Export your customer data from any platform, upload the CSV, and review your results. No formatting or cleanup required.
Step 1
Export your customer data
Most platforms allow you to export customer or contact data as a CSV file. Look for an Export or Download option in your Customers, Contacts, or People section and choose CSV format.
Go to your Customers or Contacts section
Look for an Export or Download option
Choose CSV format
No special formatting needed.CustomerClarity automatically recognises common field names like Name, Email, Phone, Address, and Balance. Export whatever your platform gives you.
Step 2
Upload your file
Drag and drop your CSV onto the upload zone or click to browse. Your analysis is generated in seconds — there's nothing to configure.
Files up to 100,000 records are supported
Analysis typically completes in under 10 seconds
Results are available for 1 hour — unlock to download before they expire
Step 3
What you'll see
Once uploaded, your analysis shows groups of likely duplicate customers, sorted by risk.
A verdict per group — what we observed, not what to do
This is analysis, not action.CustomerClarity surfaces patterns. What you do with them is always your call.
Step 4
What to do with the results
Use the analysis to review potential duplicates before merging, identify conflicting customer records, and clean your data before reporting or migration.
Expand any cluster to inspect all grouped records side by side
Unlock to access the full analysis and downloadable summary report
Download the PDF to share with your team or accountant
The PDF links back to the interactive drilldown for deeper review
Step 1
Export your customers from QuickBooks Online
Go to Sales → Customers
Click the Export icon (spreadsheet icon, top right)
Choose Export to Excel — this downloads as a .xlsx or .csv file
If you get an .xlsx file, open it in Excel or Google Sheets and save as CSV
Alternative via Reports.Go to Reports → search “Customer Contact List” → run the report → Export to CSV. This often gives cleaner column names.
Step 2
Upload your file
Drag and drop your CSV onto the upload zone. QuickBooks exports are automatically recognised and normalised.
Step 3
What you'll see
Your analysis shows clusters of likely duplicate customer records, sorted by risk. Common QuickBooks duplicate patterns include:
Same customer created multiple times from POS or import
Company name vs. individual name variants for the same customer
Records with appended phone numbers or zip codes in the name field
Customers with split balances across duplicate records
Notes for QuickBooks Online
QBO-specific tips
Address formats vary.QBO exports may include billing and shipping addresses in separate columns. CustomerClarity uses the billing address for matching.
Name field quirks.Some QBO exports include records like “John Smith 6465551234” where a phone number was appended to the name. These are automatically normalised during analysis.
Balance data.If your export includes Open Balance, this will appear in the summary report. Records with split balances across duplicates are a common issue — the analysis flags these clusters for review.
Step 1
Export your contacts or accounts from Salesforce
Go to the Contacts or Accounts tab
Click the gear icon → select Export
Choose CSV format
Select the fields you want — at minimum: Name, Email, Phone, Account Name, Billing Address
Reports are often cleaner.Go to Reports → create a Contact or Account report → export as CSV. You get more control over which fields are included.
Step 2
Upload your file
Drag and drop your CSV. Salesforce field names are automatically recognised.
Step 3
What you'll see
Salesforce databases often accumulate duplicates through lead conversion, manual entry, and integrations. Common patterns include:
Contacts duplicated across multiple accounts
Lead-to-contact conversion creating parallel records
Same person entered with different email addresses over time
Company records with spelling or formatting variations
Notes for Salesforce
Salesforce-specific tips
Contacts vs Accounts.Upload either one — or combine them. CustomerClarity analyses whatever you give it. Contacts and Accounts have different field structures but both export cleanly.
Email is the strongest signal.Salesforce records often have clean email data. HIGH confidence matches are typically driven by shared email addresses across records with name variants.
Step 1
Export your contacts from HubSpot
Go to Contacts → Contacts
Click Actions → Export
Choose CSV format
Select which properties to include — at minimum: First name, Last name, Email, Phone, Company, Address
Step 2
Upload your file
Drag and drop your CSV. HubSpot exports first and last name in separate columns — these are automatically combined during analysis.
Step 3
What you'll see
HubSpot databases often grow large through form submissions and integrations. Common patterns include:
Same person submitting multiple forms with slightly different details
Company contacts imported from multiple sources
Records with personal vs. work email addresses for the same person
Notes for HubSpot
HubSpot-specific tips
First and last name are separate.HubSpot exports “First name” and “Last name” in separate columns. CustomerClarity combines them automatically — no preprocessing needed.
Lifecycle stage not included.CustomerClarity analyses identity signals (name, email, phone, address) — it doesn't use lifecycle stage or deal data. Focus your export on contact identity fields.
Step 1
Export your contacts from Xero
Go to Contacts → All Contacts
Click the Export button (top right)
Choose CSV format
This exports your full contact list including customers and suppliers
Step 2
Upload your file
Drag and drop your CSV. Xero exports are clean and automatically recognised.
Step 3
What you'll see
Xero contact lists often include both customers and suppliers. Common duplicate patterns include:
Same business entered as both a customer and a supplier
Company name variants (Ltd vs Limited, with and without punctuation)
Contacts created separately for different branches of the same business
Notes for Xero
Xero-specific tips
Customers and suppliers are mixed.Xero exports all contacts together. If you only want to analyse customers, filter by Contact Type before exporting, or upload the full list — both work.
Account numbers included.Xero exports may include your internal account number for each contact. This isn't used in matching but won't cause any issues.
Step 1
Export your customers from Shopify
Go to Customers in your Shopify admin
Click Export (top right)
Choose All customers and CSV for Excel, Numbers, or other spreadsheet applications
Click Export customers
Step 2
Upload your file
Drag and drop your CSV. Shopify customer exports are automatically recognised.
Step 3
What you'll see
Shopify stores often have duplicate customers created through guest checkouts and account creation. Common patterns include:
Same customer checking out as a guest multiple times with different emails
Account created after previous guest purchases
Same household ordering under different names
Customers with different billing and shipping addresses flagged as address variants
Notes for Shopify
Shopify-specific tips
Guest checkout duplicates are common.Shopify doesn't require account creation, so the same customer often appears multiple times with slightly different details. This is one of the most common patterns CustomerClarity detects in Shopify data.
Phone format varies.Shopify exports phone numbers in international format (+1 555 000 0000). These are automatically normalised for matching — no preprocessing needed.
Tags and metafields not used.CustomerClarity only uses identity fields (name, email, phone, address) for matching. Shopify-specific fields like tags or metafields are ignored.
Ready to analyse your data?
No account required. Upload your CSV and see your results in seconds.