ImportsStable3 steps
Clean Customer Import
Take a raw customer import, drop empty padding, coalesce a display name, and normalize contact fields into a clean, load-ready shape.
How it works
PipelineTrim, fill a name from fallbacks, then normalize email/phone/company.
- Transform
- Trim stray whitespace from every field.
- Transform
- Fill "name" from the first available of name, full_name, and contact.
- Normalize
- Standardize "email" into a consistent email format.
- Standardize "phone" into a consistent phone format.
- Standardize "company" into a consistent company format.
Frequently asked
FAQ- Is this recipe ready to run?
- Yes. This recipe is stable — every step maps to a shipped capability, so it runs and returns structured records today.
- Can I customize the steps?
- Yes. A recipe is a starting configuration. Install it into a project and you can add, remove, or reorder steps to match your own data.
- What does it cost to run?
- Recipes run on the same usage-based pricing as every capability. Start free with 1,000 usage units a month across everything — no credit card required.
- How do I run it?
- Install the recipe into a project from your dashboard to get a saved pipeline, then call it over the REST API, an SDK, or MCP — one request in, clean records out.
clean-customer-import · 3 steps · Stable
Run this recipe on your own data
Start free with 1,000 usage units a month across every capability — no credit card. Install the recipe, adjust the steps, and call it in one request.
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Turn messy spreadsheet and customer imports into clean, load-ready data.
