An Ad Tech Temperature Check

 

HotInHerre

Ad Technology: It’s hot in herre.

 

Clayton Christensen, the father of “disruptive innovation,” would love the ad technology industry.

With more than 2,500 Lumascape companies across various verticals chasing an exit, venture funding drying up for companies that haven’t made an aggressive SAAS revenue case and the rapid convergence of marketing and ad technology, the next few years will see some dramatic shifts.

The coming tsunami of powerful megatrends is driving ad technology relentlessly forward at a time when data is king and the companies that best package and integrate it into multichannel inventory procurement will be the rulers.

In a world where scale matters most, the big are getter bigger and smaller players are getting forced out, which is not necessarily good for innovation.

Data: Powering The Next Decade Of Ad Tech

Data, especially as it relates to “people data,” is and will be the dominant theme for ad technology going forward.

Monolithic companies with access to a people-based identity graph are leaning in heavily to identity management, trying to own the phone book of the connected device era. Facebook’s connection to Atlas leverages powerful and deeply personal deterministic data, continually volunteered on a daily basis by its users, to drive targeting. Google is attaching its massive PII data set garnered through Gmail, search and other platforms to its execution platforms with its new DMP, DoubleClick Audience Manager.

Both platforms prefer to keep information on audience reach safely within their domains, leaving marketers wondering how smart it really to tie the keys of user identity in a “walled garden” with media execution.

Will large marketers embrace these platforms for their consumer identity management needs, or will they continue to leverage them for media and keep their data eggs in another basket?

While some run into the arms of powerful cloud solutions that combine data management with media execution, many are choosing to take a “church and state” approach to data and media, keeping them separate. Marketers have to decide whether the risk of tying first-party data together with someone’s media business is worth having an all-in-one approach.

Agencies Must Adapt Or Die As Consultancies Edge Into Programmatic

Media agencies have also been challenged to provide more transparency around the way they procure inventory, the various incentive schemes they have with publishers and their overall methodology for finding audiences. With cross-device proliferation, agencies must be able to identify users to achieve one-to-one marketing programs, and they need novel ways to reach those users at scale.

That means a commitment to automation, albeit one that may come at the expense of revenue models derived through percentage of spend and arbitrage. Agencies will need new ways to add value in a world where demand-side players are finding closer connections to the supply side.

As media margins collapse, agencies need to act as data-driven marketing consultants to lift margins and stay relevant. They face increasing competition from large consultancies whose bread and butter has been technology integration. It’s a tough spot but opportunities abound for smart agencies that can differentiate themselves.

Zombie Companies Die Off But Edge-Case Innovation Continues

We’ve been talking about “zombie ad tech” for years now, but we are finally starting to see the end of the road for many point solution companies that have yet to be integrated into larger mar tech “stacks.”

Data-management platforms with native tag-management capabilities are displacing standalone tag-management companies. Retargeting is a tactic, not a standalone business, which is now a status quo part of many execution platforms. Fraud detection systems are slowly being dragged into existing platforms as add-on functionality. Individual data providers are being sucked into distribution platforms and data exchanges that offer customer exposure at scale. The list goes on and on.

This is an incredibly positive thing for marketers and publishers, but it is also a challenge. Cutting-edge technologies that give a competitive advantage are rarely so advantageous after they’ve moved into a larger “cloud.” Smart tech buyers must strike a balance between finding the next shiny objects that confer differentiating value, while building a stable “stack” that can scale as they grow.

That said, the big marketing technology “clouds” offered by Adobe, Oracle and Salesforce continue to grow, as they gobble up interesting pieces of the digital marketing “stack.”

Will marketers go all-in on someone’s cloud, build their own “cloud” or leverage services offerings that bring a unified capability together through outsourcing?

Right now, the jury is out, mostly because licensing your own cloud takes more than just money, but also the right personnel and company resources to make it work. Yet, marketers are starting to understand that the capability to build automated efficiency is no longer just a function of marketing, but a way to leverage people data to drive value across the entire company.

Today’s media targeting will quickly give way to tomorrow’s data-driven enterprise strategy. It’s happening now, and quickly

New Procurement Models Explode Exchanges, Drive Direct Deals

I think the most exciting things happening in ad technology are happening in inventory procurement.

