Identity resolution is how Digital Bulldogs unifies a person’s fragmented digital footprint — mobile, desktop, connected TV, and offline — into a single, persistent identity. Instead of relying on a cookie that disappears the moment a browser closes, our identity resolution process uses deterministic matching to connect every touchpoint back to one real person.
Why Cross-Device Identity Matters Now
Consumers move between phone, laptop, connected TV, and in-store constantly, and cookie-based tracking was never built to follow them across that many surfaces. As third-party cookies continue to disappear from major browsers, marketers who still rely on cookie-based matching lose visibility into a growing share of the customer journey. Identity resolution closes that gap by connecting touchpoints deterministically rather than guessing based on browser signals that no longer exist.
What Identity Resolution Enables
- Cross-Device Targeting — campaigns follow the actual person, not a specific browser or device.
- Cookieless Matching — built for a post-third-party-cookie internet rather than patched together after the fact.
- Deterministic Links — identity connections based on verified data, not probabilistic modeling that degrades at scale.
- Unified Measurement — a single customer view across CTV, mobile, desktop, and offline data sources.
- Sequencing Control — the ability to control message frequency and sequence across channels instead of duplicating touches.
How Identity Resolution Works
Why This Approach to Identity Resolution Works
Identity Resolution and the Rest of Our Solutions
Identity resolution is the connective layer underneath our other services. It strengthens custom audiences by ensuring targeting follows a real person across channels, and it draws on the same underlying data feeds that power our broader data business. It also indirectly supports email delivery: better cross-channel sequencing reduces the redundant, poorly-timed messaging that drives complaints and unsubscribes.
Since 2011, By the Numbers
Who Needs Identity Resolution
Direct-response marketers and media buyers running campaigns across multiple channels are the primary users of our identity resolution service, especially those who depended heavily on cookie-based retargeting and have seen match rates erode as browsers restrict tracking. Agencies managing cross-channel campaigns for several clients use identity resolution to maintain consistent measurement and frequency capping across every account, regardless of which platform a given touchpoint originated on.
Real identity links, not probabilistic guesses.
Mobile, desktop, CTV, and offline unified into one identity.
Built on the same data discipline as our email work.
Related Solutions
- Custom Audiences — precision targeting strengthened by deterministic identity matching.
- Data — the underlying data feeds and provider network behind every identity graph.
- Email Delivery — better cross-channel sequencing that indirectly protects sender reputation.
Our approach to identity resolution is built with an awareness of the shifting privacy landscape; we follow guidance such as the FTC’s privacy and data security guidance as a baseline for responsible identity matching.
Frequently Asked Questions
How is identity resolution different from cookie-based retargeting?
Cookie-based retargeting relies on browser-stored identifiers that disappear and vary by device. Identity resolution uses deterministic data links to follow an actual person across devices, independent of any single browser’s cookie state.
Does this work now that third-party cookies are restricted?
Yes. Our identity resolution process is built around deterministic matching rather than third-party cookies, so it isn’t affected by browser-level cookie restrictions the way older retargeting methods are.
Can identity resolution integrate with our existing CRM or ad platforms?
Yes. Resolved identities are typically delivered in formats that integrate with the CRM, ad platform, or measurement tools you already use.
Is there a long-term contract?
No. Every engagement is month-to-month and can be canceled anytime.
Does this help with email deliverability too?
Indirectly. Better cross-channel sequencing reduces redundant, poorly-timed messaging, which tends to lower spam complaints and support the sender reputation work in our email delivery service.
Book Your Delivery Audit
Ready to unify your customer view across every channel? Book your delivery audit and we’ll scope an identity resolution plan for your campaigns — no long-term contracts, month-to-month, cancel anytime.
Built for In-House Teams, Media Buyers, and Agencies
In-house marketing teams typically come to identity resolution after noticing match rates on retargeting campaigns quietly eroding as browsers tighten cookie policies. We start by mapping which channels and touchpoints matter most to a given business, then build the identity graph around those specific data sources rather than a one-size-fits-all approach.
Media buyers running paid acquisition across multiple platforms need a consistent view of frequency and sequencing that no single ad platform can provide on its own. Identity resolution gives them that cross-platform view, so a prospect isn’t hit with the same message five times across five different channels in a single day.
