Duplicate records are hiding your best leads. Identity resolution reveals true buyer intent and fixes your pipeline.
Lead scoring models become significantly more accurate because they operate on complete buyer journeys instead of fragmented signals.
Sales teams engage high-intent buyers faster, improving response times and conversion rates.
Marketing attribution improves because touchpoints are correctly linked to a single user.
Instead of exact matches, systems use similarity scoring across name, email, phone, location, and behavior patterns to identify duplicates.
Different portals export data in different formats. A normalization layer converts all inputs into a consistent schema before processing.
Deduplication should happen at the point of ingestion, not as a batch process. This ensures new leads are immediately matched against existing profiles.
Identity resolution is the process of linking multiple records that belong to the same individual into a single unified profile. In real estate, this is critical because buyers interact across multiple channels, creating fragmented records.
Duplicates occur because leads come from multiple sources such as portals, ads, and direct traffic. Each source captures slightly different data, creating multiple records for the same person.
Lead scoring models rely on signals like frequency of interaction and engagement. When those signals are split across multiple records, the system underestimates buyer intent.
Probabilistic matching uses algorithms to determine the likelihood that two records belong to the same person, even if they are not exact matches. This is essential because real-world data is inconsistent.
Exact matching fails when there are variations in spelling, formatting, or missing data. For example, “John Smith” vs “Jon Smith” or different phone formats would not match exactly.
A golden record is a unified profile created by merging duplicate records. It contains all interactions, data points, and history associated with a single individual.
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