Upload people, companies, and job titles via XLSX

The most important decision is the upload type. Choose it from the data you actually have, then provide enough context for a reliable match without adding unnecessary personal or customer information.

Before you start

• Confirm that you are allowed to process the data and that it belongs in the selected Signalist workspace.
• Keep one data type per column and use a single, descriptive header row.
• Remove empty rows, totals, formulas, merged cells, comments, and decorative formatting.
• Clean obvious duplicates and exclude internal employees, customers, or other protected contacts before upload.
• Prepare a small test file first. Review the result before processing the full dataset.

Choose the right upload type

A LinkedIn URL can be a stronger matching signal than a name alone when the URL is current and you are allowed to use it. If you do not have a URL, combine the name with company and role information instead of relying on a single ambiguous value.

Signalist The verified Create new list view with the three upload cards Start with a list of people, Start with a list of companies, and Start with a list of job titles.

Prepare a clean XLSX file

Use clear columns such as First name, Last name, Company, Job title, Company website, and LinkedIn URL only where they are relevant to the selected upload type. Keep values in the correct column and use the same convention throughout the file.

• Use the current company and current job title where possible.
• Prefer the company website or domain when company names are ambiguous.
• Keep LinkedIn profile URLs in a dedicated column and remove tracking parameters.
• Use plain cell values. Replace formulas with their final values before upload.
• Do not include passwords, API keys, private notes, health data, or other information Signalist does not need.

Signalist A small example XLSX file with a single header row and separate columns for the relevant person, company, role, website, and LinkedIn data.

Steps

1. **Create the workbook. **Save the source as an XLSX file with one descriptive header row and one record per row. Keep each field in its own column.
2. **Add the fields needed for your upload type. **For people, add identifying person and company context. For companies, add company name and preferably website or domain. For job-title uploads, combine target role information with company data.
3. **Clean the file. **Remove blank rows, formulas, merged cells, formatting-only columns, obvious duplicates, internal contacts, and records that should be excluded.
4. **Open Create new list. **Choose Start with a list of people, Start with a list of companies, or Start with a list of job titles according to the input you prepared.
5. **Name and upload the file. **Use a clear list name that identifies the source, purpose, and date without exposing confidential data.
6. **Map the columns. **Match every spreadsheet column to the correct Signalist field. Leave unnecessary columns unmapped and resolve missing required fields before continuing.
7. **Review the preview. **Confirm that headers, sample values, and mappings are aligned. Stop if values appear in the wrong fields or if sensitive data is visible.
8. **Process a small test. **Start with a limited sample where the current flow allows it, then inspect Found, Not Found, email status, and exclusion reasons.
9. **Validate before scaling. **Check several matched and unmatched records, correct the source or mapping, and only then process the remaining approved data.

Signalist The verified column-mapping and preview step after an XLSX file has been selected.

Review the upload result

Review both successful and unsuccessful matches. A high Found count is not enough on its own: open a sample and confirm that Signalist matched the intended person or company.

• Compare Found and Not Found results against the source file.
• Check whether the current employer and role are plausible for matched people.
• Review email status before using addresses in outreach.
• Inspect exclusion reasons and existing-list indicators such as Other Lists where available.
• Resolve duplicates and blacklist requirements before assigning leads or starting a campaign.

Signalist The verified post-upload results view with Found, Not Found, email status, exclusions, and existing-list indicators where available.

Troubleshooting

Frequently asked questions

Can I upload a CSV file instead of XLSX?

Use the file type offered by the current upload flow. This article documents XLSX. If your workspace shows another supported format, follow its preview and mapping requirements; otherwise convert the file to XLSX before uploading.

Which fields give Signalist the best chance of finding a person?

Use a current name together with company and role context. A current LinkedIn URL can provide a strong additional identifier when it is available and appropriate to process.

Should I remove duplicates before uploading?

Yes. Clean obvious duplicates in the source file first, then review existing contacts, Other Lists, exclusions, and blacklist rules in Signalist before using the results.

Why should I test with a small file?

A small test makes it easier to detect mapping errors, weak identifiers, sensitive columns, and unexpected matches before they affect a larger dataset or consume unnecessary credits.

What should I do with Not Found records?

Review their names, companies, current roles, websites, and LinkedIn URLs for missing or outdated information. Correct the source file and test again; do not repeatedly re-upload unchanged data.

Can I include internal notes in the spreadsheet?

Only include fields required for the Signalist task. Remove confidential notes and unnecessary personal or customer information before upload.