Set Up Tracking and Carrier Fields for Shipping Labels
Configure shipping label fields in the dashboard — capture tracking numbers, carrier service levels, and addresses from label images.
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What this guide helps you do
This guide shows how to configure a shipping label parser in PerfectParser, define tracking and address fields, run a test batch, and export parcel data. Leave the prompt blank on the first pass if you want auto-detect to find every label element before refining field names.
Why shipping labels are hard to parse
Shipping labels pack tracking numbers, barcodes, addresses, and service class into a dense thermal-print layout with little whitespace. The human-readable tracking number and the barcode-encoded value are not always identical — some carriers prepend routing digits in the barcode. Sender and recipient blocks use abbreviated address formats optimized for sortation, not readability. Service type ("Ground", "2Day", "Priority Mail") appears in small type near the carrier logo. Photos taken at an angle or under warehouse lighting introduce glare that obscures zip codes. Multi-package shipments may print a master label plus child labels with different tracking numbers. A schema tuned on FedEx labels will misplace fields on USPS formats unless you test with carrier-specific samples.
Recommended Fields
We suggest configuring the following schema fields for your Shipping Label Parser to capture all essential tracking and logistics details.
| Field Name | Type | Description |
|---|---|---|
tracking_number | Text | The unique carrier tracking number (e.g. UPS, FedEx, DHL tracking ID). |
carrier | Text | The courier or shipping company (e.g., FedEx, UPS, DHL). |
sender_name | Text | The name and address of the shipper. |
recipient_name | Text | The name of the package recipient. |
recipient_address | Text | The full destination address, including street, city, state, and zip code. |
package_weight | Text | The package weight listed on the label. |
service_type | Text | The courier service level (e.g. Ground, Next Day Air, Priority Mail). |
AI Prompt (Optional)
Use this only when you want to guide auto-detect toward a specific set of fields.
If you want PerfectParser to discover additional fields on its own, leave the AI Prompt (Optional) box blank for the first pass, review the detected schema, then add a prompt only if you need tighter consistency.
When you do use a prompt, copy and paste the following instructions into the AI Prompt (Optional) field during setup:
Set up this parser in the dashboard
Create a parser
Go to Parsers → New Parser in the dashboard. Give it a name like "Shipping Label Parser" and optionally select the document category.
Upload a sample document
Drag and drop a representative shipping label (PDF, PNG, or JPEG). Use a label image at the resolution and angle typical of your warehouse or intake process.
Detect fields or use standard fields
Paste the AI Prompt from the section above into the AI Prompt (Optional) box if you want tighter field mapping, then click Auto-Detect. To discover more fields automatically, leave the prompt blank and click Auto-Detect. Or skip auto-detect and add fields manually using the Recommended Fields table above.
Review and save your schema
Check that tracking_number captures the printed number, not the carrier logo or routing code. Confirm recipient_address includes city, state, and postal code. Click Save.
Run a test batch
Navigate to Bulk Extraction, choose how your files are organised, upload a small test set of label images, and click Extract All Files. Review the results in Batch History and export to CSV or Excel.
Common mistakes
- Confusing barcode data with the human-readable tracking number when both appear on the label.
- Using a high-resolution PDF label as the sample when production inputs are low-contrast thermal photos.
- Omitting service_type — it is easy to miss in small print but critical for freight charge validation.
- Merging sender and recipient into one address block when sortation workflows need them separate.
Next steps
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FAQs
Do I need a sample shipping label to set up this parser?
Yes. Upload a label from the carrier you process most often — UPS, FedEx, USPS, and DHL use different layouts. Thermal label photos should match the image quality you receive in production (warehouse scan vs phone photo).
Should I store the barcode value separately from the printed tracking number?
Define tracking_number as a Text field for the human-readable number on the label. If your workflow decodes barcodes separately, add a dedicated field rather than overloading tracking_number — barcode payloads sometimes include routing prefixes not shown in plain text.
How many credits does setup and a test extraction use?
Parser setup is free. Each label image or PDF costs 1 credit. Batch sortation workflows uploading hundreds of label photos should budget 1 credit per label.
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