You will get a clean, deduplicated, CRM-ready contact list from your messy CSV
Project details
Messy contact data breaks CRM imports and bounces cold email. Send your file and get back a clean, upload-ready version.
What gets fixed:
• Name casing: MCDONALD becomes McDonald, o'brien becomes O'Brien
• Phone numbers normalised to one international format
• Invalid, role-based (info@, sales@) and disposable emails flagged
• Duplicates removed on email and name
• Blank rows, junk headers, NULL, and N/A values cleared
• Multiple files merged into one list
I use Python, not manual Excel work, so 25,000 rows takes seconds. Reads CSV, Excel, tab, or semicolon-delimited files of any encoding. It works out which column holds what from the data, so your headers can be named anything.
Nothing is deleted silently. You get the cleaned file, a second file listing every removed row and why, and a one-page summary of what was fixed. Rows are always equal, kept, plus removed.
Benchmarked on 5,104 corrupted rows: 2.3 seconds, 100% of names correctly cased, and 100% of phones normalized.
Message me before buying. Send 50 rows, and I will clean them free within the hour so you can check the output first.
What gets fixed:
• Name casing: MCDONALD becomes McDonald, o'brien becomes O'Brien
• Phone numbers normalised to one international format
• Invalid, role-based (info@, sales@) and disposable emails flagged
• Duplicates removed on email and name
• Blank rows, junk headers, NULL, and N/A values cleared
• Multiple files merged into one list
I use Python, not manual Excel work, so 25,000 rows takes seconds. Reads CSV, Excel, tab, or semicolon-delimited files of any encoding. It works out which column holds what from the data, so your headers can be named anything.
Nothing is deleted silently. You get the cleaned file, a second file listing every removed row and why, and a one-page summary of what was fixed. Rows are always equal, kept, plus removed.
Benchmarked on 5,104 corrupted rows: 2.3 seconds, 100% of names correctly cased, and 100% of phones normalized.
Message me before buying. Send 50 rows, and I will clean them free within the hour so you can check the output first.
Data Tool
PythonWhat's included
| Service Tiers |
Starter
$15
|
Standard
$35
|
Advanced
$70
|
|---|---|---|---|
| Delivery Time | 1 day | 1 day | 2 days |
Number of Revisions | Unlimited | Unlimited | Unlimited |
Number of Pages Mined/Scraped | 1 | 1 | 1 |
Number of Sources Mined/Scraped | 1 | 1 | 1 |
Optional add-ons
You can add these on the next page.
12-hour rush delivery
+$15
Merge up to 5 extra files
+$15Frequently asked questions
About Pranav
Python Data QA & Lead List Normalization | HubSpot & Apollo
Satara, India - 8:38 pm local time
I build automated Python data QA pipelines that clean, normalize, and deduplicate 50,000+ lead records in seconds—with a strict Zero-Silent-Loss guarantee.
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THE ZERO-SILENT-LOSS GUARANTEE:
Most data cleaners quietly drop rows when they encounter malformed delimiters or unescaped quotes. With every dataset I process:
• Every single input row is accounted for (Input Rows = Kept + Removed).
• You receive your cleaned CRM-ready file PLUS an itemized audit log detailing the exact reason for every dropped or merged record.
========================================
WHAT MY PYTHON PIPELINE DELIVERS:
• NAMES AND TITLES:
- Casing normalization (McDonald, O'Brien, Jean-Luc, van der Berg)
- Removes noise honorifics (Mr, Dr, Jr, PhD) and splits full names into First and Last Name
• EMAIL ACCURACY AND DELIVERABILITY:
- Fixes common domain typos (gmial to gmail, outlok to outlook)
- Strips plus-tags and extracts clean emails from display wrappers
- Flags disposable and role-based emails (info, sales) to protect sender reputation
• PHONE NORMALIZATION:
- Standardizes messy formats into global E.164 (+1-XXX-XXX-XXXX) or US standard (XXX) XXX-XXXX
• RECOVERY AND DEDUPLICATION:
- Recovers displaced columns caused by unescaped commas in company and address fields
- Smart deduplication that preserves distinct colleagues at the same firm
COMPATIBILITY:
Ready for direct 1-click import into HubSpot, Salesforce, Apollo, Klaviyo, Zoho, Smartlead, Instantly, and Excel.
Want to test before hiring? Message me with 50 sample rows from your active list. I will clean and return them in 10 minutes for free with a full data health audit log.
Steps for completing your project
After purchasing the project, send requirements so Pranav can start the project.
Delivery time starts when Pranav receives requirements from you.
Pranav works on your project following the steps below.
Revisions may occur after the delivery date.
Send your file
Upload your CSV or Excel file and tell me the output format you need and which country most phone numbers are from.
Cleaning and validation
I deduplicate, fix name capitalization, normalize phone numbers, validate emails, and clear blank rows and junk headers.