Score identity connections so teams can choose precision or scale per workflow, with clear, repeatable confidence thresholds.
RFIS stands for Recency, Frequency, Intensity and Strength. BIGDBM uses these dimensions to describe confidence in an identity link. A score should not be treated as a calibrated probability unless the service documentation establishes that interpretation.
Evaluate candidate thresholds against a labeled validation sample. Measure accepted coverage and false matches for your use case before applying the threshold to production data.
Coverage definitions and performance context · API reference · RFIS reference · Discuss scope and pricing
Assign a measurable confidence score to each identity link so decisions are explainable and consistent.
Set match thresholds by workflow, activation, analytics, or governance, without changing your data model.
Prioritize high-authority matches first, then expand responsibly when additional coverage is needed.
Refresh identity links over time as signals change, strengthening strong matches and downgrading weak ones.
Our proven process for connecting and scoring customer identities
Bring in email, phone, address, MAIDs, IPs, and first-party IDs from your CRM, site/app, partners, and offline sources, ready for resolution.
Link fragmented records into people and households using deterministic rules and modeled logic, creating a unified identity foundation.
Score each connection using RFIS-style confidence signals so you can see match strength and apply thresholds per workflow.
Continuously re-check and refresh connections as new signals arrive, while handling suppression and quality updates so scores stay accurate over time.
Deliver measurable business outcomes with trusted identity data
Match Coverage Lift
Increase usable identity by improving linkage quality and applying confidence thresholds that support safe expansion.
Duplicate Reduction
Reduce duplicate profiles and conflicting identifiers across systems to improve reporting, segmentation, and activation consistency.
Conversion Lift
Improve outcomes by activating higher-confidence identity connections, reducing mis-targeting and inconsistent experiences.
Media Waste Reduction
Lower wasted spend through deduplication, cleaner suppression, and confidence-based thresholds applied to activation.