Agencies managing cross-channel campaigns for several clients standardize on identity resolution to keep measurement consistent across every account, which matters most when a client asks why performance looks different on one platform’s dashboard versus another’s.
Deterministic vs. Probabilistic Matching
Probabilistic identity matching estimates the likelihood that two data points belong to the same person based on statistical patterns — useful at scale, but inherently uncertain, and that uncertainty compounds as more devices and channels get added to the graph. Deterministic matching instead relies on verified, shared identifiers, so the connection between two touchpoints is confirmed rather than estimated.
We default to deterministic matching wherever the underlying data supports it, reserving probabilistic methods for edge cases where no deterministic link exists yet. That priority order is what keeps accuracy high as an identity graph scales across millions of touchpoints.
How long does it take to build an identity graph?
Initial graph construction typically takes a few weeks depending on the number of data sources being connected, with continuous refinement afterward as new touchpoints are ingested.
What data sources feed into the identity graph?
Sources vary by client but commonly include CRM records, email engagement data, mobile device IDs, CTV viewership data, and offline purchase records where available.
Digital Bulldogs in the Community
Since 2011 our team has stayed close to the direct-response and affiliate marketing community rather than operating as an anonymous vendor. We’ve exhibited at Contact.io, MailCon, and both Affiliate Summit East and West, sponsored events like Mailer Meetup and Affiliate Ball, and attended LeadsCon, Affiliate World, and Inbox Expo — the same rooms where the shift away from third-party cookies gets discussed as it happens, rather than read about after the fact.
Privacy and Compliance in a Cookieless World
Cross-device matching only holds up long-term when it respects the regulatory environment it operates in. We’re direct with clients about how identity graphs are built and what data feeds into them, rather than obscuring the mechanics behind a black-box match rate. Current guidance on consumer data rights and consent shapes how every graph is constructed and maintained.
That transparency matters because privacy regulation continues to evolve, and a matching approach built on genuine compliance holds up far better over time than one built purely for short-term performance gains.
Do you support opt-out and consent management?
Yes. Identity graphs respect consumer opt-outs and consent signals, and matching logic is built to honor those preferences rather than working around them.
Can this work alongside our existing measurement or attribution tools?
In most cases, yes. Resolved identities are typically delivered in a format that plugs into existing measurement and attribution stacks rather than requiring a full platform replacement.
Why Accuracy Compounds Over Time
An identity graph gets more valuable the longer it’s maintained, since every new touchpoint adds confirming evidence to existing connections rather than starting from scratch. Programs that treat identity resolution as a one-time project rather than ongoing infrastructure tend to see accuracy degrade as devices are replaced, emails change, and household composition shifts. Continuous refresh is what keeps a graph useful years into a program rather than just for the first campaign it supports.
Getting Started
Most engagements begin with a short discovery conversation about which channels and data sources matter most to your acquisition or retention strategy, followed by a scoping exercise to determine which existing systems the resolved identity needs to integrate with. From there, initial graph construction begins using whatever verified data sources are available, with probabilistic methods reserved only for gaps that deterministic sources can’t yet cover.
What results should we expect to see first?
Most clients see the clearest early wins in frequency capping and cross-channel measurement consistency, since those improvements don’t require waiting on a fully mature graph the way some targeting gains do.
Longer term, the compounding value shows up in acquisition efficiency: campaigns stop wasting spend on duplicate touches across channels, measurement stops crediting the wrong platform for a conversion that happened elsewhere, and creative testing gets cleaner because frequency is actually controlled at the person level rather than the device level. None of that happens overnight, but it’s the reason clients tend to expand identity resolution across more channels once the first integration proves out.
The same discipline that goes into building a clean identity graph up front is what makes it durable later, which is why we treat the initial scoping conversation as seriously as the technical build itself.
For teams weighing whether to prioritize this now versus waiting, the honest answer is that the cost of waiting compounds too: every quarter spent relying solely on eroding cookie-based methods is a quarter of acquisition data that can’t be recovered or reprocessed later. Building the graph earlier simply means more historical signal to work with once it matures.
That’s the practical case for starting now rather than later.
Our matching methodology is informed by the NIST Digital Identity Guidelines.
Read a related case study on identity resolution, or check the FAQ for common questions.