Use Data Explorer to capitalize on historical audiences by building traits based on used and unused signals, and backfilling them with historical data to avoid potential loss of relevant audiences.
Creating traits based on existing insights related to your audience is a rather straightforward process, as long as you always know who your audience is. But how often does that happen?
Data Explorer simplifies your trait management process while offering you a higher degree of flexibility when it comes to taxonomy curation. Two Data Explorer components help you achieve this:
Signals Dashboard and Signals Search help you keep track of signals received by Audience Manager that you can use to build new traits or add to existing ones.
Trait Realization Backfill helps you qualify historical audiences for newly created traits, so that you can include them in future targeting efforts.
Use Data Explorer to optimize your audience building in multiple ways:
A global electronics retailer has a high volume of visitor traffic, but conversion rates are lower than expected, although they’ve optimized the content for multiple platforms. Using the Signals Dashboard, they identify a high volume of unused signals, indicating that visitors are searching for a specific electronics brand not currently in stock. The company can take advantage of this insight by refreshing their stock and targeting those visitors with personalized campaigns.
After a travel services provider adds new destinations to their booking website, they want to advertise them to historical audiences, although they don’t have any traits created for them. They can use Signals Search to identify the unused signals related to the new destinations, include them in new traits and backfill them with historical realizations. Then, create new segments with the new traits and immediately target them with dedicated campaigns.
One of the most powerful features of Audience Manager is the ability to onboard offline data and tie it together with your online data. In the video below, learn how to use Data Explorer to validate that you have created all the necessary traits to leverage this onboarded data.