Programmatic direct technologies are evolving, adding real audience enablement. Version 1.0 of programmatic direct was the ability to access a futures marketplace of premium blocks of inventory. Most buyers, used to transacting on audience, not inventory, rejected the idea.

Version 2.0 brings an audience layer to premium, well-lit inventory, while changing the procurement methodology. I think most private marketplaces within ad exchanges are placeholders for a while, as big marketers and publishers start connecting real people data pipes together and start to buy directly. It’s happening now – quickly.

I also can see really innovative companies leaning into creating a whole new API-driven way of media planning and buying across channels that makes sense. In the near future, the future-driven approaches of companies like MassExchange will bring to cross-channel inventory procurement a methodology that is more regulated, transparent and reminiscent of financial markets. It’s a fun space to watch.

Who will begin adding algorithmic, data-science driven automation and proficiency to the planning process, not just execution and optimization in the programmatic space?

Many of those in the ad technology and media game are here for the challenge, the rapid pace of innovation and the opportunity to change the status quo. We are all getting way more than we imagined lately, in a fun, exciting and fast-moving environment that punishes failure harshly, but rewards true market innovation. Stay safe out there.

[This post was originally published in AdExchanger on 6.16.15]

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What Marketers want from AdTech

WhatDoYouWant

If you read AdExchanger regularly, you might think that nearly every global marketer has a programmatic trading strategy. They also seem to be leveraging data management technology to get the fabled “360-degree view” of their customers, to whom they are delivering concise one-to-one omnichannel experiences.

The reality is that most marketers are just starting to figure this out. Their experience ranges from asking, “What’s a DMP?” to “Tell me your current thinking on machine-derived segmentation.”

A small, but significant, number of major global marketers are aggressively leaning into data-driven omnichannel marketing, pioneering a trend that is not going anywhere anytime soon. Over the next five years, nearly every global marketer will have a data-management platform (DMP), programmatic strategy and “chief marketing technologist,” a hybrid chief marketing officer/chief information officer that marries marketing and technology. These are exciting times for people in data-driven marketing.

So, what are marketers looking for from technology today? Although these conversations ultimately become technical in nature, you soon discover that marketers want some pretty basic, “table stakes” type of stuff.

Better Segmentation Through First-Party Data 

Marketers spend a lot of time building customer personas. Once a customer is in their customer relationship management (CRM) database and generates some sales data, it’s pretty easy to understand who they are, what they like to buy and where they generally can be found. From a programmatic perspective, these are the equivalent of a car dealer’s “auto intenders,” neatly packaged up by ad networks and data providers to be targeted in exchanges.

That’s still available today, but the amazing amount of robotic traffic, click fraud and media arbitrage has made marketers realize just how loose some segment definitions may be. Data companies have a great deal of incentive to create and sell lots of auto intenders, so marketers are starting to look deeper at how such segments are actually created. It turns out that some auto intenders are people who brushed past a car picture on the web, which lumped them into a $12 cost per mille (CPM) audience segment.

Those days seem to be coming to an abrupt close as marketers increasingly use their own data to curate such segments and premium publishers, which do have auto intenders among their readerships, use data-management tools to make highly granular segments available directly to the demand side. Marketers are now willing to pay premium prices for premium audiences in a dynamic being driven by more transparency into how audiences are created in the first place. Audiences comprised of first- and second-party data will win every time in a transparent ecosystem. 

Less Waste, More Efficiency

Part and parcel of better audience segmentation is less waste and more media efficiency. The old saw, “I know half of my marketing works, I just don’t know which half,” goes away with good data and better attribution.

As an industry, we promised to eliminate waste 20 years ago. The banner ad was supposed to usher in a brave new world of media accountability, but we ended up creating a hell of a mess. Luckily, venture money backed “solutions” to the problems of click fraud, faulty measurement and endless complexity in digital marketing workflow.

Marketers don’t want to buy more technology problems they need to fix. And they don’t want to spend money chasing the same people around the web. They want to limit how much they spend trying to achieve reach. Data-management technology is starting to rein in wasteful spending, via tactics including global frequency management, more precise segmentation, overlap analysis and search suppression.

