Skip trace CSV checker: see how your file will map before you upload

The checker reads a CSV in your browser and shows which of your columns will be used for the owner name, the mailing address and the property address, how many rows are exact duplicates, and what to fix before you order. It runs the same column detection and required-field check as the Skipmatch order flow, splits a one-column address into street, city, state and ZIP, and downloads the fixed file.

Price your list See a sample result

Key facts

Price: a flat $0.03 a record at any list size from 50 to 100,000 records.
Unit: Priced per matched record.
Minimum order: 50 records
Minimum charge: Minimum charge $0.50 when any record matches.
Single search: Single search: $0.10, charged only on a match, paid from prepaid credit ($10 minimum top-up).
Prepaid credit: Prepaid credit expires 12 months after your last credit purchase, single search or credit-paid list, and unused credit is refundable on request within 90 days of purchase.
Free tool: Check your list free at /tools/skip-trace-csv-checker. Check columns, split addresses and download a fixed CSV in your browser before tracing at $0.03 a record. No account needed.
Subscription: None. A list order is paid for on its own by card or prepaid credit.
Max per order: 100,000 rows or 50 MB per file
Output: Up to 10 phones per owner, each with its line type (mobile, landline or VoIP), plus emails where found
Sources: 3 core providers: idiCORE, Enformion and Delvepoint
Not for: FCRA uses: credit, insurance, employment or tenant screening
Prices last changed: 2026-10-02
Last updated: 2026-10-08

Check your file

It opens on our ten-row sample file, whose records are invented, so you can see what a result looks like. Drop your own .csv in to replace it.

Drop your CSV here

A .csv with a header row, up to 50 MB.

The file is read by your browser and is not uploaded, stored or sent anywhere. Close the tab and it is gone.

sample-input.csv(sample file, invented records)

12 columns · 1 KB

Records to order: 10
Ready to order: 10
Missing a name: 0
Incomplete address: 0
Exact duplicates: 0
Address couldn't be split: 0

10 rows read.

The fixed file uses the order’s own column names, with names and addresses split. Made in your browser.

The required columns are there

A name and a complete address block are mapped, so the order's mapping step will let this file through.

The sample holds 10 records, which is fewer than one order takes. Your own list needs 50 to 100,000 records after duplicates are removed.

How sample-input.csv maps to the fields the order uses
Field	Your column	How it matched
Owner first name	`OwnerFirstName`	Exact name
Owner last name	`OwnerLastName`	Exact name
Mailing street	`MailingAddress`	Exact name
Mailing city	`MailingCity`	Exact name
Mailing state	`MailingState`	Exact name
Mailing ZIP	`MailingZip`	Exact name
Property street	`PropertyAddress`	Exact name
Property city	`PropertyCity`	Exact name
Property state	`PropertyState`	Exact name
Property ZIP	`PropertyZip`	Exact name

Not used to find the owner, and returned unchanged in your result file: APN, Acres.

How to use it

Export your list as CSV. Save or download the list as a .csv file with a header row naming the columns. Excel workbooks (.xlsx) are not read, so use Save As, CSV.
Drop the file into the checker. Drop it on the checker or choose it. The file is read by your browser and is not uploaded; the page shows the result straight away.
Read the column mapping. Each field shows the column the order flow would use for it. A column matched only on part of its header is flagged, so check those first.
Fix what the checker flags. Add a name column if one is missing, rename headers the checker read wrongly, and fill in or remove rows with no name or no complete address. If the whole address sits in one column the checker splits it for you; choose Download fixed CSV to keep the split file.
Upload it to an order. Create an order and upload the same file. The mapping step starts from the same guesses, lets you correct any column by hand and shows the price before you pay.

What the checker looks at

The header row and separator. The first line has to name the columns. Commas, tabs, pipes and semicolons are detected on their own.
Which column feeds which field. Your headers are matched to the ten fields the order uses: owner first and last name, and street, city, state and ZIP for the mailing and the property address. One column holding the whole name is split into first and last when no separate name columns are found.
The required fields. An owner name, and one complete address block (street, city, state and ZIP) for either the mailing or the property address. Without both, the order's mapping step will not go on.
Duplicates and the record count. The same duplicate rule and the same count the order is priced on. See Duplicates.
An address in one column. A column of whole addresses is split into street, city, state and ZIP. A row that will not split is left out of the order and is not charged for.
Rows that need a look. Rows ready to order, rows with no name, rows with no complete address, and rows named for a company, trust or estate, with the first few examples of each. A row with no name or an incomplete address still counts as a record.

It does not look anyone up, check that an address exists or can receive mail, or estimate how many records will come back with a phone or email. It checks the file, not the people in it.

