Free CSV Health Checker for CRM Imports

Upload or paste a CSV file to instantly check for duplicates, missing fields, email issues, and data-quality problems that break CRM imports. Supports HubSpot, Salesforce, and any CRM that accepts CSV uploads.

The checker analyses your file and returns a prioritised list of issues to fix - before they cause problems in production.

Check your CSV

Upload a file or paste CSV content. Max 500 rows, 1 MB.

Do not upload sensitive personal data or files you are not allowed to process. This checker is for small sample CSVs and pre-import data-quality checks. Your CSV is processed by DataFixr to generate the health report and is not stored after analysis.
Example report - sample data only, not a real analysis

What a CSV health check looks like

Here is an example of the output you get when you run the checker on a typical sales CSV with common data-quality issues.

42 Needs attention CSV health score
7 data rows
6 columns
5 issues found
1 fuzzy duplicate clusters

Issues found in this example

  • 1 exact duplicate row - jane.smith@acme.com appears twice with identical data
  • 1 fuzzy duplicate cluster - "Acme Ltd" and "acme limited" likely refer to the same company
  • 1 invalid email address - bob.jones@ is missing a domain
  • 1 role-based email address - info@globaldemo.com is not a personal contact email
  • Inconsistent lifecycle_stage values - mix of "Lead", "lead", "Subscriber", "MQL" without a standard format
Email: email First name: first_name Last name: last_name Company: company Phone: phone

Upload your own CSV above to get a real health report, or

What to fix before a CRM import - checklist

Work through these checks before importing any CSV into HubSpot, Salesforce, or another CRM. The order matters: fix duplicates first, then missing fields, then formatting.

  • Remove duplicate email addresses HubSpot and Salesforce both deduplicate on email. Any duplicate in the CSV will merge with or overwrite an existing record.
  • Fill or remove records missing company names Contacts without a company name cannot be matched to accounts and are harder to segment or route.
  • Fix invalid email formats Addresses missing @ symbols, domains, or extensions fail CRM validation and increase bounce rates.
  • Populate required CRM fields HubSpot requires email. Salesforce requires Last Name. Importing records without required fields causes silent failures or import errors.
  • Remove or consolidate empty columns Empty columns get mapped to CRM fields during import and can overwrite valid existing data with blank values.
  • Standardise lifecycle and status field values Mixed casing ("Lead" vs "lead") and non-standard values ("hot lead", "MQL candidate") break segmentation and automation triggers.
  • Normalise company-name variants "Acme Ltd", "Acme Limited", and "acme" are treated as separate accounts in most CRMs, preventing correct account matching.
  • Format phone, country, and domain fields consistently Mixed phone formats (+44, 07xxx, 0044) and non-standard country codes reduce data usability and enrichment match rates.

What the CSV health checker looks for

Before running a CSV through a CRM import, it's worth knowing exactly what problems exist in the file. The checker analyses the following:

  • Duplicate contact checks - exact matches on email address or a combination of name and company fields that would create duplicate contacts on import. The checker reports the count and flags which records are affected.
  • Fuzzy duplicate detection - records that refer to the same contact but differ in spelling, formatting, or capitalisation (e.g. "Jane Smith" and "J. Smith" at the same company). These are grouped into clusters so you can review them before importing.
  • Missing required field checks - rows without an email address, first name, or other fields that CRMs require for a valid record. Records with missing required fields either fail validation or import as incomplete contacts.
  • Email format validation - addresses that fail basic syntax checks, role-based addresses (info@, admin@, support@), and obviously undeliverable formats. Invalid emails increase hard bounce rates and hurt sender reputation.
  • Column detection - which columns contain email, company, name, and phone data, so you can verify the mapping before running the import.
  • Company-name standardisation checks - mixed capitalisation, legal suffix variants ("Ltd" vs "Limited"), and other formatting inconsistencies that prevent correct account matching in the CRM.
  • CRM import readiness checks - a combined assessment of whether the file is ready to import based on the issues found, with a health score from 0 to 100.

HubSpot CSV import checks

HubSpot imports fail or produce dirty data for a small set of predictable reasons. The most common issues to check before a HubSpot CSV import:

  • Duplicate email addresses - HubSpot deduplicates contacts on email address. If your CSV contains duplicate emails, HubSpot will update the existing record rather than creating a new one, which can overwrite clean data with stale values. Remove duplicates before importing.
  • Column headers that don't match HubSpot property names - HubSpot maps CSV columns to contact properties during import. Headers that don't match a property name require manual mapping during the import wizard. Pre-aligning headers to HubSpot internal names reduces import errors and speeds up the process.
  • Invalid lifecycle stage values - HubSpot's lifecycle stage property accepts only specific values (Subscriber, Lead, Marketing Qualified Lead, Sales Qualified Lead, Opportunity, Customer, Evangelist, Other). Any non-standard value will either fail or default to a blank.
  • Missing email address field - HubSpot requires an email address to create a contact record. Rows without email will be skipped during import.
  • Date formatting issues - HubSpot expects dates in ISO 8601 format (YYYY-MM-DD). Other date formats may be parsed incorrectly or rejected.