Marketers want to use data to be more precise. They are starting to leverage systems that help them understand viewability and get a better sense of attribution by moving away from stale last-click models. The days are numbered for marketers with black-box technology that creates a layer between their segmentation strategies and how performance is achieved against it.

One-To-One Communication Via Cross-Device Identity

Maybe the biggest trend and aspiration among marketers is the ability to truly achieve one-to-one marketing. A few years ago, that meant email, telemarketing and direct mail. Today, if you want to have a one-to-one customer relationship, you must be able to associate the “one” person with as many as five or six connected devices.

That is extremely difficult, mostly because we have been highly dependent on the browser-based “cookie” to determine identity. Cookie-based technologies evolved to ensure different cookies match up in different systems, but it’s a new world today.

Really understanding user identity means being able to reconcile different device signals with a universal ID. That means lots of cookies from different browsers, Safari’s unique browser signature, IDFAs, Android device IDs and even signals from devices like Roku, not to mention reliably “onboarding” anonymized offline data, such as CRM records.

Without device mapping, an individual looks like seven different devices to a marketer, making it impossible to deliver the “right message, right place, right time.” Frequency management is tougher, attribution models start to break and sequential messaging is hard to do. Marketers want a reliable way to reconcile user identity across devices so they can adapt their messages to your situation.

Data-Derived Insights 

Marketers inject tons of dollars into the advertising ecosystem and expect detailed performance reports. Each dollar spent is an investment. Some dollars create sales results, but all dollars spent in addressable channels create some kind of data.

Surprisingly, that data is still mostly siloed, with social data signals not connected to display results. Much of it is delivered in the form of weekly spreadsheets put together by an agency account manager. It seems crazy that marketers can’t fully take advantage of all the data produced by their digital marketing, but that is still very much the reality of 2015.

Thankfully, that dynamic is changing quickly. Data technology is rapidly offering a “people layer” of intelligence across all channels. Data coming into a central system can look at campaign performance across many dimensions, but the key is aggregating that data at the people level. How did a segment of “shopping cart abandoners” perform on display vs. video?

Marketers now operate under the new but valid assumption that they will be able to track performance in this way. They are starting to understand that every addressable media investment can create more than just sales – it can produce data that helps them get smarter about their media investments going forward.

It’s a great time to be a data-driven marketer.

[This post originally appeared in AdExchanger on 4.6.15]

The Agency’s Role in Data Management

MadMen

Twenty years after the first banner ad, the programmatic media era has firmly taken hold. The Holy Grail for marketers is a map to the “consumer journey,” a circuitous route filled with multiple addressable customer touchpoints. With consumers spending more of their time on mobile devices – and interacting with brands like never before through social channels, review sites, pricing comparison sites and apps – how can marketers influence customers everywhere they encounter a brand?

It’s a tough nut to crack, but starting to become an achievable reality to companies dedicated to collecting, understanding and activating their data. Marketers are starting to turn towards data management platforms (DMP), which help them connect people with their various devices, develop granular audience segments, gain valuable insights and integrate with various platforms where they can activate that data. In addition to technology, marketers also have to configure their entire enterprises to align with the new data-driven realities on the ground.

The question is: Where do marketers turn for help with this challenging, enterprise-level transition?

Many argue that agencies cannot support the type of deep domain expertise needed for the complicated integrations, data science and modeling that has become an everyday issue in modern marketing. But should data management software selection and integration be the sole province of the Accentures and IBMs of the world, or is there room for agencies to play?

For lots of software companies, having an agency in between an advertiser and their marketing platform sounds like a problem to overcome, rather than a solution. Many ad tech sellers out there have lamented the process of the dreaded agency “lunch and learn” to develop a software capability “point of view” for a big client.

Yet, there are highly compelling ways agencies add value to the software selection process. The best agencies insert themselves into the data conversation and use their media and creative expertise to influence what DMPs marketers choose, as well as their role within the managed stack.

From Digital To Enterprise

It makes perfect sense that agencies are involved with data management. The first intersection of data and media added the “targeting” column to the digital RFP. Agencies have started to evolve beyond the Excel-based media planning process to start their plans with an audience persona that is developed in conjunction with their clients. Today, plans begin with audience data applied to as many channels as are reachable. Audience data has moved beyond digital to become universal.

