my Facebook ad move any items off the shelf?”

We are living in a world where technology is starting to shed some light on actual in-store purchases, such that we are going to be able to get ecommerce-like attribution for Corn Flakes soon.

In one real world example, a CPG company has partnered with 7-11, and placed beacon technology in the store.

Consumers can receive a “get 20% off” offer on their mobile device, via notification, when the they approach the store; the beacon can verify whether or not they arrive at the relevant shelf or display and an integration with the point-of-sale (POS) system can tell (immediately) whether the purchase was made.

These marketing fantasies are becoming more real every day.

Cross-device targeting is important, but so is improving mobile inventory

James Bourner, Head of Display at Jellyfish

2016 will be the year of mobile: Just kidding!

Although on a more serious note, 2016 will be the year of more measured and more integrated mobile activity – we have only really just started to get to grips with cross-device targeting and tracking on a macro level.

While the big companies who are making a play for control of the ad tech industry will put a lot of emphasis on cross-device targeting and tracking in their battle plans, I think there will be a lot of improvements to the quality of inventory, especially in apps.

A lot of mobile supply is from developers, not traditional publishers, which has led to quality issues.

However, as we are now becoming very discerning in what we buy in mobile hopefully the developers will respond to the data and not be tempted to place banners quite so close to where accidental clicks may occur!

Google has been trying to prevent accidental clicks since 2012.

Frequency management will reduce waste and improve UX

Chris O’Hara, VP Strategic Accounts at Krux Digital

Before marketers could effectively map users to all of their various devices (cross-device identity management) and also match users across various execution platforms (hosting a “match table” that assures user #123 in my DMP is the same guy as user #456 in DataXu, as an example), they were helpless to control frequency to an individual.

Recent studies have revealed that, when marketers are only frequency capping at the individual level, they are serving as many as 100+ ads to individual users every month, and sometimes much, much more.

What if the user’s ideal point of effective frequency is only 10 impressions on a monthly basis? As you can see, there are tremendous opportunities to reduce waste and gain efficiency in communication.

This means big money for marketers, who can finally start to control their messaging – putting recovered dollars back into finding more reach, and starting to influence their bidding strategies to get users into their “sweet spot” of frequency, where conversions happen.

It’s bad news for publishers, who have benefitted from this “frequency blindness” inadvertently. Now, marketers understand when to shut off the spigot.

Increased creativity will harness new forms of inventory

James Bourner, Head of Display at Jellyfish

From the buy side we will be looking forward to more video-on-demand inventory and new areas of supply opening up, especially for the UK market, which is hugely exciting.

Closely linked to this will be far more involvement from the creative guys.

There have been rumblings in the programmatic community for some time that we do not exploit creativity enough and we need to encourage our creative counterparts to the possibilities of programmatic, whether that be simply more permutations of ads to complement targeting or a more subtle but fundamental shift in some of the tools used to build creative.

Additionally, 2016 will see more large and impactful formats, skins and take-over placements served programmatically. This is obviously excellent for both media planners and buyers as well as the creative teams.

On the subject of placements there will be a proliferation of in-feed display (or native-type placements) becoming available programmatically. 2016 will also see more connected TV and digital radio exchanges being added into the programmatic supply line.

Programmatic out of home has been on the horizon for a while but I would predict connected TV will be the faster growing element of these.

An in-stream Guardian ad format. James expects more in-feed display to be available programmatically.

We should probably let the machines decide

Chris O’Hara, VP Strategic Accounts at Krux Digital

The adoption of advanced data technology is starting to change the way media is actually planned and bought. In the past, planners would use their online segmentation to make guesses about what online audience segments to target, and test-and-learn their way to gain more precision.

Marketers basically had to guess the data attributes that comprised the ideal converter. Soon, algorithms will start doing the heavy lifting.

What if, instead of guessing at the type of person who buys something, you could start with the exact composition of that buyer? Today’s machine learning algorithms are starting at the end point in order to give marketers a huge edge in execution.

In other words, now we can look at a small group of 1,000 people who have purchased something, and understand the commonalities or clusters of data attributes they all have in common.

