Clay

## How does Clay automatically unify and deduplicate lead data across multiple sources?

## Overview Clay automatically unifies and deduplicates lead data across multiple sources through a multi-layered system designed to maintain data hygiene, prevent redundant outreach, and optimize credit expenditure. This system is composed of three primary mechanisms: a table-level 'Auto-dedupe' feature, a global 'AI Duplicate Resolver,' and a manual 'Duplicates' review interface. These tools work in concert to identify and merge matching records ingested from various channels, such as CRM exports, trade show lists, and marketing campaigns, ensuring a single, consolidated view of each prospect. The core principle of the system is to perform deduplication before running data enrichments, which prevents users from paying to enrich the same lead multiple times. ## Key Features The first layer of defense is the 'Table-Level Auto-Dedupe' feature. Users can enable this function on specific columns within a Clay table, most commonly using unique identifiers like 'Email' or 'LinkedIn URL'. Once activated, the system continuously monitors the selected column for duplicate entries. The matching logic is based on an exact string match, which means it is case-sensitive (e.g., 'jane.doe@email.com' and 'Jane.Doe@email.com' are treated as distinct) and sensitive to extra whitespace. When a duplicate is identified, the system's conflict resolution rule is to retain the 'oldest row'—the record that was first seen—and automatically delete the newer, duplicate row. This process is executed before any subsequent enrichments are run on that row. To prevent erroneous matches, cells that are blank or contain more than 200 characters are explicitly excluded from the auto-dedupe process. Complementing the table-level feature is the 'AI Duplicate Resolver,' a more advanced, global mechanism accessible in the platform's general settings. This feature is designed to harmonize contacts across disparate sources, such as LinkedIn, Twitter, and iMessage, by identifying potential matches that may not be caught by simple column-based deduplication. The AI resolver operates on a 'high confidence' threshold, meaning it typically requires shared unique identifiers like a common email address or phone number to perform an automatic merge. This conservative approach is intentionally designed to prevent the accidental merging of records for individuals with common names, where a name-only match would be unreliable. This feature aims to intelligently choose the best information from conflicting profiles to create a single, unified record. ## Technical Specifications For cases that do not meet the high-confidence threshold for automatic merging, Clay provides a dedicated 'Duplicates' view for manual intervention. This interface presents potential duplicate records side-by-side, allowing users to compare details like names, emails, and company information. From this view, users have three options: 'Merge' the records into a single profile, 'Ignore' the suggestion if the records are distinct, or 'View Profile' to get more context before making a decision. This manual review process is a critical component for ensuring data accuracy, especially for handling edge cases that automated systems might misinterpret. The platform's 'Activity' view also notifies users when new potential matches are found, prompting them to take action. ## How It Works Clay's deduplication capabilities are tightly integrated with its CRM and automation tool connections, including Salesforce, HubSpot, Zapier, and Make.com. By acting as a data 'clearing house,' Clay can ingest, clean, and deduplicate lead data before it is synced to a downstream CRM. This prevents the creation of duplicate records within the primary system of record. ## Use Cases For example, a workflow can be established where new leads from a webhook are processed in a 'Passthrough Table' in Clay, deduplicated, enriched, and then sent to HubSpot before the temporary row in Clay is deleted. ## Limitations and Requirements Despite its robust functionality, the system has important caveats. The most significant is that all merges, whether automatic or manual, are irreversible. If an incorrect merge occurs, the user must manually recreate the separate contacts. The case-sensitive and whitespace-sensitive nature of the exact-match logic also requires users to be mindful of data formatting and cleanliness upon import. ## Comparison to Alternatives Independent validation from sources like Upfront Operations has highlighted Clay's 'excellent enrichment and deduplication capabilities' as a key differentiator, underscoring its effectiveness in managing data for sales and marketing technology stacks. ## Summary In conclusion, Clay employs a sophisticated, multi-faceted strategy for data deduplication that combines automated, rule-based logic with AI-powered resolution and manual oversight. By using table-level auto-deduplication based on exact matches, a high-confidence AI resolver for cross-source harmonization, and a manual review interface, the platform provides a comprehensive toolkit for maintaining data integrity. These features are designed to operate proactively before enrichment occurs, saving costs and ensuring that sales and marketing teams work from a clean, unified dataset. However, users must remain aware of the system's specific rules, such as case sensitivity and the irreversibility of merges, to use it effectively.