Column names we recognise

Matching ignores case, spaces and punctuation, so Owner First Name, owner_first_name and OWNERFIRSTNAME all read as ownerfirstname. Within a field, an exact match always wins. When a field has no exact match, a header that contains one of its spellings is used instead: Primary Mailing Address contains mailingaddress. Fields are filled in a fixed order (names, then mailing address, then property address), and a column used for one field is not used for another. So an earlier field's partial pick can take a header that exactly matches a later field (see Postal Code below).

Header spellings the column detector maps to each field
Field	Header spellings that match
Owner first name	firstname, ownerfirstname, owner1firstname, first, fname, ownerfirst, contactfirstname
Owner last name	lastname, ownerlastname, owner1lastname, last, lname, ownerlast, surname, contactlastname
Owner full name (split into first and last)	ownername, owner, owner1, name, contactname, propertyownername
Mailing street	mailingaddress, mailaddress, mailingstreetaddress, mailingaddress1, ownermailingaddress, mailingstreet, mailstreet, owneraddress
Mailing city	mailingcity, mailcity, ownermailingcity, ownercity
Mailing state	mailingstate, mailstate, ownermailingstate, ownerstate, mailingprovince
Mailing ZIP	mailingzip, mailzip, mailingzipcode, mailingpostalcode, ownerzip, mailpostal
Property street	propertyaddress, propertystreetaddress, siteaddress, situsaddress, address, streetaddress, propertyaddress1, addressline1
Property city	propertycity, sitecity, situscity, city
Property state	propertystate, sitestate, situsstate, state, st
Property ZIP	propertyzip, sitezip, situszip, zip, zipcode, postalcode, zip5

This table is generated from the detector itself: a spelling is listed only when the detector, given that header alone, maps it to that field.

Four headers that catch people out

Address, City, State and Zip with no prefix are read as the property address. If they hold the owner's mailing address, rename them Mailing Address, Mailing City, Mailing State and Mailing Zip, or pick them under Mailing address when you map the order.
Full Name and Owner Full Name are read as a last name. Both headers contain lname, and last-name spellings are tried before whole-name ones, so the order then asks for a first name. Rename the column Owner Name, Owner or Name and it is split into first and last.
With no state column, Postal Code or Estimated Value can be read as the property state. Both contain st. Add a State column, or rename the ZIP column Zip. The checker marks every partial pick so you can spot this.
A column is used once. After a header is picked for one field it is out of the running for the rest, so one wrong early pick can leave a later field with no column at all.

Warnings and what to do

Everything the checker can flag, what it means, and the fix. Red messages stop an order; the rest are advice.

CSV checker warnings, what they mean and what to do
Message	What it means	What to do
Not a .csv file	Only .csv files are read. Excel workbooks (.xlsx, .xls) and other spreadsheet files are refused here and by the order upload.	Save or download the sheet as CSV UTF-8, then check the saved file.
Over 50 MB	One order takes a file of up to 50 MB.	Split the list into two files and run each as its own order.
No header row was found	The first line has to name the columns.	Add a header row, or delete any title lines above it.
Rows with a different number of columns than the header	Usually a comma inside a value that is not in quotes. Those rows are still included.	Export the list again from the tool it came from, or put quotes around values that contain commas.
The delimiter could not be detected	The columns could not be told apart with confidence.	Save the file again as comma-separated CSV.
Choose the columns holding the owner's name	No first and last name pair and no whole-name column were recognised. A Full Name header lands here: it is read as a last name only.	Rename the headers First Name and Last Name, or one column Owner Name. You can also pick them by hand when you order.
Map one complete address block	Street, city, state and ZIP were not all found for either address.	Rename the missing header using the table above, or pick it by hand when you order.
Only the mailing (or property) address is mapped	Advice only: the order can go ahead.	Add the other address if your list has it.
Partial name: check it	The column was picked because its header contains a spelling, not because it is one.	If the pick is wrong, rename the header or choose the right column when you order.
Too few or too many records	One order takes 50 to 100,000 records, counted after duplicates are removed.	Combine small lists into one file; split large ones into several.
Rows with no owner name, or no complete address	Those rows are still counted as records.	Fill them in, or delete them before you order.
We split your address column	A column held whole addresses and each one was split into street, city, state and ZIP. The first rows are shown.	Check the preview, then use Download fixed CSV so your file has the split columns.
Rows whose address we couldn't split	The address had no recognisable city, state or 5-digit ZIP, or was blank. The row is left out of the order and not charged for.	Open Rows we couldn't fix, correct them, and add them to a later order.
Rows named for a company, trust or estate	The name belongs to an entity, not a person. The rows are still counted as records.	Look up the person behind the entity and put their name on the row, or take the row out.
Not saved as UTF-8	Accented letters may not come through intact.	In Excel, use File, Save As, CSV UTF-8.

