spelling correction Customer Data Cleanup
Budget / SalaryHourly project
TypeFreelance project
LocationRemote
Posted2 hours ago
I have a single Excel workbook filled with customer and contact details that has become messy over time. Before I can use it for marketing and reporting, it needs a thorough cleanup—specifically removing every duplicate entry and filling-in or clearly flagging any missing information. Once the file is fully organised, I should be able to filter, sort, and hand it off to my CRM with confidence.
Here’s what I’m expecting from you:
• A copy of the workbook that is deduplicated (no repeated names, emails, phone numbers, or customer IDs).
• All blank or inconsistent fields either completed from the data you find elsewhere in the sheet or highlighted for my review.
• Consistent formatting for dates, phone numbers, and email addresses so everything lines up cleanly.
• A brief change log or notes tab that explains what was fixed and any assumptions you had to make.
If you prefer Power Query, advanced filtering, or VBA to speed things up, I’m open to whichever Excel tools you find most efficient—just keep the final file macro-free unless we agree otherwise. Accuracy is more important than speed, so take the time you need to be sure the dataset is rock-solid before you return it.
Here’s what I’m expecting from you:
• A copy of the workbook that is deduplicated (no repeated names, emails, phone numbers, or customer IDs).
• All blank or inconsistent fields either completed from the data you find elsewhere in the sheet or highlighted for my review.
• Consistent formatting for dates, phone numbers, and email addresses so everything lines up cleanly.
• A brief change log or notes tab that explains what was fixed and any assumptions you had to make.
If you prefer Power Query, advanced filtering, or VBA to speed things up, I’m open to whichever Excel tools you find most efficient—just keep the final file macro-free unless we agree otherwise. Accuracy is more important than speed, so take the time you need to be sure the dataset is rock-solid before you return it.
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