Marblism Stan CSV Import: Check Leads in 15 Minutes

Download the clean template, check which rows meet Stan's documented import rule and fix expected skips before you upload the list.

A small lead-file problem becomes expensive when it is found after a campaign is built. Blank identifiers create skipped rows, missing names can trigger enrichment, and unclear columns make the import harder to review. A five-row test catches the structure first without putting an entire customer export at risk.

This is the file-preparation step. Use the Stan sales setup guide for the larger workflow, and keep outreach paused until you complete the separate Stan campaign preview challenge.

What Marblism officially supports

Marblism's current instructions say to open the Leads tab, select Import Leads, upload a CSV and map these columns: name, email, company, job title, location, LinkedIn URL and website. The same guide says you can instead drop a CSV or Excel file into Stan's chat.

The key rule is short: A row is usable if it has an email, a LinkedIn URL, or a name + company. Marblism says rows without one of those three identifier paths are skipped and the import reports how many.

Marblism also says an imported row that already contains both a name and email skips enrichment. A usable row missing either may require enrichment to find the email, which can draw from Stan's monthly enrichment quota.

Prepare a Marblism Stan CSV import step by step

1. Start with a five-row copy. Use contacts your business is allowed to contact. Do not experiment on the original CRM or customer export.
2. Keep only useful columns. Use Marblism's seven documented fields: name, email, company, job title, location, LinkedIn URL and website.
3. Paste the copy into the checker. A ready row needs an email, LinkedIn URL, or name plus company.
4. Fix expected skips with known facts. Add a verified identifier. Do not guess an address, profile, title or company just to make the count turn green.
5. Review likely enrichment rows. If you already know the person's correct name and email, include both; Marblism says that combination skips enrichment.
6. Import from Stan's Leads tab. Select Import Leads, upload the clean copy and map each column to the matching field.
7. Compare the result. Confirm Stan's imported and skipped counts match your expectation, then inspect the import tag before adding any lead to a campaign.

If the count differs, stop and inspect the exact skipped rows. A clean five-row test is easier to diagnose than a large import with mixed headers, empty records and stale contact data.

Why the five-row test is worth doing

• It exposes a bad header or empty identifier before the problem is repeated across the list.
• It shows which rows may require enrichment so you can use known contact data first.
• It gives you an expected import count to compare with Stan's own result.
• It separates lead cleanup from campaign activation, making the approval decision easier.

Once the five-row copy imports cleanly, repeat the same structure with the next small batch. More rows are only useful when the source, mapping and permission are still clear.