Update Product Sales Customer Data
Budget: ₹100 – ₹400 INR
I have an existing product-sales database that now contains outdated and incomplete customer information. I need a detail-oriented data specialist to review the records and bring everything up to date. The job centres on three specific areas:
• Contact details – verify names, phone numbers, email addresses and physical addresses
• Purchase history – reconcile past orders, dates, quantities and values so the timeline is accurate
• Demographic information – fill in or correct age range, location and other profile fields I already track
All source files will be provided in spreadsheet/CSV format pulled from my CRM. Your task is to cross-check each entry against the latest source data I share, correct inconsistencies, and return a single, clean file ready for import back into the system.
Accuracy is critical; before sign-off I will run random spot-checks and a pivot summary to confirm that totals and counts align with the raw exports. Please outline your relevant experience with Excel, Google Sheets or similar tools and let me know how quickly you could turn around the first draft once you receive the files.
• Contact details – verify names, phone numbers, email addresses and physical addresses
• Purchase history – reconcile past orders, dates, quantities and values so the timeline is accurate
• Demographic information – fill in or correct age range, location and other profile fields I already track
All source files will be provided in spreadsheet/CSV format pulled from my CRM. Your task is to cross-check each entry against the latest source data I share, correct inconsistencies, and return a single, clean file ready for import back into the system.
Accuracy is critical; before sign-off I will run random spot-checks and a pivot summary to confirm that totals and counts align with the raw exports. Please outline your relevant experience with Excel, Google Sheets or similar tools and let me know how quickly you could turn around the first draft once you receive the files.
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Data Processing
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Data Cleansing
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Data Management