Agencies have also been at the tip of the spear, both from an audience research standpoint (understanding where the most relevant audiences can be found across channels) and an activation standpoint (applying huge media budgets to supply partners). Since they are on the front lines of where media dollars are expressed, they often get the first practical look at where data impacts consumer engagement. During and after campaigns conclude, the agency also owns the analytics piece. How did this channel, partner and creative perform? Why?

Having formerly limited agencies to doing campaign development and execution, marketers are now turning to the collected expertise of their agency media and analytics teams and asking them to embed the culture of audience data into their larger organization. When it’s time to select the DMP—the internal machine that will drive the people-based marketing enterprise—the agency is naturally called upon.

Data Management Is About Ownership

Although a small portion of innovative marketers have begun leveraging DMP technology and taken media execution “in-house,” the vast majority stills relies on agencies and ad tech platform partners to operate their stacks through a managed services approach. Whether a marketer should own the capability to manage its own ad technology stack is a matter of choice, but data ownership shouldn’t be. Brands may not want to own the process of applying audience data to cross-channel media, but they absolutely must own their data.

Where Agencies Play in Data Management

The Initial Approach: Most agencies have experience leveraging marketers’ first-party data through retargeting on display advertising. In an initial DMP engagement, marketers will rely on their agencies to build effective audience personas, map those to available attributes that exist within the marketer’s taxonomy and apply the segments to existing addressable channels. Marketers can and should rely on past campaign insights, attribution reports and other data insights from their agencies when test-driving DMPs.

Connect the Dots: For most marketers, agencies have been the de-facto connector of their diverse systems. Media teams operate display, video and mobile DSPs, ad serving platforms, and attribution tools. Helping a marketer and their DMP partner tie these execution platforms together, understand audience data, and the performance data generated from campaigns is a critical part of a successful DMP implementation.

Operator: Last, but not least, is the agency as operator of the DMP. Marketers want their data safely protected in their own DMP, with strong governance rules around how first-party data is shared. They also need a hub for utilizing third-party data and integrating it with various execution and analytics platforms. Marketers may not want to operate the DMP themselves, though. Agencies can win by helping marketers wring the most value from their platforms.

Marketers have strong expertise in their products, markets and customer base – and should focus on their core strengths to grow. Agencies are great at finding audiences, building compelling creative and applying marketing investment dollars across channels, but are not necessarily the right stewards of others’ data.

Future success for agencies will come from helping marketers implement their data management strategy, align their data with their existing technology stack and return insights that drive ongoing results.

[This post originally appeared in AdExchanger on 2.2.15]

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Matching Offline Data for Online Targeting

A Conversation with Live Ramp’s CEO Auren Hoffman

When all marketers have universal access to an entire world of third party online segmentation data, advertisers are increasingly turning offline for an edge. Leveraging established and deep CRM data, marketers are matching their customer databases to online cookies for targeting and retargeting, and going beyond basic demographic data by bringing multiple data sets into the digital marketing mix. I recently interviewed Live Ramp’s Auren Hoffman to learn more about how traditional databases are getting matched to online cookies, and made available for targeting.

Offline data versus online data. You hear first-party data talked about like it’s the gold standard. Just how much more valuable is a company’s first party data?

Auren Hoffman (AH): First, some clarification: Offline does not equal first-party data; nor is online equivalent to third party data.

The gold standard is not first-party data. It’s the rich knowledge (and capacity for segmentation) that lies in a company’s CRM database, typically tied to a name/address or an email address (including purchase history, direct mail, email campaigns, and loyalty). That knowledge, which is largely (but not exclusively) first-party data, exists almost exclusively offline.

Oftentimes, this specific customer knowledge – first-party data belonging to a brand or business – is augmented by complementary third-party data (for example, zip code-based psychographic typing). Also added into the mix is certain online data (largely transactional, where the customer is known) that has been taken offline (into the CRM database).

