Data quality
The accuracy, completeness, and consistency of data flowing through automations. Poor data quality causes silent failures a CRM record missing a phone number means the SMS reminder never sends. PURIST validates data at every entry point.
Expert insight
Garbage in, garbage out. An automation is only as reliable as the data it processes.
In a real workflow
Before sending leads to the CRM, emails are validated and obvious test entries are removed.
Common mistakes
- Fixing data quality downstream instead of at the source.
- No owner for data quality.
Complexity level
Requires some familiarity with automation concepts.
Related terms
See it in action
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Go deeper
Guides that cover Data quality
Your CRM is lying to you: how data quality automation fixes the silent revenue killer.
Duplicate contacts, outdated emails, missing fields, CRM data rot costs businesses thousands in lost deals every quarter. Here is how to automate the cleanup.
Pardot vs Marketo in 2026: Account Engagement vs Marketo Engage for B2B Marketing Automation
Salesforce Marketing Cloud Account Engagement (Pardot) vs Adobe Marketo Engage: published and estimated pricing, total cost of ownership, scoring, nurturing, CRM fit and which one suits your team.
Actuarial Reserving Process Automation: What to Automate and What to Leave Alone
The two layers of actuarial reserving, data assembly versus actuarial judgment, and why automating only the first one is what actually works.