Salesforce lead import: required fields and common errors

Salesforce is stricter than most CRMs about what it accepts. That is good news once your file is right, and painful until then: the Data Import Wizard tends to reject rows in bulk and hand you an error file rather than explain itself.

Here is what actually blocks a lead import.

The two fields you cannot omit

Every lead needs, at minimum:

• Last Name
• Company

That second one surprises people importing a consumer list. Salesforce leads are modelled as B2B records, so Company is mandatory even when there is no company. The usual workaround is to fill it with the person's own full name, or a placeholder your team agrees on.

Miss either and you get Required fields are missing: [Company] on every affected row.

Beyond those two, your org may have made other fields required, or added validation rules. Those fire on import exactly as they do in the UI, and they are the most common source of "it worked in my sandbox" surprises.

Picklist values must match, character for character

Lead Source, Industry, Lead Status and Rating are picklists. Salesforce compares your value against the defined options exactly — Web and web are not the same, and Trade Show is not Tradeshow.

What happens next depends on the field:

• On a normal picklist, an unrecognised value is silently dropped and the field lands empty.
• On a restricted picklist, the row fails outright.

The fix. Open Setup → Object Manager → Lead → Fields & Relationships, click the picklist, and copy the values verbatim into your spreadsheet. Do not retype them.

Dates follow the importing user's locale

Salesforce parses dates according to the locale of the user running the import, not the file. If your Salesforce user is set to English (United States), 03/04/2026 is read as 4 March, not 3 April.

The fix. Use YYYY-MM-DD in the file. It is unambiguous under every locale setting.

Fields that are too long

Standard lead fields are capped, and Salesforce rejects rather than truncates. The two that bite most often are Last Name at 80 characters and Company at 255. Long company names pasted with their legal suffix routinely cross the second one.

The fix. Before importing, check the length of your longest values — in Excel, =MAX(LEN(B:B)) entered as an array formula over the column — and trim what overflows.

Duplicate rules block the insert

If your org has duplicate rules with a block action (the default for the standard Lead rule matches on email), Salesforce refuses new records that match an existing lead or contact. The import reports rows as failed with a duplicate error, and nothing is created.

The fix. Decide up front which behaviour you want. Either deduplicate your file against your existing base before importing, or switch the rule from Block to Allow + Report for the duration of the import — and switch it back afterwards.

Encoding and separators

The Data Import Wizard expects a UTF-8, comma-delimited CSV. A file saved from a French, German or Spanish Excel is semicolon-delimited and Windows-1252 encoded, which produces either a single-column mess or mangled accented characters.

The fix. In Excel, Save as → CSV UTF-8 (Comma delimited) — the dedicated entry in the format list, not the plain CSV one.

Which importer you should be using

The Data Import Wizard handles up to 50,000 records at a time and covers leads, accounts, contacts and custom objects. Above that volume, or when you need to specify the encoding and separator yourself, use Data Loader instead.

Pre-flight checklist

• Every row has a Last Name and a Company
• Picklist values copied verbatim from Setup
• Dates written as YYYY-MM-DD
• No value exceeding its field limit
• Duplicate-rule behaviour decided deliberately
• File saved as CSV UTF-8, comma-delimited

When it's a recurring list

A one-time migration is worth doing by hand — you learn your org's validation rules along the way.

A list you re-import every month is a different problem. Importly takes the raw export, maps your columns to Salesforce's lead fields, converts the dates to ISO, normalises phone numbers, drops duplicates and empty rows, and hands back a file the Data Import Wizard accepts. Save the mapping as a profile once and every later export goes through identical rules.

Clean your first export free →