This deep customer knowledge has – before now – really only been usable offline (to manage direct marketing, for example). Customer segmentation derived from CRM data is commonly used to target certain audiences with specific messages. That same knowledge has not been – could not be – used to achieve better targeting online through display advertising… until recently.

Companies such as LiveRamp take the knowledge about individual customers from offline CRM databases to form useful and rich customer segmentation that can be “onboarded” – taken online and used for highly-focused display advertising, in a safe and privacy centric way. For example, catalog recipients (from a CRM-driven direct marketing campaign) whom it is known both purchase online and focus on a particular product line in their purchases can be transformed into an online audience with a very focused marketing message. This is what LiveRamp does: translate rich offline data (first- or third-party, or both) into anonymized online segments that can be used to create highly targeted and therefore more effective display advertising. LiveRamp is the only company focused solely on providing data onboarding that can be used to achieve “CRM Retargeting” (using CRM data to enable highly-targeted display advertising).

It should be emphasized that onboarded data is anonymized – that is, unlike CRM data which is frequently used in its individualized form (specific customers tied to an email or postal), onboarded data is aggregated based on customer segments (e.g. a possible segment could be customers who have not purchased from the brand in more than six months) who receive a specific message (e.g. special incentive to return to the brand). So the customer’s privacy is protected, while the customer is still able to receive an offer or message likely to be of specific appeal. With CRM retargeting, brands can target last year’s shoppers with relevant ads about the upcoming holiday season to remind them about your brand’s offer, regardless of if, or when they’ve been to your site.

What kind of offline data should marketers consider bringing online? What offline data do you consider to be the most valuable in terms of audience targeting?

AH: Marketers should consider any data that allows them to create more targeted – and therefore more valuable – segmentation for use in online display advertising; which will vary depending on a brand’s business and messaging strategy. The most valuable such data is that which, when linked with focused messaging, is most likely to achieve resonance with the audience segment. Onboarded data, as noted above, is anonymized; consequently the objective is not to track down and message individual consumers (which would be intrusive), but rather to develop creative messaging to groups of (anonymized) customers (e.g. lapsed customers, or those with particular product or service requirements – for instance, customers with car leases about to expire might well be interested in incentives for a new lease).

Though the most valuable data is likely to be based on transactional history or product/service preferences, it is by no means limited to this. The most valuable data is that determined by the brand to create segmentation – and the accompanying messaging – needed to elicit a positive customer response and in turn ROI.

How should marketers manage their data? Now that data is so cheap to collect, transfer, load, and store the tendency is to make almost every piece of data available for analysis. Where should marketers draw the line? What about recency? Does the cost of keeping certain datasets (transaction events, for example) recent outweigh their potential value?

AH: We’re agnostic on this. (That is, we’re not in the business of managing the data, just bridging the offline/online divide with onboarding expertise.) Each marketer must judge for him or herself the value of data in relation to its potential use for targeted segmentation.
How does it work? Please describe, in layman’s terms where possible, the various methodologies for matching offline data with an online consumer. (cookie matching, key value pair match, etc)

  • A brand (or a brand’s agency) provides LiveRamp with an encoded CRM safely through our secure upload portal.
  • LiveRamp matches your offline data keyed off an email address to an anonymous online audience via cookies with extensive coverage and high accuracy.
  • LiveRamp places the online audience on a brand’s existing DSP or DMP (or we can suggest one of our partner platform’s) & the display campaign runs as normal with a larger, more valuable, and more targeted audience.
  • Your customers see a relevant and timely message from your brand
  • LiveRamp does not buy or sell data. We do not collect any data from a site, our cookies do not contain PII, and we do not pass any site audience information to any third party.

This interview, among many others, appears in EConsultancy’s recently published Best Practices in Data Management by Chris O’Hara. Chris is an ad technology executive, the author of Best Practices in Digital Display Media, a frequent contributor to a number of trade publications, and a blogger.

This post also appeared on the iMediaConnection blog on 1/3/12.

Choosing a Data Management Platform

A Conversation with Bridget Bidlack

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. In order to combat that problem, there are now over a dozen data management platforms (DMPs) configured to help marketers and publishers leverage their first party data, and take advantage of the growing universe of 3rd party data. I recently sat down with a DMP veteran, Bridget Bidlack, to ask how one should approach choosing a platform.