For a complete HubSpot import walkthrough, see the guide on cleaning a CSV before uploading it to HubSpot or the HubSpot import cleaning page.

Salesforce CSV import checks

Salesforce CSV imports via Data Import Wizard or Data Loader have their own set of common failure modes. Check for these before importing:

  • Missing Last Name field - Salesforce requires a Last Name value for every contact or lead record. Rows missing Last Name will fail validation or be skipped.
  • Duplicate records by email or lead key - Salesforce Data Import Wizard can match on email or name. If duplicates exist in the CSV, the import may create multiple records for the same person or update the wrong existing record.
  • Picklist value mismatches - Salesforce fields like Lead Status, Rating, and Industry accept only values defined in the org's picklist. Values outside that list cause import errors or default to blank.
  • API field name vs. label - Salesforce Data Loader uses API field names (e.g. FirstName, LastName, Email), not display labels. Mismatches between CSV headers and API names cause columns to be ignored entirely.
  • Phone number formatting - While Salesforce accepts most phone formats, inconsistent formats produce noisy data that's harder to use in workflows and routing rules.

For CRM-agnostic cleaning guidance, see the CRM data cleaning page.

Why CSV files break CRM imports

Most CSV files collected from events, third-party tools, or manual research arrive with at least one data-quality problem. Common causes of failed or dirty CRM imports:

  • Duplicate email addresses split contact history across multiple records and break routing and assignment rules.
  • Inconsistent company names - "Acme Ltd", "Acme Limited", and "acme" are treated as separate accounts by most CRMs, preventing accurate account matching.
  • Column headers that don't match CRM field names cause data to land in the wrong field or get dropped entirely during import.
  • Invalid or role-based email addresses increase hard bounce rates, hurt sender reputation, and fail CRM validation on import.
  • Missing values for required CRM properties cause the import to skip records silently or fail with a validation error.

A quick pre-import check catches all of these before they enter the CRM. See the CSV cleaning tool for the full cleaning workflow.

What to fix before uploading to HubSpot or Salesforce

Once you know what's wrong, the fix order matters. Work through this checklist before the next import:

  1. Remove exact duplicates - deduplicate on email address first, then on name + company combinations.
  2. Review fuzzy duplicate clusters - check near-matches manually or with a tool to decide whether to merge or keep separate records.
  3. Fill or remove records with missing required fields - records without email addresses will fail HubSpot validation or import as incomplete leads.
  4. Standardise company names and job titles - normalise formatting so CRM account matching and segmentation work correctly after import.
  5. Validate email addresses - remove role-based, syntactically invalid, and high-risk addresses before they reach an outbound tool.
  6. Align column headers to CRM field names - match your CSV headers to HubSpot property names or Salesforce field API names to ensure correct field mapping.

See the guide on HubSpot import cleaning for a step-by-step walkthrough, or CRM data cleaning for a CRM-agnostic approach.

Related CSV cleaning guides

Step-by-step guides on cleaning, deduplication, and import preparation for sales and RevOps teams.

Browse all CSV cleaning guides →

Frequently asked questions

What does the CSV health checker look for?
The checker analyses your CSV for duplicate rows, missing required fields, email address issues, inconsistent formatting, and data-quality problems that typically cause CRM imports to fail or produce dirty data. It reports detected columns, row counts, and a prioritised list of issues to fix before importing.
Is this the same as the full DataFixr cleaning tool?
No. The CSV health checker is a read-only analysis tool. It tells you what problems exist in the file but does not clean or modify it. The full DataFixr platform performs the actual cleaning, deduplication, standardisation, and produces a clean export. The health checker is designed for a quick pre-import readiness check.
Does the checker store my CSV data?
Your CSV is sent to the DataFixr analysis service for processing and is not stored after the check completes. Do not upload files containing sensitive personal data. This tool is designed for small sample exports and pre-import data-quality checks.
What file size and row limits apply?
The public health checker accepts CSV files up to 1 MB in size and up to 500 data rows. For larger files, use the full DataFixr platform which supports files with tens of thousands of rows.
Why is my CSV failing the import into HubSpot or Salesforce?
Common causes include duplicate email addresses, column headers that do not match CRM field names, invalid email formats, missing required fields, and values that do not match CRM picklist options. Run the health checker to identify which of these issues exist in your file before the next import attempt.
How do I check a CSV for duplicate contacts before a HubSpot import?
Upload or paste your CSV into the free health checker. It will identify exact duplicate rows and fuzzy duplicate clusters - records that look like the same contact but differ in spelling, capitalisation, or formatting. HubSpot deduplicates on email address by default, so any duplicate email in the file will either create a duplicate contact or overwrite an existing one depending on your import settings.
What is a CSV health score?
The CSV health score is a number between 0 and 100 that summarises the overall data quality of your file. A score above 75 means the file is largely clean and ready for import. A score between 35 and 75 means there are issues that should be addressed before importing. A score below 35 means the file has significant problems that will likely cause duplicate records, failed imports, or dirty CRM data if uploaded without cleaning first.
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