Resources
Guides, tutorials, API recipes, and MCP walkthroughs for keeping lead and CRM data clean. Every example calls a real Zapinner endpoint — copy, paste, and run it.
Data Quality
Normalize, validate, profile, and reason about the quality of your data.
Data Quality1 min read
Data Normalization Explained
What normalization actually means for real fields — emails, phones, currency, dates — why it must be deterministic, and where it fits in a data pipeline.
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Data Validation vs Data Cleaning
They sound interchangeable and do opposite jobs. One decides whether a record is allowed through; the other changes its values. Here's when to use each.
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CRM Data Quality Checklist
A practical checklist for auditing and maintaining CRM data quality — completeness, consistency, duplicates, validity, and the boundary controls that keep it clean.
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