Customer Record Matching uses AI to link customer records that refer to the same individual across disparate systems, enabling a unified customer view for accurate research and segmentation, by probabilistically matching on identity signals, behavioural patterns, and interaction history, across CRM, e-commerce, support, and loyalty data stores.
Customer data lives across CRM, e-commerce, support, and loyalty platforms under different identifiers; the same individual appears as multiple entities, corrupting customer counts, inflating churn rates, and undermining the reliability of any segmentation or research built on top.
AI probabilistically matches and links customer records across source systems using identity signals, hashed identifiers, and behavioural fingerprints, producing a deduplicated unified customer profile for each individual.
Entity resolution accuracy improves and the duplicate customer rate in research populations drops, materially improving the reliability of segmentation and lifetime value models.
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