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.

Choosing a Data Management Platform

“Big  Data”  is  all  the  rage  right  now,  and  for a good reason. Storing tons and tons of data has gotten very inexpensive, while the accessibility of that data has increased substantially in parallel. For the modern marketer, that means having access to literally dozens of disparate data sources, each of which cranks out large volumes of data every day. Collecting, understanding, and taking action against those data sets is going to make or break companies from now on. Luckily, an almost endless variety of companies have sprung up to assist agencies and advertisers with the challenge. When it comes to the largest volumes of data, however, there are some highly specific attributes you should consider when selecting a data management platform (DMP).

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

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

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

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

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

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

First Party Data

  • CRM data, such as user registrations
  • Site-site data, including visitor history
  • Self-declared user data (income, interest in a product)

Second Party Data

  • Ad serving data (clicks, views)
  • Social signals from a hosted solution
  • Keyword search data through an analytics platform or campaign

Third Party Data

  • Audience segments acquired through a data provider

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

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

Making it Work
At the end of the day, it’s  not  just  about  getting  all  kind  of  nifty  insights  from  the  data.  It’s   valuable to know that your visitors that were exposed to search and display ads converted at a 16% higher rate, or that your customers have an average of two females in the household.  But  it’s   making those insights meaningful that really matters.
So, what to look for in a data management platform in terms of actionability? For the large agency or advertiser, the basic functionality has to be creating an audience segment. In other words, when the blend of data in the platform reveals that showing five display ads and two SEM ads to a household with two women in it creates sales, the platform should be able to seamlessly produce that segment and prepare it for ingestion into a DSP or advertising platform. That means having an extensible architecture that enables the platform to integrate easily with other systems.

Moreover, your DSP should enable you to do a wide range of experimentation with your insights. Marketers often wonder what levers they should pull to create specific results (i.e., if I change my display creative, and increase the frequency cap to X for a given audience segment, how much will conversions increase)? Great DMPs can help built those attribution scenarios, and help marketers visualize results. Deploying specific optimizations in a test environment first means less waste, and more performance. Optimizing in the cloud first is going to become the new standard in marketing.

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

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

Available DMPs, by Type
There are a wide variety of DMPs out there to choose from, depending on your need. Since the space is relatively new, it helps to think about them in terms of their legacy business model:

  • Third Party Data Exchanges / Platforms: Among the most popular DMPs are data aggregators like BlueKai and Exelate, who have made third  party  data  accessible  from  a  single  user  interface.  BlueKai’s  exchange approach enables data buyers  to  bid  for  cookies  (or  “stamps”)  in  a  real-time environment, and offers a wide variety of providers to choose from. Exelate also enables access to multiple third party sources, albeit not in a bidded model. Lotame offers  a  platform  called  “Crowd  Control”  which  was  evolved  from  social   data, but now enables management of a broader range of third party data sets.
  • Legacy Networks: Certain networks with experience in audience segmentation have evolved to provide data management capabilities, including Collective, Audience Science, and Turn. Collective is actively acquiring assets (such as creative optimization provider, Tumri14) to  broaden  its  “technology   stack”  in  order  to  offer  a  complete  digital  media  solution  for  demand  side customers. Turn is, in fact, a fully featured demand-side platform with advanced data management capabilities, albeit lacking  the  backend  chops  to  aggregate  and  handle  “Big  Data”  solutions  (although  that  may   rapidly change, considering their deep engagement with Experian). Audience Science boasts the most advanced native categorical audience segmentation capabilities, having created dozens of specific, readily accessible audience segments, and continues to migrate its core capabilities from media sales to data management.
  • Pure Play DMPs: Demdex (Adobe), Red Aril, Krux, and nPario are all pure-play data management platforms, created from the ground up to ingest, aggregate, and analyze large data sets. Unlike legacy networks, or DMPs that specialize in aggregating third party data sets, these DMPs provide three core offerings: a core platform for storage and retrieval of data; analytics technology for getting insights from the data with a reporting interface; and applications, that enable marketers to take action against that data, such as audience segment creation, or lookalike modeling functionality. Marketers with extremely large sets of structured and unstructured data that go beyond ad serving and audience data (and may include CRM and transactional data, as an example), will want to work with a pure-play DMP

This post is an excerpt of Best Practices in Digital Display Advertising: How to make a complex ecosystem work efficiently for your organization All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording or any information storage and retrieval system, without prior permission in writing from the publisher.

Copyright © Econsultancy.com Ltd 2012

Same Turkey, New Knife

The way the ad tech world looked pre-DSP...and pre-DMP

Technology may still capture the most advertising value, but what if publishers own it?

A few years ago, ad technology banker Terence Kawaja gave a groundbreaking IAB presentation entitled, “Parsing the Mayhem: Developments in the Advertising Technology Landscape.” Ever since then, his famed logo vomit slide featuring (then) 290 different tech companies has been passed around more than a Derek Jeter rookie card.

