# Step 2: Column Mapping Explained

After uploading your CSV, CSVgo automatically analyzes your file and maps columns using AI.

The goal of column mapping is to **keep only essential data**, remove junk fields, and prepare the list for clean processing and export.

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### Automatic Column Mapping

CSVgo scans all columns in your CSV and attempts to map them to known data fields, such as:

* First name
* Last name
* Email
* Company name
* Website
* LinkedIn URLs
* Job title
* Phone
* Industry
* Technologies

If a column clearly matches a known field, it is mapped automatically.

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### Ambiguous Columns (Blue Selection)

If a column could map to multiple fields, CSVgo highlights it in **blue**.

This means:

* The AI needs confirmation
* You must choose which field the column should map to

This ensures accuracy and prevents incorrect data assignments.

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### Unmapped Columns (Orange)

Columns shown in **orange** are marked as **Unmapped**.

This usually means:

* The data is irrelevant for cold email
* The column contains junk or unused information
* Keeping it would add noise to the final CSV

By default, unmapped columns are **removed** for cleaner results.

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### Managing Unmapped Data

If you want to keep unmapped columns:

1. Open the **Preferences** tab
2. Enable **Keep Other Data**

This will include unmapped columns in the final export instead of deleting them.

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### Reordering Columns

You can fully control the column order in your final CSV.

In the **Preferences** tab, you can:

* Drag and drop columns to reorder them
* Define the exact position of each field
* Save the order for future uploads

This ensures your exported CSV matches your outreach or CRM requirements.

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### Confirm and Start Processing

Once mapping is complete:

* Review mapped, ambiguous, and unmapped columns
* Adjust preferences if needed
* Click **Confirm & Process**

At this point, the full CSVgo workflow begins, including cleanup, verification, analysis, and export generation.

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### Summary

In Step 2, you:

* Let AI map your CSV columns automatically
* Manually resolve ambiguous fields
* Remove or keep unmapped data
* Define the final column order before processing

This step ensures clean, structured input before verification starts.