# How CSVgo Processes a Lead List

## How CSVgo Processes a Lead List

CSVgo processes lead lists through a structured, automated workflow designed for cold email preparation.

This page explains each step, from uploading an unverified file to generating export-ready data.

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### Step 1: Upload a Messy, Unverified Lead List

You start by uploading a raw CSV file.

The file can contain:

* Unverified email addresses
* Duplicate rows
* Inconsistent columns
* Mixed or unnecessary data

CSVgo is designed to handle imperfect input. The list does not need to be cleaned before upload.

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### Step 2: AI-Based Column Mapping

CSVgo automatically analyzes the uploaded file and maps columns using AI.

This step:

* Detects relevant fields such as names, company, and email
* Identifies unnecessary or junk columns
* Suggests a clean, standardized structure

Before processing continues, you can review and confirm the column mapping to ensure only essential data is kept.

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### Step 3: Lead List Data Cleanup

Once mapping is confirmed, CSVgo cleans the data.

This includes:

* Removing duplicate email addresses
* Cleaning first and last names
* Normalizing company names
* Renaming and rearranging columns
* Separating rows with missing email addresses

The goal of this step is to produce a consistent, structured dataset before verification begins.

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### Step 4: Email Verification (Primary Verification)

CSVgo performs standard email verification across the entire list.

This step checks:

* Syntax and formatting
* Domain and MX records
* Mail server responses

Emails are initially classified as:

* Valid
* Invalid
* Risky (catch-all)

At this stage, catch-all emails are identified but not discarded.

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### Step 5: Catch-All Verification (Secondary Verification)

All risky catch-all emails are sent through an additional verification step.

This secondary analysis:

* Applies deeper validation signals
* Separates deliverable catch-all emails from undeliverable ones

This allows CSVgo to recover usable leads that basic verification tools typically remove.

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### Step 6: Email Service Provider Identification

CSVgo identifies the email service provider associated with each email address.

Providers are grouped into:

* Google
* Other providers
* Microsoft / Outlook

The list is structured so that:

* Google-based emails appear first
* Other providers follow
* Outlook emails are grouped last

This ordering supports safer sending strategies, such as delaying Outlook campaigns to improve inbox placement.

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### Step 7: Analytics Generation

After processing is complete, CSVgo generates an analytics overview.

This includes:

* Initial row count
* Rows after deduplication
* Valid and invalid email counts
* Deliverable rate
* No-email rows

Analytics provide visibility into list quality and processing outcomes.

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### Step 8: Export Generation

CSVgo generates four export options designed for speed and flexibility:

* **Deliverable Emails**
* **Deliverable (Outlook Removed)**
* **No Email Rows**
* **All Results**

Each export is immediately usable in cold email sending tools without additional cleanup.

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### Summary

CSVgo processes lead lists through a single automated flow:

1. Upload raw data
2. Map and confirm columns
3. Clean and normalize data
4. Verify emails
5. Analyze catch-all domains
6. Identify email service providers
7. Generate analytics
8. Produce workflow-ready exports

The result is clean, verified, and segmented data ready for cold email campaigns.