Buying on the promise. Marketers currently spend millions on identity data and attribution solutions based on performance statistics provided by vendors. While pre-buy metrics like match rates provided to marketers may be useful to compare expected campaign success, marketers currently have no standardized way to validate vendor claims.
Building confidence in the reality. Without a way for marketers and vendors to reconcile estimates with actuals, there will always exist unnecessary friction and mistrust between the two parties. Common tests to confirm scale, accuracy and match rates are needed to create benchmarks and facilitate trust and accountability.
That's why DMA is creating the Identity Data Assessment Toolkit: An expanded Identity RFI template that builds upon DMA's XDID RFI template by adding additional identity data definitions, offline-to-online use-cases and questions, pre-sale data validation assessment techniques and easy-to-use checklists to improve buyer and seller alignment.
Standardized testing methodologies for the most common identity data metrics, so that both buyer and seller can more easily validate estimates, and all parties can reduce the gap between expectations and reality.