Ground Rent Data Extraction
Budget / Salary$30–250
TypeFreelance project
LocationRemote
Posted1 hour ago
I have 1,663 individual property information files available through a public website. For every case I need you to:
• download the document, save a local copy using the file-naming convention I’ll share,
• open that document and locate the Ground Rent owner section,
• capture the owner’s full name, current mailing address, and any contact details that appear (phone or email),
• record each field in the Excel template I will provide.
The site is straightforward—one PDF per property—but the wording and placement of the Ground Rent details can vary slightly, so a careful eye is essential. Accuracy is more important than speed; I will spot-check against the original PDFs before sign-off.
Deliverables
1. Folder containing all 1,663 downloaded PDFs, correctly named.
2. Completed Excel sheet with the three data columns populated for every case.
Acceptance criteria
• 100 % of cases accounted for in both the folder and the spreadsheet.
• Data in the spreadsheet must match the text found in each PDF without transcription errors.
• File names follow the agreed format exactly so the documents can be auto-linked later.
Please be comfortable working with large batches of property documents and Excel. If you have any questions about the workflow or need a sample file before starting, let me know and I’ll provide one.
• download the document, save a local copy using the file-naming convention I’ll share,
• open that document and locate the Ground Rent owner section,
• capture the owner’s full name, current mailing address, and any contact details that appear (phone or email),
• record each field in the Excel template I will provide.
The site is straightforward—one PDF per property—but the wording and placement of the Ground Rent details can vary slightly, so a careful eye is essential. Accuracy is more important than speed; I will spot-check against the original PDFs before sign-off.
Deliverables
1. Folder containing all 1,663 downloaded PDFs, correctly named.
2. Completed Excel sheet with the three data columns populated for every case.
Acceptance criteria
• 100 % of cases accounted for in both the folder and the spreadsheet.
• Data in the spreadsheet must match the text found in each PDF without transcription errors.
• File names follow the agreed format exactly so the documents can be auto-linked later.
Please be comfortable working with large batches of property documents and Excel. If you have any questions about the workflow or need a sample file before starting, let me know and I’ll provide one.
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