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Shifts focus from reactive cleanup to proactive prevention by mapping the four entry vectors where duplicates originate -- manual creation, web forms, integrations, and imports -- with specific controls for each. Makes the business case that prevention is structurally cheaper than remediation and outlines the operational ownership required.

A step-by-step configuration guide for Salesforce Matching Rules and Duplicate Rules, covering standard vs. custom rules, exact vs. fuzzy matching, API enforcement, and Duplicate Jobs for existing data. Includes the common configuration mistakes admins make and a checklist for getting rules into production.

Goes beyond definitions to provide three calculation methods (top-down, bottom-up, value-theory), a worked example with specific numbers, and guidance on how investors scrutinize these metrics. Shows how TAM/SAM/SOM should drive territory planning, hiring, and GTM resource allocation rather than just populating a pitch deck slide.

Introduces the two enrichment models (append vs. discovery), six types of enrichment data, and the step-by-step process for evaluating whether your current approach is leaving revenue on the table. Clarifies the distinctions between enrichment, cleansing, and enhancement, and explains why the sequence matters.

A technical and operational guide to Salesforce's native deduplication system, covering Matching Rules, Duplicate Rules, configuration, and the specific limitations that drive teams toward third-party tools. Quantifies the revenue impact of duplicates -- split pipeline, rep conflicts, wasted enrichment spend -- and lays out a long-term prevention strategy.