Data is everywhere in digital advertising, but rarely unified. Each browser, device, and platform a consumer uses leaves behind data fragments that, by themselves, are loosely informative. Identity and data resolution connect those fragments, transforming scattered signals into coherent customer profiles that fuel effective targeting.
This glossary page explains what identity and data resolution mean, why they matter, how they work, and what each advertiser should consider when choosing a strategy.
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Identity and data resolution are closely related processes that help advertisers make sense of user data across the many touchpoints consumers create when engaging with digital media.
Generally speaking, identity resolution is the practice of linking disparate identifiers, such as cookies, mobile IDs, email addresses, login credentials, or phone numbers, to form a unified view of a person, a household, or a digital profile. This connection prevents marketers from treating the same person as multiple anonymous visitors, avoiding inefficient targeting and misleading measurement.
Data resolution starts with data normalization, by cleaning and standardizing raw inputs (for example, turning [email protected] into a hashed ID). Then, it proceeds to matching, where systems compare signals across datasets to determine which signals likely belong to the same user. Data resolution then infers and enriches profiles so they can be used for predictive segmentation and campaign activation.
In practice, identity resolution systems stitch together signals from a single user’s phone and laptop, while data resolution enriches that unified identity with demographic or behavioral attributes. These systems involve technologies such as identity graphs, hashed identifiers, and probabilistic matching engines.
At Perion, we’ve adopted industry solutions like Unified ID 2.0, which converts first-party data (e.g., emails or mobile numbers)into privacy-safe hashed identifiers that help link authenticated audiences across devices and channels, enabling more precise targeting and measurement without exposing personally identifiable information (PII).
Advertising depends on understanding audiences, who they are, what they care about, where they are in the purchase journey, and how they respond to creative across screens. Without resolution, marketers rely on fragments: a cookie here, a mobile ID there, a login over there. These fragments don’t openly reveal whether they belong to the same consumer.
Identity and data resolution solve this problem in several ways:
Identity and data resolution involve interconnected technical layers that ingest, match, manage, and activate identity information across devices and channels. Let’s break down the major components.
The process of linking identifiers that likely belong to the same individual. The goal is to establish connections between these identifiers to form a more complete picture.
There are several ways matching happens:
Once identifiers are matched, they must be managed in scalable, compliant systems. This typically involves building an identity graph – a structured representation of all linked IDs and attributes.
Some advantages of identity management include:
Identity resolution solutions bring matching and management together into a usable stack for marketers. These solutions ingest first-party data from CRM systems, websites, apps, and subscription databases. They also normalize and hash identifiers to protect privacy and build and maintain identity graphs that link identifiers across devices. Identity applications provide APIs and integrations so that audiences can be activated in DSPs (demand-side platforms), measurement tools, and analytics platforms.
Effectively resolving identities unlocks multiple benefits for advertisers. Below are the major outcomes that many advertisers seek.
Fragmented data leads to wasted impressions: the same user might be targeted multiple times under different identifiers, or audiences may be under-reached because they appear “unknown”. Unifying identities reduces duplication, improves frequency control, and ensures messages reach actual unique individuals. Higher match rates and accurate targeting result in better ad ROI.
Persistent IDs aren’t tied to ephemeral cookies. They survive changes in browsers, logouts, and cross-device shifts because they are based on stable first-party signals. Persistent IDs help advertisers maintain customer profiles over time, track long-term engagement patterns, and attribute conversions more accurately.
Once identities are resolved, they can be enriched with behavioral, demographic, or contextual data. Advertisers can then infer consumer intent and preferences accurately. Rather than purely demographic targeting, advertisers can build audiences that reflect likely purchase intent or content affinities.
Example enrichments might include demographic segments, content preferences, purchase histories, or engagement patterns across touchpoints.
Advertisers increasingly want to understand journeys that span channels like CTV, mobile web, and display. By resolving identities across screens, brands can link exposure to outcomes across devices, personalize messaging based on previous interactions, and improve cross-channel attribution.
For instance, cross-channel campaigns that leverage identity resolution can show consistent creative sequences to the same individual as they move between streaming, browsing, and social platforms.
While identity resolution offers benefits, advertisers must evaluate several factors when implementing or selecting a solution.
Good identity resolution depends on high-quality data. Inaccurate, outdated, or incomplete first-party data leads to poor matches and unreliable profiles. Marketers must ensure that data collection is consistent and consented, identifiers are hashed and formatted, and noise and duplicates are minimized.
Resolution works best with scale. More signals increase the system’s ability to find reliable matches. Advertisers or platforms with limited data footprints may see lower match rates, but weak graph integrations can help improve match rates and activation potential.
Handling identity data triggers legal and ethical obligations. Hashing and tokenization protect raw PII, but platforms must also ensure compliance with regulations like GDPR, CCPA, and evolving global privacy standards. Transparency with consumers, opt-in management, and strict access controls are essential.
Despite its many benefits, identity resolution isn’t exempt from challenges. First, consumers and regulators increasingly scrutinize data practices, which leads to privacy complexity. Any mishandling can damage trust or lead to penalties.
Not all platforms support the same identifiers; for example, connected TV may lack conventional cookie-based signals. Additionally, as new identifiers and frameworks emerge, advertisers must continually adapt strategies and integrate new technologies.
There could also be technical integration barriers. Identity graphs and resolution engines require careful integration with existing martech stacks. If not addressed, poorly executed implementations can lead to inconsistencies or data silos.
