Extracting valuable insights from consumer datasets isn’t easy. Even deterministic first or third-party data can be limited due to a lack of common consumer identifiers from dataset to dataset. What you need is a ‘Rosetta Stone’ that helps you translate points across various disparate sources of data to a common ID.
Extracting valuable insights from consumer datasets isn’t easy. Even deterministic first or third-party data can be limited due to a lack of common consumer identifiers from dataset to dataset. What you need is a ‘Rosetta Stone’ that helps you translate points across various disparate sources of data to a common ID.
Crosswalking takes advantage of the multiple individual and household level match keys present in an identity graph and maps the equivalent fields across your various datasets. Whether you need to be able to compare offline-to-offline, offline-to-online, online-to-offline, or online-to-online (cross-device), with Crosswalking you can break down existing silos to get the most out of your data.
Crosswalking is like the Rosetta Stone of data, allowing marketers and data owners to harness the power of a consumer identity graph without possessing one. It takes advantage of multiple individual and household level match keys present in an identity graph and maps the equivalent fields across various datasets.
