With Hurdlr, you can link your banks and credit cards to automatically track your finances, however, there may be situations where you’re not able to automatically import transactions that you need, such as:
Your bank or credit card isn’t supported and can’t be linked in Hurdlr
You’d like to pull in transactions dating further back than your bank shares with third parties
You don’t want to link your bank/credit card and prefer to track transactions manually
In these cases, Hurdlr Premium/Pro allows you to upload a CSV file (spreadsheet) of your bank statement, credit card statement, or even transactions from an app that you used before Hurdlr.
Preparing your CSV for Import
To use this feature, you’ll first need to download the file from your bank or other app. If you have an option to choose the format, choose CSV. If you don't see that option, select any spreadsheet option available and resave it as a CSV file.
For best results, we recommend using one of the following date formats for the date field when uploading a CSV file into your Hurdlr account:
MM/DD/YYYY (ex: 01/02/2025 is January 2nd, 2025)
OR
MM/DD/YY (ex. 01/02/25 is January 2nd, 2025)
Linking your CSV Imported Transactions to a Bank Account
If you would like to tag the transactions in your file to a specific bank account or credit card, ensure that you have added that account as a Manually Tracked Account in Hurdlr. The next section will go over how to use that account during the CSV Import process.
Importing your CSV
Log into the web app on your computer at web.hurdlr.com/login
Click the gear icon in the top right corner
Select ‘Import Transactions'
Select an existing manual bank account/credit card or add a new account to associate with these transactions
Upload your CSV file by clicking ‘Add File’
Click ‘Next’ in the top right corner
For each field, use the drop-down to map your spreadsheet columns.
Date: Map the column with transaction dates.
Vendor: Map the column with vendor names (optional if using the ‘Description’ column).
Description: Map the column with transaction descriptions (optional if using the ‘Vendor’ column).
Amount:
For a single column showing both deposit (income) and withdrawal (expense) values, map it as is.
If deposits and withdrawals are in separate columns, select the ‘2 column’ checkbox, and map the respective columns for:
Amount (Out): Withdrawals
Amount (In): Deposits
Click ‘Next’ in the top right corner to see an overview of all transactions from your file.
If needed, deselect transactions you don’t want to import by unchecking the checkbox next to the transaction.
If the deposits/withdrawals were not mapped correctly, click ‘Reverse Amounts’ to correct them.
Click ‘Done’ to complete the import.
A banner will show when the CSV file is in-progress, failed, or complete. Click ‘OK’.
Once the import is complete, you can navigate to the Income/Expenses Dashboard (Premium) or Transaction Dashboard (Pro) to tag and categorize the imported transactions. To ensure your imported transactions are accurate, validate a small batch by pre-importing it. This helps identify issues like incorrect categorizations or mislabeling before processing a larger dataset. Note that any incorrect entries need to be manually deleted. If you encounter persistent import issues, review the formatting of your original CSV file. Re-download it from the source, and double-check the column mappings and signs to ensure they follow Hurdlr's requirements.
Troubleshooting Common Issues
Refund Misclassification: Ensure transactions have accurate positive or negative signs to denote income or expenses, respectively.
Formatting Errors: Re-download the CSV file and check that the necessary columns (e.g., date, description, amount) are correctly formatted.
Best Practices for Smooth Import
Check for Errors Early: Upload and test a smaller dataset initially to detect and fix any inconsistencies or incorrect mappings before importing the complete file.
Understand Column Mapping: Be aware that the "Category" column isn't used for transaction categorization; transaction types and classifications need to be mapped separately.