Identity has become the connective tissue of modern marketing, yet many brands and publishers still struggle to cut through vendor noise, technical jargon, and shifting privacy rules to choose the right identity resolution partners. This guide is designed to help buyers who own first-party data turn identity from a confusing buzzword into a practical, durable advantage across targeting, measurement, and customer experience. To do so, this paper provides a clear framework for understanding core identity concepts (including expansion, collapse, identity graphs, deterministic vs. probabilistic matching, interoperability), along with a structured needs assessment to determine whether, when, and how to engage external providers. The paper then walks through how to navigate the marketplace: segmenting provider types, asking the right RFI/RFP questions, “kicking the tires” with match tests and demos, and applying rigorous evaluation criteria across data quality, integration, privacy/compliance, service, and commercial models. It concludes with a peek into synthetic IDs and non-human identities that points the way to the near future.
Throughout, the guide translates hard-won lessons and input from more than 40 industry leaders into checklists, example scoring matrices, and practical prompts can be applied immediately in vendor reviews, internal strategy discussions, or board-level conversations.
Evaluating identity solutions can be confusing and exhausting, since in between expansion and collapse lies the real work: deciding which signals to trust, which partners to empower, and how to align identity with accountability. The purpose of this guide is not to crown winners and losers, but to equip buyers with a clear, structured way of thinking – so they can ask sharper questions, make more confident decisions, and build identity practices that are resilient, privacy-forward, and genuinely useful to the business for years to come.
Whether an organization is standing up identity for the first time or recalibrating an existing stack, this paper will help the buyers separate signal from noise and select partners that deliver accurate, privacy-conscious, and future-ready identity intelligence at scale.
