Data Cleaning
& Formatting.
Messy data costs businesses millions every year in bad decisions, failed campaigns, and broken workflows. ExtractHelp transforms your dirty, inconsistent, duplicate-ridden datasets into pristine, structured, analysis-ready gold — fast.
JOHN@GMAIL
+1-555 123 4567
New york, NY
john doe ← duplicate
??? missing field
john@gmail.com ✓
+15551234567
New York, NY 10001
— removed —
N/A (flagged)
We Turn Chaotic Data Into Clean, Actionable Datasets
Whether you have 500 rows or 5 million — if your data is messy, inconsistent, or duplicated, you can't trust it. Our data cleaning experts use a combination of Python automation, manual validation, and AI-assisted enrichment to deliver spotless, structured datasets ready for analysis, import, or automation.
Quick answer: Data cleaning and formatting is the process of removing duplicates, fixing inconsistencies, filling missing fields, and standardizing structure in a dataset so it's accurate and ready to use. ExtractHelp checks every change and typically delivers within 24–72 hours.
Duplicate Detection & Removal
We identify and eliminate exact and fuzzy duplicates across millions of rows using advanced matching algorithms — no manual guesswork.
Format Standardization
Phone numbers, dates, addresses, currencies — normalized to a consistent, universal format matched to your CRM or database schema.
Email & Phone Validation
Every email and phone number is syntax-checked, domain-verified, and flagged for deliverability — so you only market to real contacts.
Structural Reformatting
Split columns, merge fields, restructure flat files into relational tables, or transform wide-format data into long-format — all to spec.
Missing Data Handling
Blank cells filled via research, conditional logic, or clearly flagged for review — so your dataset is complete and honest.
01 — Data Intake & Audit
We receive your raw file and run an automated audit — counting duplicates, blank cells, format errors, and outliers before touching anything.
→ CSV / XLSX / JSON / Google Sheets02 — Duplicate Removal
Exact and near-duplicate rows identified and removed using both rule-based and fuzzy matching. You receive a removal log.
→ Python dedupe / FuzzyWuzzy / OpenRefine03 — Format Standardization
All fields normalized — dates to ISO 8601, phones to E.164, addresses to postal standards, text to consistent case rules.
→ Custom Python scripts / Regex04 — Validation & Enrichment
Emails verified, phones checked, missing fields researched or flagged. Optional enrichment from third-party sources available.
→ Hunter.io / NeverBounce / Manual Research05 — Delivery & QA Report
Clean file delivered in your format of choice, alongside a full QA report showing exactly what was changed and why.
→ CSV / XLSX / JSON / Google SheetsEvery Data Problem We Eliminate
If your data has any of these issues, they're costing you time, money, and missed opportunities every single day.
Duplicate Records
The same contact, company, or product appearing 2, 5, or 50 times across your database — inflating counts, skewing analytics, and sending the same email twice to the same person.
Inconsistent Formatting
Phone numbers in 12 different formats. Dates as MM/DD, DD-MM, and "Jan 5th". Country names as "US", "USA", "United States", and "U.S.A" — all in the same column.
Invalid Emails & Phones
Fake emails, syntax errors, disposable domains, and disconnected phone numbers that destroy deliverability, cause bounce rates to spike, and damage your sender reputation.
Missing & Blank Fields
Entire columns of empty cells — no job title, no company, no city. Data that cannot be segmented, personalized, or used for automation because critical fields are simply absent.
Wrong Structure & Layout
Data exported in the wrong shape — all info crammed into one column, first/last name combined, address in a single field, or columns in an order your CRM refuses to import.
Outdated & Stale Data
Contacts who changed jobs 3 years ago. Companies that no longer exist. Prices that haven't been updated since last quarter. Old data is worse than no data — it actively misleads.