To the unpracticed eye, it seems like many DMPs do exactly the same things. What are some of the subtleties and differences between the major platforms?

Bridget Bidlack (BB): It’s true that, to someone unfamiliar with the technology, the differences may seem subtle, but that’s often the case no matter what you are discussing. I recently came across a catalog that featured a violin bow for $22,000. To me they all look alike but to a virtuoso the right bow can make all the difference in the world.

That’s the way it is for marketers and the technology they rely on every day. DMPs are very different in the capabilities they provide; the approach and level of integration they are capable of; their ability to adapt to future media channels and market demands; how well they can scale in terms of the amount of data they can ingest, manage and store; and their ability to deliver actionable analytics regardless of the audience touch point.

Smart marketers who evaluate their needs and assess the full range of solutions to find the one best able to suit their needs will benefit today and in the future.

Many DMPs sprang forth from a network background. Is there an advantage to having a heritage in the online media business? Is it better to leverage a “pure play” DMP that has been built from the ground up?

BB: It’s really important to bear in mind the differences between a DMP designed exclusively for display media and an enterprise DMP designed for the needs major brands that require multi touchpoints.

Too often people behave as though display advertising is the be-all and end-all of marketing, and that’s probably true inside an agency. But enterprise marketers have a much broader palette of customer and prospect touchpoints they need to manage. That’s where a purpose-built enterprise DMP really shows its value. So, what are the differences between a display-focused DMP and an enterprise DMP?

  • First, an enterprise DMP ingests and normalizes data from a wide variety of sources
  • Second, is to automate the way data is organized and segmented
  • Third, is to be configurable enough to use an organization’s unique approach to audience identification and data match key models
  • Fourth, is to make the enterprise’s unique data actionable across ALL touch points in real time
  • Fifth, is to deliver consistent messages and enforce offer eligibility across all channels – not just display,  but important customer channels such as email, click to chat and SMS for example.

You have worked with some of the world’s largest and most aggressive marketers to help them leverage their data. What were some of the challenges you encountered at the enterprise level that surprised you?

BB: This probably doesn’t come as a surprise, but in large organizations it is sometimes difficult for individual departments to put the greater good of the overall organization ahead of their own goals. Typically this is because of the way individual departments are measured. It’s important to understand the needs of all departments and how an enterprise DMP can help meet those needs. The costs and benefits of DMPs are enterprise-wide and their benefits should be evaluated that way.

Some organizations have created systems that provide DMP-like capabilities. In these situations, a company can weigh the total cost of ownership and benefits of building out the full DMP functionality versus working with an available enterprise DMP. There are a number of factors to consider: speed to market, ROI, domain expertise and consumer privacy, to name a few.

Large organizations have many disparate data sets that are used in many different ways. Sometimes, just getting a list of all the different data sources and attributes is a challenge. Often, there isn’t a shared taxonomy that can be used across departments. Data management and permissions can also become an issue as different departments might have rights and permissions to different data sets that others do not. All of this points to the challenge of finding a unique ID to link all of an organization’s data for a given customer together in a way that makes it accessible and actionable where and when it is needed.

How big is the market for DMPs? How many companies actually have the data challenges that warrant leveraging a “big data” platform for marketing?

BB: The market is growing so fast that this is a difficult question to answer. Any marketer would love to have one platform to reach their customers across any current or future channel. Some marketers might claim they’re comfortable limiting their reach to channel-specific audiences available through specific ad networks or email providers, but that’s rare. Sophisticated marketers want to use the full force of tools, technology and insights at their disposal. They want to use their own data along with third-party data, they want to take into account interactions on their website, as well as those taking place on other marketing channels to inform every message put in front of a consumer. To do otherwise seems like marketing with one hand tied behind your back. Who would choose that?

What are some of the considerations to bear in mind? The number of disparate data systems they are working with, the number of touch points they use to reach their consumers, how frequently the data they depend on is updated, how quickly they need access to the data and the sheer amount of data that they have on their customers. They also need to ask themselves whether their goals can be met with internal systems or by using multiple point products. In most cases it will be more efficient, economical and effective to work with a complete platform able to meet all their needs.

