Keeping data under the data owner's control, rather than centralizing it for extraction, expands the range of brands and partners willing to join a data collaboration network, including those blocked by competitive or regulatory constraints from traditional data-sharing arrangements.
Decades of independent agency operation produced duplicated infrastructure and siloed data across markets. Resolving it required consolidating governance and restructuring teams alongside the technology itself.
Keeping data under the owner's control expanded the range of partners willing to share it, beyond what extraction-based data-sharing arrangements typically allow. That architecture is what makes a large-scale data network commercially viable.
A governed catalog lets data scientists see available data sets, review approved use cases, and request access directly, without managing individual credentials. Governance and audit trails stay automatic as part of project setup.
Nearest-neighbor projection of behavioral variables brings audience segments into planning without a shared identifier, closing a gap key-based joins can't. Match rates between first-party and third-party data often cover only a small population share.
The Matched Market Testing approach is valuable before a campaign launches, when test and control regions are chosen using pre-campaign behavioral similarity. Adding measurement afterward produces weaker evidence of impact.
WPP Media's data and analytics organization grew through decades of agency acquisitions, leaving each constituent agency with its own cloud accounts, governance model, and data science tooling. That fragmentation was structural, produced by how the organization was assembled, and closing it required consolidating infrastructure and organizational reporting lines together.
The resulting audience intelligence platform, called Open Intelligence, keeps client and partner data under the owner's control rather than moving it into WPP's systems. That approach has opened partnerships with brands that would not participate in traditional data-sharing arrangements. Data scientists request access through a governed self-service catalog connected to Domino via service accounts, replacing informal, relationship-dependent data hunting.
To bring a client's proprietary audience segments into planning without a shared identifier, WPP built a data fusion pipeline using nearest-neighbor projection of behavioral variables from a donor data set onto a target data set. The pipeline is now packaged as a reusable workflow other market teams can run for their own clients, a foundation WPP is extending toward agentic tools that automate geographic audience visualization.
