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When Big Data Doesn't Provide Big Insights

  |  November 9, 2011   |  Comments

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

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

For the modern marketer, that means having access to 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 will make or break companies from now on. Luckily, 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 specific attributes you should consider when selecting a data management platform (DMP).

Collection and Storage: It's All About Scale, Cost, and Ownership

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 lot of data now, you will be surprised at how the amount 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 value out of this data. Make sure to understand how your data management platform scales and what kinds of hardware it uses 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 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 ensuring 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 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 customer-relationship management 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 data sets.

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 policies around historical storage and enables you to use the data across multiple channels.

Consolidation and Insights: Welcome to the (Second and Third) Party

bigdata2Third-party data (in this context, available audience segments for online targeting and measurement) is the stuff that the famous Terence Kawaja's logo 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 data management platform should:

  • Marry highly validated first-party data, and match it against third-party data for the purposes of identifying, anonymizing, and matching third-party users.
  • Consolidate and create as whole of a view of your audience as possible.
  • Enrich 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).
  • Be able to increase reach by ensuring that you can collect information about as many relevant users as possible and through lookalike modeling.

For example, if I'm selling cars and I find out that my onsite users who register for a test drive are most closely matched with Prizm's "Country Squires" segment, it is not enough to buy the Nielsen segment. A good data management platform 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

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

So, what to look for in a data management platform? For the large agency or advertiser, the platform must - at the very least - be able to create audience segments. 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 produce that segment and prepare it for ingestion into a demand-side or advertising platform. That means having an architecture that enables the platform to integrate easily with other systems. Moreover, your DSP should enable you to experiment 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 data management platforms can help build those attribution scenarios, and help marketers visualize results. Using a test environment to optimize results means less waste and better performance. Optimizing in the cloud first will 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 the 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 data management platform 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. Data management platforms must not only provide the ability to profile your segments, but also assist you with experimentation and attribution - and provide you with the 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.

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ABOUT THE AUTHOR

Chris O'Hara

Chris O'Hara is an ad technology executive, and the author of "Best Practices in Digital Display Media," a contributor to ClickZ, and the author of the new whitepaper "Best Practices in Data Management." He can be reached through his blog at www.chrisohara.com

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