How to parse useful fields from an email
Emails often combine a reference number, dates, contact details and explanatory prose. Parsing turns those repeated details into structured fields so they can be reviewed or copied into an administrative workflow.
Start with the right material.
- What you provide
- one opened email with all relevant text expanded.
- The intended result
- Extract user-specified fields into a single structured record with missing values flagged.
How the workflow works.
Provide the message and identify the fields that matter. Separate the sender's wording from quoted history, and keep the original labels beside ambiguous dates or amounts until their meaning is clear.
What to check in the result.
Check every extracted reference against the message. A number in an example or signature is not automatically the order number, and an omitted field should never be filled from guesswork.
Import the CSV with a consistent delimiter and inspect text identifiers, dates and amounts before using spreadsheet totals. Keep the original file available while checking any automatic type conversion.
Learn from the worked example.
The downloadable CSV example uses these columns: Order ID, Amount, Currency, Delivery date. Compare a complete record with the source before sorting, combining or importing your own output.
The supplied example is illustrative. It is not a recorded run on your data.
Download the example ↓Use it with your own material.
- Open the source you want to work with and activate WebAct on that tab.
- Copy the task from the hero, add any required fields or preferences, and review the proposed actions.
- Compare the first result with your source. Ask for a specific correction or refinement where needed.