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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.
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.
We identify and eliminate exact and fuzzy duplicates across millions of rows using advanced matching algorithms — no manual guesswork.
Phone numbers, dates, addresses, currencies — normalized to a consistent, universal format matched to your CRM or database schema.
Every email and phone number is syntax-checked, domain-verified, and flagged for deliverability — so you only market to real contacts.
Split columns, merge fields, restructure flat files into relational tables, or transform wide-format data into long-format — all to spec.
Blank cells filled via research, conditional logic, or clearly flagged for review — so your dataset is complete and honest.
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 SheetsExact and near-duplicate rows identified and removed using both rule-based and fuzzy matching. You receive a removal log.
→ Python dedupe / FuzzyWuzzy / OpenRefineAll fields normalized — dates to ISO 8601, phones to E.164, addresses to postal standards, text to consistent case rules.
→ Custom Python scripts / RegexEmails verified, phones checked, missing fields researched or flagged. Optional enrichment from third-party sources available.
→ Hunter.io / NeverBounce / Manual ResearchClean file delivered in your format of choice, alongside a full QA report showing exactly what was changed and why.
→ CSV / XLSX / JSON / Google SheetsIf your data has any of these issues, they're costing you time, money, and missed opportunities every single day.
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.
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.
Fake emails, syntax errors, disposable domains, and disconnected phone numbers that destroy deliverability, cause bounce rates to spike, and damage your sender reputation.
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.
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.
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.
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) |
Our structured delivery process ensures every dataset is cleaned, validated, and documented before it reaches your inbox.
Upload your CSV, Excel, JSON, or Google Sheets link. Tell us your goal — CRM import, email campaign, analysis, or all three.
We run a full automated audit in under an hour — duplicate count, format error rate, blank cell percentage, and a full cleaning plan.
Our team runs the cleaning pipeline — duplicates removed, formats standardized, emails validated, blanks handled — all logged.
A second-pass quality review validates every change. We don't deliver until the data meets our 98%+ accuracy threshold.
Clean file in your chosen format plus a detailed QA report. What was removed, why, what was changed, and what needs follow-up.
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 a 98%+ accuracy guarantee — or we fix it free.
Python scripts handle the volume. Human analysts catch the edge cases. Every clean file goes through both layers before delivery.
Every project delivers a change log — exactly what was removed, fixed, enriched, or flagged. Full transparency, every time.
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.
Standard datasets delivered in under 72 hours. Large-scale enterprise files scoped individually. Rush delivery available for urgent projects.
We sign NDAs, use encrypted file transfer, and never store your data beyond the project window. Full compliance, full peace of mind.
CSV, Excel, JSON, Google Sheets, Airtable, or directly matched to your CRM import template — delivered the way you need it.
Dirty data doesn't discriminate. Every industry, every team, every database has the same problem — and we've solved it for all of them.
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. Clients saw deliverability jump from 68% to 96% post-clean.
Standardize product data across SKUs, fix category mismatches, clean customer address data for accurate shipping, and deduplicate order histories before importing into new platforms.
Normalize property listing data pulled from multiple MLS sources — consistent addresses, standardized price formats, removed outdated listings — ready for CRM import or website publishing.
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.
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.
Clean transaction records, normalize currency formats, remove test entries, standardize date fields, and prepare financial datasets for modeling, reporting, and auditing.
We combine automated cleaning scripts with industry-leading tools to handle data at any scale — from 500 rows to 10 million.
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 |
| 98%+ Accuracy Guarantee | Yes | No guarantee | No |
| Dedicated Project Manager | Every project | No | No |
| GDPR Compliance + NDA | Standard | Inconsistent | No |
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.
Ideal for CRM imports, email campaigns, and datasets up to 100,000 rows.
For large-scale datasets, recurring cleaning pipelines, and enterprise requirements.
Businesses across e-commerce, SaaS, real estate, and marketing rely on ExtractHelp to clean the data that powers their growth.
"ExtractHelp cleaned our 80,000-contact email list before a major product launch. They removed 14,000 duplicates, validated every email, and delivered in 36 hours. Our bounce rate dropped from 18% to under 2%. Absolutely phenomenal result."
"We migrated our CRM from Zoho to HubSpot with 120,000 contacts. ExtractHelp cleaned, de-duped, and reformatted everything to HubSpot's exact import schema. Zero errors on import. What would have taken our team weeks took them 3 days."
"Our property database had listings from 6 different MLS sources, all in wildly different formats. ExtractHelp standardized everything — addresses, prices, square footage, dates — into a clean unified schema. Now it imports flawlessly every time."
"We sent them a 500,000-row product catalog from our WooCommerce store. Complete chaos — duplicate SKUs, inconsistent categories, mixed currencies, missing weights. They returned a perfectly structured file in 4 days. The QA report alone was worth the price."
"I was skeptical about outsourcing our clinical trial data cleaning. But ExtractHelp understood the compliance requirements, signed the NDA, and delivered a spotless dataset with a full audit trail. They know their stuff at a professional level."
"We now use ExtractHelp on a weekly basis — every Monday morning, a fresh cleaned file arrives ready for our sales team to use. The recurring pipeline they built handles everything automatically. It's become a core part of our sales operation."
Everything you need to know before sending us your data.
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.
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.
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.
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.
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.
Every project includes a free revision round. Tell us what needs fixing and we'll rework it at no charge. If the issue is unresolvable on our end, we offer a full refund. See our Guarantees page for full details.
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.
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.
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.