Admin & Extend · Module 17

Import / Export

Thousands of Records, Minutes Not Days

How to load a whole spreadsheet of Leads into the CRM at once, get a clear report on anything that didn't work, and export any list back out just as easily.

⏱ ~8 min to complete80 pts available🏅 Badge: Data Migration Specialist

About & Business Case #

Why bulk import/export matters #

Dana Reyes · Sales Operations

"We just came back from a trade show with 5,000 business cards' worth of leads sitting in a spreadsheet. Nobody has time to type those into the CRM one at a time before they go cold."

A Lead is a person who might become a customer — like someone who handed you a business card or filled out a "Contact Us" form. Typing them in one at a time only works for a handful of rows.

And one bad row in a big spreadsheet shouldn't block the other 4,999 good ones.

What this means for you

Thousands of records load in minutes instead of days. You get full visibility into exactly which rows need a fix by hand — nothing silently gets lost.

Implementation #

Anatomy of the Import Wizard #

📄 Upload CSV

→

🔗 Map Columns

→

✅ Run Import

Step	Detail
Header detection	A CSV is just a spreadsheet saved as plain text, with one column per field. The system reads its header row (the column titles) and shows them to you so you can map them
Field mapping	You tell the system which CSV column matches which field in the CRM — or skip a column entirely — before anything actually imports
Per-row processing	Each row goes through the exact same checks as typing a record in by hand — required fields, validation rules, and workflows all still apply
Result report	Shows total rows, how many succeeded, how many failed, and a per-row list explaining exactly why each failure happened

One bad row ≠ a failed batch

Each row is imported on its own. If one row fails — say, it's missing a required field — it doesn't block or undo the other rows. You just get a clear list of exactly what to fix.

1 Import a trade-show lead list #

Prepare a CSVMake a small test spreadsheet with columns: Company, First Name, Last Name, Email. On purpose, leave one row missing a required field, so you can see what an error looks like.

Open the Import WizardGo to Import, pick object: Lead, then upload your CSV file.

Map the columnsMatch "Company" to company, "First Name" to first_name, "Email" to email, and so on.

Run the importReview the result: how many succeeded, how many failed, and the specific error for the row you broke on purpose.

Export it back outGo to Export, pick Lead, download the CSV, and confirm the records you just imported are in it.

How to Use #

Day-to-day: after an event or a data handoff #

Load the batchUpload the CSV the same day you get it, before leads go cold.

Fix only what failedWork through the error report row by row — everything else is already in.

Day-to-day: reporting or handing data to another tool #

Export what you needPick the object and download a CSV — it respects the same sharing rules as everywhere else, so you only see what you're allowed to. A cell that starts with =, +, - or @ (and isn't a number) gets a leading ', so Excel shows it as text instead of running it as a formula.

What to try next

Look at the Data Quality Tools trail — Duplicate Rules apply to imported records too, not just manual entry.

Quiz #

Test what you learned #

1. Row 42 of a 1,000-row CSV import is missing a required field. What happens to the other 999 rows?

The whole import is cancelled and undone

They still import normally — only row 42 shows up as failed

2. Does a record created through CSV import trigger the same Workflow Rules as one typed in by hand?

Yes — each row goes through the exact same save process as typing it in manually

No — imported records skip workflows and validation rules