Let’s pretend all current DMPs have exactly the same attributes right now. What should I look for on a DMPs product roadmap to tell me they are going to offer the next great differentiator? Is it Hadoop compatibility? Fast query speeds, based on different storage abilities?

BB: If I were in the market for a DMP and all things were equal, the items I’d like to see in a roadmap would be:

  • A robust and constantly expanding set of self-service tools to allow end users to manage and use their data independently and in a scalable way
  • Continued investment in analytics and modeling to allow customers to understand data in the ways that will make it work best for them. There should also be a balance of pre-defined reports that provide deep insights out of the box, as well as the ability for users to customize them to meet their own specific needs
  • The ability to adapt to emerging market trends and new technologies
  • Attribution modeling that provides the ability to implement custom approaches into the media planning, buying and decisioning processes

Integration seems to be the name of the game. How important are existing server-to-server integrations? Are DMPs becoming truly “plug and play” as they plug into more and more various technologies?

BB: Having open web service APIs is important for any DMP that claims to provide ‘plug and play’ capabilities. This approach makes it fast and flexible and easy to integrate with new partners, channels and data sources. Without this type of framework, integration can become a nightmare of custom code, delays and missed opportunities.

What about data? Does the company with the most data win? Should I select a DMP based on the ability not just to manage first party data, but for their ability to link my data to the wider universe?

BB: The idea that more data equals better performance is much too simplistic. When it comes to data, the things that matter are how it is filtered, analyzed and put to work to inform decisions. Quantity isn’t the key at all; it’s all about having the right data and being able to act on it to reach customers and prospects at the right time through the right channels.

The ability to centralize, normalize and make data actionable through any touch point needs to be at the core of any enterprise DMP. The DMP should also close the loop by ingesting campaign data from all channels and vendors, as well as offline activities like in-store sales and call center interaction. The data can be surfaced in a way that is meaningful to the marketer. This means marketers need the ability to define custom attribution models to reflect their unique sales funnels. Based on this information, marketers can measure ROI and inform future strategies.

Data is key but it has to be available, accurate and actionable for it to have the kind of impact that marketers demand.

Will be still be talking about “DMPs” in 2 years, or is there another acronym coming along that marketers need to be aware of?

BB: In the future, marketers will continue to invest in learning about and tapping into the latest channels, networks and screens through which consumers are living their increasingly digital lives. Whenever new channels, networks and screens emerge, there will be an evolution and expansion of the data available to marketers. This means that the systems and technologies for ingesting, testing and validating data will continue to be valued – probably even more than they are today.

Smart marketers increasingly understand the importance of being customer-centric and this implies the need to be data-centric. Knowing this they will continue to invest in data management technologies. They will also bring these capabilities in-house as they have in the past with their core CRM and operational data. Even as the hardware and software running their data management platform migrates to the cloud, it will still be viewed as an “owned” solution. This means that the technology companies that marketers partner with to develop and execute their marketing campaigns will need to continue to invest in becoming data savvy and fluent with the tools and systems in the marketplace.

 This interview, among many others, appears in EConsultancy’s recently published Best Practices in Data Management by Chris O’Hara. Chris is an ad technology executive, the author of Best Practices in Digital Display Media, a frequent contributor to a number of trade publications, and a blogger.

This post also appeared in the iMediaConnection blog on 12/11/12.

The Five Things to Expect in a DMP

Getting back control over their inventory is giving publishers a lot to think about.

“We want to make sure that we’re controlling what happens with data . . . we want to make sure we control pricing. Control’s a very important message. We don’t want there to be a cottage industry built on our backs” – Nick Johnson, SVP, NBC Universal

What do publishers really want? It’s simple, really: Power and control. In order to survive the ad technology era, publishers need the power to monetize their audiences without relying on third parties, and complete control over how they sell their inventory. In this era of “Big Data,” there is a fire hose stream of tremendously valuable information for publishers to take advantage of, such as keyword-based search data, attitudinal survey data, customer declared data from forms, page-level semantic data, and all the 3rd party audience data you can shake a stick at.

