New targeting capabilities have evolved most rapidly in the arena of performance display. The targeting techniques that have developed the fastest include:
• Site retargeting: Showing a message to someone who has already performed an action on a marketer’s website
• Intent targeting: Capturing signals that paint a portrait of a consumer’s current state of mind and presenting them with adequate messages before they even visit the marketer’s website
• Contextual targeting: Deriving the consumer’s current sphere of interest from the web page they are visiting
• Targeting based on social signals: Some audience platforms build a social graph describing the way consumers interact, and derive intent from what is happening in a consumer’s social environment
Most of these capabilities fall under the purview of Data Management Platforms, or DMPs. To understand DMPs more deeply, click here.
2) Crossing to Other Digital Channels
Popular and effective audience targeting techniques across digital channels involve:
• Search retargeting: Gathering search data, these technologies build audience profiles that can then be exposed to display or video messages across the web
• Social audiences: Social networks such as Facebook and Twitter have a large amount of information about consumers interests and profiles as well as extensive information about their current behaviors, such as “liking” a product or place, or hashtagging a TV show. They also know a lot about a consumer’s surroundings, marital status, friends, and so forth. Using that data within the social networks’ walled garden is valuable, but porting the data across other channels is even more valuable.
An example of these can be found for Twitter here.
• Porting audience profiles built in the display or search world to email marketing and automated marketing: By understanding better the real-time intent and state of mind of their consumer base, marketers can use marketing automation to send their consumers more appropriate messages via retargeting.
3) Crossing Devices and Platforms
• Audiences across devices: Most audience profiles depend on being able to identify a user, generally based on the user’s browser. This ability breaks down if a person changes devices. Some DMPs have technology specifically designed to identify devices and derive information about a household or individual based on a collection of devices, creating a “device graph” that helps them understand which consumers are the most likely to match a particular audience profile. These matches, like most other audience-profiling techniques, rely on probabilistic methods. Data quality among vendors can vary.
• Location-based audiences: Local is the new audience for mobile. Many DMPs use geo- and localization-targeting to create proxies for audiences that share the same intent and can be reached on mobile devices.
4) The grail: Unifying multiple sources into one consumer profile
Some DMPs build and maintain extensive data sets of user profiles that use sophisticated probabilistic methodologies to match them to specific consumer identities.
These DMPs help marketers tie signals from marketing and CRM programs to a real (or presumed real) consumer as he or she surfs around the web, and tie digital behavioral and marketing signals to offline outcomes such as in-store purchases or other actions.
In our next piece, we’ll look at how we can build a measurement framework to link data coming from platforms managing audiences to performance data from execution platforms such as DSPs and ad servers to make better data-driven optimization decisions.