Free template: combine Amazon Seller Central data with Excel data
Combine Amazon Seller Central data with Excel data without writing a single line of code.
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Sign up for freeTransform your data in five easy steps using Parabola's drag-and-drop interface, powered by AI.
- Set up your data sources by creating a new Parabola flow, connecting your Amazon Seller Central account, and uploading your Excel file. This creates the base for your automated workflow.
- Configure your Amazon Seller Central pull by selecting your required data types, such as orders, inventory, or sales metrics. Set any necessary filters or date ranges.
- Prepare your Excel data by ensuring your spreadsheet is properly formatted and contains all necessary information. This step is crucial for accurate data mapping.
- Combine your datasets using Parabola's transformation tools. This step allows you to match corresponding fields and create rules for how your marketplace and spreadsheet data should merge.
- Generate your results by previewing the combined data and running your automated flow. The process will run automatically for future updates once configured.
See Parabola in actionPractical workflow automation use cases and examples
Inventory management
Merge Amazon’s current inventory levels with supplier lead times stored in Excel to create automated reorder point calculations and prevent stockouts while maintaining optimal inventory levels.
Profit margin analysis
Combine Amazon sales data with cost information stored in Excel to automatically calculate accurate profit margins and identify your most profitable products and categories.
Customer behavior tracking
Match customer purchase history from Amazon with customer segments defined in Excel to create targeted marketing campaigns and improve customer retention strategies.
By automating the combination of Amazon Seller Central and Excel data in Parabola, businesses can save countless hours of manual data processing while gaining deeper insights into their operations. This integration empowers companies to make data-driven decisions with confidence and scale their operations efficiently.
