IAB Releases New Lexicon On Data Segments, Techniques

The Interactive Advertising Bureau (IAB) on Friday released a new Data Segments & Techniques Lexicon that attempts to demystify data usage in the marketplace and create a common language for buyers and sellers. The Lexicon, created by the IAB Data Council, represents a comprehensive update to a document that had not been tweaked since 2011. 

The Lexicon, which goes well beyond a simple glossary to offer a specific framework for how different data segments and techniques work together, is being released in advance of the IAB’s Annual Leadership Summit, which kicks off on Jan. 24.

The Data Segments & Techniques Lexicon was introduced to the industry via a blog post by IAB EVP & COO Patrick Dolan.  “Whether thinking high-level about programmatic ad purchasing, or diving into the nitty-gritty of geo-data or cross-device segmentation, we need a common framework to keep pace with an industry in constant transformation,” Dolan wrote.

The IAB sets out first to define the world of data-generation systems: devices (from traditional desktops to tablets, wearables, and cars); delivery systems (ad servers, CMS, social networks); collection and storage systems (CRM, digital beacons, POS systems); and analysis systems (audience segmentation, inventory analysis, creative engagement analysis, etc). Then, it defined and described data segments and techniques, breaking this down further into sources, collection, processes, and attributes.

The IAB also offers examples that tie all the pieces together into modeled audience segments, such as “Descriptive Segment (Offline to Online) – Demographics (Gender=Male, Age range= 18-25)” and “Predictive Segment (1st Party & Inferred) – Business Traveler.”

Driving the changes to the Lexicon is the “revolution,” as Dolan calls the way that data is generated, organized and applied for marketing.

“Data has largely been driven by the proliferation of mobile platforms informed by geo-location data, Internet-connected devices like set-top boxes, TVs, and wearables, as well as new media attribution technologies that provide marketers with sophisticated real-time signals about the performance of their marketing mixes across channels and devices,” Dolan said in an email to Real-Time Daily.

The changes, he said, can be overwhelming for marketers and media planners, so the IAB saw the need to update the Lexicon to:

#1. Ensure a common language is used to discuss the devices, delivery systems, collection/storage, and analysis systems that are now commonplace in our media environment.

#2 Provide practical examples of how to organize these recent developments within the original conceptual framework outlined by the IAB in 2011.

Dolan also said that he hoped that the changes will be relevant to the Internet of Things as it evolves, since that involves even more diverse data collection types and techniques.

With respect to issues over consumer privacy and trust over data usage, Dolan has this to say: “Data privacy and security have understandably gotten much more attention from legislatures and governments in recent years. High-profile financial leaks, revelations about data sharing programs between industry and governments, the 'creepiness' factor that’s often cited when ads follow consumers around the Internet …

"This document is intended to create a common language to discuss media applications of data, as well as serve as a valuable resource for those who need a common language and conceptual framework to make sense of and discuss broader implications of data collection and data privacy.”

Dolan told Real-Time Daily he hoped people working within emerging data-centric functions inside organizations -- beyond ad-industry professionals -- would find the document helpful. “It would be difficult to find any company today, digital or not, that doesn’t need to develop and formalize strategies around data governance, business informatics, and how to best use and apply data to build competitive advantage.

"Many of these concepts are new to businesses, and this overview will help provide a common language and framework to understand how data can be collected, organized and applied to business functions.”  



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