Maybe all buyers of a certain car share 20 distinct data attributes. Marketers can have segments automatically generated from that data, and expand it from there.

This brand new approach to segmentation is a small harbinger of things to come, as algorithms start to take over the processes and assumptions of the past 15 years and truly transform marketing.

Econsultancy runs Creatve Programmatic, a one day conference in London, as well as providing training on programmatic advertising.

Know these Five AdTech Memes for 2014

Well, at least it’s not the “year of mobile” again. Or, maybe it is. After several days of media investment banking conferences (Gridley and JEGI), I can reliably report that 2014 will be “the year” of many uber-trends ,some of which will enrich the M&A bankers who have a focus on the increasingly frothy ad technology and marketing space. Here are five memes to consider:

“Mobile First”

If you were to believe every ad tech panelist, you might be inclined to throw your laptop in the East River. Apparently—despite desktop only slightly starting to lose overall time-spent share to mobile on a year-over-year basis—nobody is developing ad tech solutions for the desktop anymore. Everyone is “mobile first,” meaning that they are writing code for tablet and mobile phone browsers and apps before developing solutions for the poor laptop or desktop computer. Of course, mobile devices are showing explosive growth, and clearly where the majority of consumers’ time will be found (as evidenced by the 8 of 10 people at my conference table multitasking during the eMarketer presentation which laid out the mobile data). This might be only a slight exaggeration when it comes to mobile eCommerce, which is trending to dominate the vast majority of online sales transactions in just a short time. Also, in case you missed this, it is now passé to call “mobile” “mobile.” Companies are so hip to the growth in portable digital devices that they just talk about “reach” rather than distinguishing between “tablets” and “smartphones.” You know it’s really the “year of mobile” when it’s too lame to talk about.

“No Cookie, No Problem”

Guess what? Nobody is worried that cookies are going away. Again, if you spend all of your time in conference ballrooms listening to panelists, you naturally understand that cookies are a thing of the ancient past, rather than the data currency without which 80% of Lumascape companies could not credibly operate. In fact, if the cookie disappeared tomorrow, ad tech players would simply go with a “statistical ID” or another cool sounding identification technology that is being invented somewhere. I am really glad that no one is particularly worried but—hearing this meme several times over the past week—I would be interested in how many platforms and ad networks have developed and deployed data technologies that enable them to do audience targeting at scale without cookies. What I think the reality of the situation might be is that cookie technology is replaceable, but if legislation changes suddenly or Google Chrome decides to switch things up, there could be huge trouble in Luma land. So much value destruction in so short a period is just something not fun to talk about at M&A conferences.

“Stack”

The idea of the “technology stack” is not new for 2014, but what has changed is that tons of point solutions that were funded in 2008 are still unprofitable, their VCs are at the end of their fund lifespans, and it’s time to find an exit. That means someone unprofitable point solution can either become a part of another’s “stack” or everyone can take their toys and go home. The problem with everyone wanting you to have a “stack” is that they are expensive to build and also expensive to license via SaaS. Small players cannot afford a “stack” and the big players already have them. That dynamic is going to create a ton of M&A activity in 2014, as vulnerable point-solution providers, some with excellent technology, succumb to larger integrators. As repeatedly pointed out, the biggest players in the marketing space (IBM, Adobe, Salesforce, etc.) represent the vast majority of M&A dollar volume, all of which has gone towards augmenting “stacks”—and it doesn’t look like they are going to be done anytime soon. There are a lot of good engineers that aren’t going to exit big at their point solution company, and may be ready for a comparatively cushy work life in the bosom of corporate behemoths that offer unlimited Mountain Dew and Skittles in the company snack room. Look for lots more M&A, and much of it “aquihire” focused.

The Funnel is Dead…It’s Now the “Customer Journey”

Everyone now has to have an “omnichannel-capable programmatic offering.” That’s the one parked right next to my Unicorn. Not that the instinct is incorrect—the proliferation of screens means that marketers have to reach people along their “consumer journey.” It’s no longer a trip down the sales funnel, but a twisting landscape where the consumer pushes you information through various social interactions. The smart marketer has to be ready at the drop of a hat to deliver perfect, personalized messages into the consumer’s smartphone at the “moment of truth” before a purchase—and, at the very least, be prepared for various “Oreo” social media moments that can create “earned” media at scale. Sounds like marketers may actually start to miss the old “AIDA” funnel!