See the Transformation Firsthand
This is what a typical client dataset looks like before and after our cleaning process. Every row fixed, every field verified, every format standardized.
| john doe | JOHNDOE@GMIAL.COM | 555-123-4567 |
| SARAH JOHNSON | sarah@ | (555) 987 6543 |
| john doe | JOHNDOE@GMIAL.COM | 555-123-4567 |
| michael b | michael@company | N/A |
| Emma Wilson | emma.wilson@tempmail.xyz | +1 (800)000-0000 |
| chris TAYLOR | CHRIS@OUTLOOK.COM | 1800-CALL-NOW |
| John Doe | johndoe@gmail.com ✓ | +15551234567 |
| Sarah Johnson | REMOVED (invalid) | +15559876543 |
| — Duplicate removed — | — | — |
| Michael Brown | Flagged (incomplete) | N/A (noted) |
| Emma Wilson | REMOVED (disposable) | +18000000000 |
| Chris Taylor | chris@outlook.com ✓ | REMOVED (non-numeric) |
From Raw File to Pristine Dataset in 5 Steps
Our structured delivery process ensures every dataset is cleaned, validated, and documented before it reaches your inbox.
Send Your File
Upload your CSV, Excel, JSON, or Google Sheets link. Tell us your goal — CRM import, email campaign, analysis, or all three.
Free Data Audit
We run a full automated audit in under an hour — duplicate count, format error rate, blank cell percentage, and a full cleaning plan.
Cleaning & Validation
Our team runs the cleaning pipeline — duplicates removed, formats standardized, emails validated, blanks handled — all logged.
QA & Accuracy Check
A second-pass quality review validates every change. We don't deliver until the data meets the standard we agreed with you.
Delivery + Report
Clean file in your chosen format plus a detailed QA report. What was removed, why, what was changed, and what needs follow-up.
Built for Accuracy. Delivered with Speed.
There are a hundred freelancers offering to "clean your data" on Fiverr. We're not that. We're a dedicated data engineering team with documented processes, automated validation pipelines — and if something's wrong, we fix it free.
Automated + Human Verification
Python scripts handle the volume. Human analysts catch the edge cases. Every clean file goes through both layers before delivery.
Full QA Report Included
Every project delivers a change log — exactly what was removed, fixed, enriched, or flagged. Full transparency, every time.
Free Revision Round
Not satisfied with the output? We rework any issue at no extra cost. Our goal is a clean dataset you can actually use, not just one that looks clean.
24–72 Hour Turnaround
Standard datasets delivered in under 72 hours. Large-scale enterprise files scoped individually. Rush delivery available for urgent projects.
Privacy-First Process
We sign NDAs, use encrypted file transfer, and never store your data beyond the project window. Full compliance, full peace of mind.
Any Output Format You Need
CSV, Excel, JSON, Google Sheets, Airtable, or directly matched to your CRM import template — delivered the way you need it.
Who Needs Data Cleaning & Why It Matters
Dirty data doesn't discriminate. Every industry, every team, every database has the same problem — and we've solved it for all of them.
Marketing Teams & Agencies
Clean email lists before campaigns to slash bounce rates, remove unsubscribes, eliminate duplicates, and ensure every message lands in an inbox — not a spam folder.
E-Commerce & Retail
Standardize product data across SKUs, fix category mismatches, clean customer address data for accurate shipping, and deduplicate order histories before importing into new platforms.
Real Estate Companies
Normalize property listing data pulled from multiple MLS sources — consistent addresses, standardized price formats, removed outdated listings — ready for CRM import or website publishing.
Sales Teams & CRMs
Clean and enrich your HubSpot, Salesforce, or Zoho CRM before a major campaign — removing stale contacts, merging duplicates, and standardizing all fields to your pipeline structure.
Research & Healthcare
Sanitize survey responses, standardize patient records, clean clinical trial datasets, and format research data to meet publication or compliance standards with zero tolerance for error.
Finance & Analytics
Clean transaction records, normalize currency formats, remove test entries, standardize date fields, and prepare financial datasets for modeling, reporting, and auditing.
Powered by Professional Tools
We combine automated cleaning scripts with industry-leading tools to handle data at any scale — from 500 rows to 10 million.