While the eye chart continues to change, the really important slide in that deck essentially remains the same. The “Carving up the stack” slide (see above), which depicts how little revenue publishers see at the end of the ad technology chain, has changed little since May 2010. In fact you could argue that it has gotten worse. The original slide described the path of an advertiser’s $5 as it made it’s way past the agency, through ad networks and exchanges, and finally into the publisher’s pocket.

The agency took about $0.50 (10%), the ad networks grabbed the biggest portion at $2.00 (40%), the data provider took two bits (5%), the ad exchange sucked out $0.35 (7%), and the ad server grabbed a small sliver worth $0.10 (2%), for a grand total of 64%. The publisher was left with a measly $1.80. The story hasn’t changed, and neither have the players, but the amounts have altered slightly.

While Kawaja correctly argued that DSPs provided some value back to both advertisers and publishers through efficiency, let’s look ahead through the lens of the original slide. Here’s what has happened to the players over the last 2 years:

  • Advertiser: The advertiser continues to be in the cat bird seat, enjoying the fact that more and more technology is coming to his aid to make buying directly a fact of life. Yes, the agency is still a necessary (and welcomed) evil, but with Facebook, Google, Pandora, and all of the big publishers willing to provide robust customer service for the biggest spenders, he’s not giving up much. Plus, agency margins continue to shrink, meaning more of their $5.00 ends up as display, video, and rich media units on popular sites.
  • Agency: It’s been a tough ride for agencies lately. Let’s face it: more and more spending is going to social networks, and you don’t need to pay 10%-15% to find audiences with Facebook. You simply plug in audience attributes and buy. With average CPMs in the $0.50 range (as opposed to $2.50 for the Web as a whole), advertisers have more and more reason to find targeted reach by themselves, or with Facebook’s help. Google nascent search-keyword powered display network isn’t exactly helping matters. Agencies are trying to adapt and become technology enablers, but that’s a long putt for an industry that has long depended on underpaying 22 year olds to manage multi-million dollar ad budgets, rather than overpaying 22 year old engineers to build products.
  • Networks: Everyone’s talking about the demise of the ad network, but they really haven’t disappeared. Yesterday’s ad networks (Turn, Lotame) are today’s “data management platforms.” Instead of packaging the inventory, they are letting publishers do it themselves. This is the right instinct, but legacy networks may well be overestimating the extent to which the bulk of publishers are willing (and able) to do this work. Networks (and especially vertical networks) thrived because they were convenient—and they worked. Horizontal networks are dying, and the money is simply leaking into the data-powered exchange space…
  • Data Providers: There’s data, and then there’s data. With ubiquitous access to Experian, IXI, and other popular data types through 3rd party providers, the value of 3rd party segments has declined dramatically. Great exchanges like eXelate give marketers a one-stop shop for almost every off-the-shelf segment worth purchasing, so you don’t need to strike 20 different license deals. Yet, data is still the lifeblood of the ecosystem. Unfortunately for pure-play segment providers, the real value is in helping advertisers unlock the value of their first party data. The value of 3rd party data will continue to decline, especially as more and more marketers use less of it to create “seeds” from which lookalike models are created.
  • Exchanges: Exchanges have been the biggest beneficiary of the move away from ad networks. Data + Exchange = Ad Network. Now that there are so many plug and play technologies giving advertisers access to the world of exchanges, the money had flowed away from the networks and into the pockets of Google AdX, Microsoft, Rubicon. PubMatic, and RMX.
  • Ad Serving: Ad serving will always be a tax on digital advertising but, as providers in the video and rich media space provide more value, their chunk of the advertiser pie has increased. Yes, serving is a $0.03 commodity, but there is still money to be made in dynamic allocation technology, reporting, and tag management. As an industry, we like to solve the problems we create, and make our solutions expensive. As the technology moves away from standardized display, new “ad enablement” technologies will add value, and be able to capture more share.
  • Publisher: Agencies, networks, and technologists have bamboozled big publishers for years, but now smart publishers are starting to strike back. With smart data management, they are now able to realize the value of their own audiences—without the networks and exchanges getting the lion’s share of the budget. This has everything to do with leveraging today’s new data management technology to unlock the value of first party data—and more quickly aggregate all available data types to do rapid audience discovery and segmentation.

 The slide we are going to be seeing in 2012, 2013 and beyond will show publishers with a much larger share, as they take control of their own data. Data management technology is not just the sole province of the “Big Five” publishers anymore. Now, even mid-sized publishers can leverage data management technology to discover their audiences, segment them, and create reach extension through lookalike modeling. Instead of going to a network and getting $0.65 for “in-market auto intenders” they are creating their own—and getting $15.00.

Now, that’s a much bigger slice of the advertising pie.

[This post originally appeared in ClickZ on 2/1/12]