“Sutton Pivot”

One of 2013’s memes was the notion the “Sutton Pivot,” or running where the display money is—namely, the 70% of digital dollars that get transacted through the RFP channel. That’s where we get to complain endlessly about funding the “23 year old media planner” with “sneaker parties.” David Moore remarked at the recent JEGI conference that “50% of the cost of a campaign” went into the complexity of planning and delivering it. That sounds like a lot, but might be only a slight exaggeration. Everyone wants everything more programmatically, but the problem is that publishers haven’t quite given up yet. They are still keeping the premium inventory to themselves and out of the exchanges. “Programmatic everywhere” may become a reality…in five or six years. But old habits (and buying methodologies) die hard. In the meantime, everyone with a “platform” is going to try and figure out how to automate the inefficient buying process and try and get some of that 70% flowing through a system that creates a nice “percentage of spend” platform fee. 2014 will see this trend accelerate.

Happy New Year!

Every one of these memes will produce a ton of innovation, lots of M&A, a good deal of mid- to senior- level hiring, and plenty of bankers fees, so don’t worry! 2014 looks like a great year for ad technology!

[Originally published in AdExchanger on 1.23.2014]

Why 2013 will be the Year of Premium Guaranteed

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

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

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

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

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

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

• There’s a Natural Cap on RTB Growth: I think today’s RTB technology is the best place to buy remnant inventory. As long as there are low-value impressions to buy, and as long as publishers continue to festoon their pages with IAB-standard banners, there will need to be a technology solution to navigate through the sea of available inventory, and apply data (and algorithms) to choose the right combination of inventory and creative to reach defined performance goals. While the impressions may grow, the real cap on RTB growth will be the most important KPI of them all: Share of time spent. Marketers spend money where people spend their time, whether it’s on television, Twitter, radio, or Facebook. When people spend less time on the inventory represented within exchanges, then the growth trend will reverse itself. (Already we are seeing a significant shift in budget allocation from “traditional” exchanges to FBX).

• The Pool is Still Dirty: It goes without saying, but the biggest problem in terms of RTB growth is brand safety. The type of inventory available in exchanges that sells, on average, for less than a dollar is probably worth just that. When you buy an $850 suit from Joseph A. Bank—and receive two free suits, two shirts, and two ties—you feel good. But it doesn’t take much figuring to understand that you just bought 3 $200 suits, two $75 shirts, and two $50 ties. Can you get $15 CPM premium homepage inventory for $3 CPM? No…and you never will be able to, but that type of inventory is just what the world’s largest marketers want. They would also like URL-level transparency into where their ads appeared, a limit on the number of ads on a page (share of voice), and some assurance that their ads are being seen (viewability).  Inventory will continually grow, but good, premium inventory will grow more slowly.

• It’s Not about Private Exchanges: Look, there’s nothing wrong with giving certain advertisers a “first look” at your premium inventory if you are a publisher.  Auto sites have been pursuing this concept forever. Big auto sites guarantee Ford, for example, all of the banner inventory associated with searches for Ford-branded vehicles over the course of a year. This ensures the marketer gets to his prospect when deep in the consideration set. Big auto sites may create programmatic functionality around enabling this type of transaction, but private exchange functionality isn’t going to be the savior of RTB, just necessary functionality. Big marketers want control of share of voice, placement, and flexibility in rates and programs that extend beyond the functionality currently available in DSPs. As long as they are spending the money, they will get—and demand—service.

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

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

Best Practices in Digital Display Media (Interview)

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

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

Why did you write Best Practices in Digital Display Media?

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

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

What was the methodology you used to put it together?

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

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

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

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

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

To learn more about the Best Practices in Digital Display Advertising Guide, download the report here.

The Data Driven Agency

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]

Know Your Audience

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]