ExtractHelp vs The Alternatives
See why hundreds of businesses choose us over budget freelancers and generic data cleaning tools.
| Feature / Capability | ExtractHelp ✦ | Budget Freelancer | DIY / Tools |
|---|---|---|---|
| Duplicate Detection (Fuzzy Match) | Advanced | Basic only | Manual |
| Email Validation (Live Check) | Yes | Syntax only | No |
| Full QA Report Delivered | Always | Rarely | No |
| Handles 1M+ Rows | Yes | Usually not | Crashes Excel |
| Free Revision Round | Guaranteed | Extra cost | N/A |
| Output Format Flexibility | Any format | CSV/Excel only | Limited |
| Accuracy Checked Before Delivery | Yes | Varies | No |
| Dedicated Project Manager | Every project | No | No |
| GDPR Compliance + NDA | Standard | Inconsistent | No |
Simple, Transparent Pricing
One-time project fees based on data volume and complexity. No monthly subscriptions, no per-row charges. Pay once, get clean data forever.
Perfect for small lists and one-off cleaning tasks under 10,000 rows.
- Up to 5,000 rows
- Duplicate removal
- Basic format standardization
- CSV / Excel delivery
- Email support
- 3-day delivery
Ideal for CRM imports, email campaigns, and datasets up to 100,000 rows.
- Up to 50,000 rows
- Duplicate removal (fuzzy)
- Full format standardization
- Email & phone validation
- Missing data handling
- Full QA report included
- CSV / Excel / JSON / Sheets
- Free Revisions
- 7-day delivery
For large-scale datasets, recurring cleaning pipelines, and enterprise requirements.
- Unlimited rows
- Recurring cleaning pipeline
- Dedicated data engineer
- CRM schema matching
- API / automation integration
- Priority 24-hour delivery
- Free revisions
- NDA + compliance docs
Proof before you pay
See the data before you decide
We build a free sample to your exact requirements, so you can check the fields, formatting and accuracy yourself before you order. Client feedback is published on the platforms where clients hired us.
Frequently Asked Questions
Everything you need to know before sending us your data.
What file formats do you accept as input?
We accept CSV, Excel (XLSX/XLS), JSON, Google Sheets links, Airtable exports, and plain text delimited files. If your data is in a different format, reach out — we almost certainly support it or can convert it first.
What output formats do you deliver in?
Any format you need — CSV, Excel, JSON, Google Sheets, Airtable, or a custom structure matched to your CRM's import template. If you use HubSpot, Salesforce, or Zoho, we can match their exact column requirements.
How long does data cleaning take?
Standard datasets (under 100,000 rows) are delivered in 24–72 hours. Large enterprise files are scoped individually after a quick audit. Rush delivery is available — just mention your deadline when you reach out.
Is my data kept confidential?
Absolutely. We sign NDAs for all projects, use encrypted file transfer, and delete your data from our systems after delivery. We never store, sell, or share client data under any circumstances.
Can you handle datasets with millions of rows?
Yes. We use Python, SQL, and cloud-based tools built specifically for large-scale data — not Excel, which breaks above ~1M rows. We've cleaned datasets with over 10 million records for enterprise clients.
What if I'm not happy with the results?
Every project includes a free revision round. Tell us what needs fixing and we'll rework it at no charge. If we still can't resolve it, we refund the part we couldn't deliver. See our Guarantees page for full details.
Can you set up recurring data cleaning?
Yes — we offer weekly, bi-weekly, and monthly recurring data cleaning pipelines. Your data arrives clean on a schedule without you lifting a finger. Ideal for CRM maintenance and email list hygiene.
Do you provide a report of changes made?
Always. Every project includes a detailed QA change log — what rows were removed, what fields were modified, what was flagged for review, and why. Full transparency is non-negotiable for us.
Stop Trusting Dirty Data.
Start Deciding with Confidence.
Every day you operate on messy, duplicate-ridden, or incorrectly formatted data, you're making decisions on faulty foundations. Book a free consultation — we'll audit your dataset and show you exactly what needs fixing before we touch a thing.