Identity Resolution

Match rates vary by identifier type, but BIGDBM consistently delivers some of the highest rates in the industry. Hashed emails (MD5, SHA256, SHA1) match at 80%+ against BIGDBM's 700M+ email records — the largest and most accurate email database in the U.S. MAIDs match at high rates due to BIGDBM's billions of device linkages across AAID and IDFA. Phone and IP match rates depend on data recency and quality, but BIGDBM's continuous refresh cycle (monthly for IP, weekly for other signals) ensures you're matching against current records. If your input file has lower quality data, BIGDBM can still improve match rates using probabilistic signals to bridge gaps — so even dirty lists return usable outputs. Share a sample and we'll run a free match estimate before you commit.

PQL (Phone Quality Level) is a confidence score assigned to every phone number that tells you whether it's worth calling or texting before you spend a dollar on outreach. The score evaluates carrier status (is the number active with a carrier?), connection type (landline, mobile, VoIP), line health, and DNC (Do Not Call) registry compliance. Numbers are scored on a tiered scale so you can set a threshold — for example, only contact numbers above a certain PQL score — and eliminate wasted outreach, compliance risk, and carrier penalties in one step. For SMS campaigns in particular, PQL scoring is essential: sending to invalid or DNC-registered numbers increases carrier filtering, damages sender reputation, and creates TCPA exposure. BIGDBM appends PQL scores at resolution time so every phone number in your output is pre-qualified.

BIGDBM uses both methods, and the combination is what makes its match rates industry-leading. Deterministic matching is exact: when two records share the same verified identifier — a hashed email, confirmed phone number, or government-issued ID fragment — they are linked with certainty. This is the gold standard but only works when the input data is clean and complete. Probabilistic matching takes over when deterministic signals are absent or ambiguous — using device co-location patterns, behavioral clusters, household proximity, and observed signal overlap to build high-confidence links even across fragmented input data. Every probabilistic link is scored with RFIS (Recency, Frequency, Intensity, Strength), so you know how confident the match is and can set your own threshold for activation. The result is the broadest possible identity coverage without sacrificing precision — you see both the match and the score that justifies it.

Privacy compliance is not a post-processing step at BIGDBM — it is infrastructure. Every identity resolution workflow runs on data that has been sourced with consent management from day one, with automated opt-out processing applied continuously so individuals who have exercised their CCPA rights are never returned in resolution outputs. Deceased record suppression removes individuals who are no longer contactable, protecting both compliance and deliverability. BIGDBM is SOC 2 Type II certified, TrustArc certified, and IAB Transparency compliant, with full audit trails maintained on every data workflow. For clients operating in regulated industries or handling sensitive audience segments, BIGDBM's compliance infrastructure means you can resolve identities at scale without building a separate compliance layer on top of the output.

Yes — and this is one of the strongest use cases for multi-signal resolution. When a new account is created or a transaction is submitted, BIGDBM's resolution APIs can cross-reference the supplied PII (name, address, phone, email, date of birth) against the identity graph in real time to confirm that the individual exists, that their signals are consistent with known records, and that no red flags exist — such as mismatched devices, address inconsistencies, or signals associated with known synthetic identity patterns. For fraud prevention, the RFIS confidence scores on each resolved field make it easy to flag low-confidence resolutions for manual review while auto-approving high-confidence ones. Typical API response time is 100–300ms, which integrates cleanly into onboarding, checkout, and account opening flows without adding noticeable latency.