Duplicates

Two rows are exact duplicates when every mapped name and address field matches, after spaces at either end are trimmed and letter case is ignored, with state names turned into two-letter codes (South Carolina becomes SC) and ZIP+4 codes cut to five digits. The first row is kept and the others are removed before the order's record count is set, and that record count is what the quote prices. The checker runs the same rule on your file.

Columns that are not mapped, such as APN, acreage or a list name, are not compared. Two parcels with the same owner and the same mailing address therefore count as one record when the property address is not mapped, or when both carry the same property address, as neighbouring vacant lots often do. If you need each parcel as its own record, map the property address and make sure it differs from parcel to parcel.

File limits

Skipmatch file limits for one order
Limit	Skipmatch
File type	.csv only. Excel workbooks (.xlsx, .xls) are not read.
File size	Up to 50 MB
Records per order	50 to 100,000, counted after exact duplicates are removed
Header row	Required: the first line names the columns
Separator	Comma, tab, pipe or semicolon
Required columns	An owner name, plus street, city, state and ZIP for the mailing or the property address

What the order flow cannot take

Excel workbooks. Save the sheet as CSV first. The upload refuses any file that does not end in .csv.
Address-only lists. Skip tracing searches by the owner's name, so every order needs an owner name column and a list of addresses with no names stops at the name check. Find the owner of record first, from the county or your list source.
Parcel numbers on their own. An APN column is kept and returned in your result file, but it is not used to find anyone: each row needs a name and an address.
LLC, trust and estate rows, as a way to reach a person. They are accepted and counted, but the name on them is not a person's, and Skipmatch does not promise to find the people behind an entity. Trace the person first: how to skip trace an LLC-owned property.

Download a template

The sample input file is a ten-row owner list in the layout the checker reads best, with every record invented: no real owner, address or parcel. The blank template is the same header row with no records. Its columns are OwnerFirstName, OwnerLastName, MailingAddress, MailingCity, MailingState, MailingZip, PropertyAddress, PropertyCity, PropertyState, PropertyZip, APN and Acres; APN and Acres are examples of your own columns, which come back unchanged.

Sample input (CSV)Blank template (CSV)

Why each column matters, how to split names and when to use the mailing or the property address are in how to format a CSV for skip tracing. What comes back is on the sample file page, the steps after upload are in how it works, and prices are on the pricing page.

CSV checker questions

What format does a skip trace file need to be in?

For Skipmatch, a .csv file with a header row that names the columns and one owner per row. Commas, tabs, pipes or semicolons all work as separators; save as CSV UTF-8 so accented names come through intact. Your column names do not have to match ours; the mapping step reads them.

What columns are required?

An owner name, either first and last name in two columns or the whole name in one column, and one complete address block: street, city, state and ZIP for the mailing address or the property address. The address can be in four columns or in one ("123 Main St, Atlanta, GA 30301"), which is split for you. Every other column is optional and comes back in your result file unchanged.

My addresses are all in one column. Do I have to split them?

No. If most of a column's cells read like a whole address, with a street, a city, a state and a 5-digit ZIP, the checker and the order flow split it into street, city, state and ZIP for you, and the checker downloads the split file. A row that will not split, such as one with no ZIP, is left out of the order and not charged for, instead of being sent with a guessed address. You can fix those rows by hand and add them to a later order.

Can I upload an Excel file?

No. Skipmatch reads .csv files only, and the upload refuses .xlsx, .xls and other spreadsheet files. In Excel choose File, Save As, CSV; in Google Sheets choose File, Download, Comma-separated values. Then run the saved file through the checker.

Do I need the owner's name?

Yes. Skip tracing searches by the owner's name, so an order cannot go ahead without a name column and an address-only list cannot be run as it is. Rows whose name cell is empty are still counted as records, and so are rows named for an LLC, trust or estate, so fix or remove them before you order.

How many rows can a file have?

One order takes 50 to 100,000 records, counted after exact duplicates are removed, in a file of up to 50 MB. A bigger list splits into more than one order.

Does the checker predict my match rate?

No. It checks the shape of the file: which columns will be used, whether a name and a complete address are there, and how many rows are exact duplicates. It looks nobody up, so it cannot say how many records will come back with a phone or email.

Price your list before you pay for it.

Create an account, upload the file, and see your total before you pay. Records with no phone and no email are never charged.

Price your list