All of this data (cheap to produce, and ever-cheaper to store) has given rise to companies who can help publishers bring that data together, make sense of it, and use it to their advantage. Currently, ad technology companies have been using the era of data to their advantage, utilizing it to create vertical ad networks, ad exchanges, data exchanges, DSPs, and a variety of other smart-sounding acronyms that ultimately purport to help publishers monetize their audiences, but end up monetizing themselves.

Rather than power the ad tech ecosystem, what if data could actually help publishers take back their audiences? If “data is the new gold” as the pundits are saying, then smart publishers should mine it to increase margins, and take control of their audiences back from networks and exchanges. Here are the five things a good data management platform should enable them to do:

  • Unlock the Value of 1st Party Data: Publishers collect a ton of great data, but a lot of them (and a LOT of big publishers) don’t leverage it like they should. Consider this recent stat: according to a recent MediaPost article, news sites only use in-site audience targeting on 47% of their impressions, as opposed to almost 70% for Yahoo News.  By leveraging site-side behavioral data, combined with CRM data and other sources, it is possible to layer targeting on almost every impression a publisher has. Why serve a “blind” run-of-site (ROS) ad, when you can charge a premium CPM for audience-targeted inventory?
  • Decrease Reliance on 3rd Parties: The real reason to leverage a DMP is to get your organization off the 3rd party crack pipe. Yes, the networks and SSPs are a great “plug and play” solution (and can help monetize some “undiscoverable” impressions), but why are publishers selling raw inventory at $0.35 and letting the people with the data resell those impressions for $3.50? It’s time to turn away those monthly checks, and start writing some to data management companies that can help you layer your own data on top of your impressions, and charge (and keep) the $3.50 yourself. Today’s solutions don’t have to rely on pre-packaged 3rd party segments to work, either, meaning you can really reduce your data costs. With the right data infrastructure, and today’s smart algorithm-derived models, a small amount of seed data can be utilized to create discrete, marketable audience segments that publishers can own, rather than license.
  • Generate Unique Audience Insights: Every publisher reports on clicks and impressions, but what advertisers are hungry for (especially brand advertisers) are audience details. What segments are most likely to engage with certain ad content? Which segments convert after seeing the least amount of impressions? More importantly, how do people feel about an ad campaign, and who are they exactly? Data management technology is able to meld audience and campaign performance data to provide unique insights in near real-time, without having to write complicated database queries and wait long times for results. Additionally, with the cost of storing data getting lower all the time, “lookback windows” are increasing, enabling publishers to give credit for conversion path activity going back several months. Before publishers embraced data management, all the insights were in the hands of the agency, who leveraged the data to their own advantage. Now, publishers can start to leverage truly powerful data points to create differentiated insights for clients directly, and provide consultative services with them, or offer them as a value-added benefit.
  • Create New Sales Channels: Before publisher-side data management, when a publisher ran out of the Travel section impressions, he had to turn away the next airline or hotel advertiser, or offer them cheap ROS inventory. Now, data management technology can enable sales and ops personnel to mine their audience in real time and find “travel intenders” across their property—and extend that type of audience through lookalike modeling, ensuring additional audience reach. By enabling publishers to build custom audience segments for marketers on the fly, a DMP solution ensures that no RFP will go unanswered, and ROS inventory gets monetized at premium prices. 
  • Create Efficiency: How many account managers does it take to generate your weekly ad activity reports? How much highly paid account management time are publishers burning by manually putting together performance reports? Why not provide an application that advertisers can log into, set report parameters, and export reports into a friendly format? Or, better yet, a system that pre-populates frequent reports into a user interface, and pushes them out to clients via an e-mail link? You would think this technology was ubiquitous today, but you would be wrong. Ninety-nine percent of publishers still do this the hard (expensive) way, and they don’t have to anymore.

It’s time for publishers to dig into their data, and start mining it like the valuable commodity it is. Data used to be the handcuffs which kept publishers chained to the ad technology ecosystem, where they grew and hosted a cottage industry of ad tech remoras. The future that is being written now is one of publishers’ leveraging ad technologies to take back control, so they can understand and manage their own data and have the freedom to sell their inventory for what it is truly worth.

That’s a future worth fighting for.

[This post originally appeared in ClickZ on 2/29/12]