How to count days between dates within your Amazon Seller Central data
Lean how to count days between dates within your Amazon Seller Central data — and gain valuable business insights — with Parabola.
Adam Reisfield
How to use Amazon Seller Central with Parabola
Parabola seamlessly integrates with Amazon Seller Central to transform your e-commerce data analysis into an automated, efficient process.
- Eliminate manual data extraction and calculation processes
- Create automated workflows that update in real-time
- Customize date calculations based on your specific business needs
- Generate consistent, error-free results
- Share insights across your organization effortlessly
Retrieving data from Amazon Seller Central
Parabola's integration with Amazon Seller Central allows users to pull various types of reports directly from their seller account. This secure connection enables automatic data retrieval and updates, ensuring you're always working with the most current information.
Key features
- Automated data extraction from multiple report types
- Secure API authentication
- Customizable date ranges for data retrieval
- Real-time data synchronization
- Support for multiple marketplace regions
How to use
- Navigate to the Pull from Amazon Seller Central step in your Flow
- Authenticate your Amazon Seller Central account
- Select the desired report type and date range
- Configure any additional parameters
- Run the step to import your data
How to compare dates with Parabola
Once your Amazon Seller Central data is imported, you can use the Compare dates step to calculate the time difference between any two date fields. This feature allows you to perform complex date calculations without writing any code.
Key features
- Flexible date format support
- Multiple time unit options (days, months, years)
- Custom output formatting
- Batch processing capabilities
- Error handling for invalid dates
How to use
- Add the Compare dates step to your Flow
- Select your input columns containing the dates or compare a column against the current date/time
- Choose your preferred output time unit
- Name the newly created column with the different calculation
- Run the step to calculate date differences
Practical use cases and examples
Inventory aging analysis
Calculate the age of each product in your inventory by comparing the initial stocking date to the current date. This helps identify slow-moving items and optimize inventory management strategies.
Order fulfillment performance
Track the time between order placement and delivery to monitor shipping efficiency. This data can help identify bottlenecks in your fulfillment process and improve customer satisfaction.
Seasonal trend analysis
Measure the duration between peak sales periods to better understand seasonal patterns and prepare inventory levels accordingly. This information is crucial for strategic planning and forecasting.
By combining Amazon Seller Central data with Parabola's date calculation capabilities, you can automate these analyses and make data-driven decisions to optimize your e-commerce operations.
Start building Flows today to unlock valuable insights from your Amazon selling data.
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Pull from Amazon Seller Central
Compare dates
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What is Amazon Seller Central?
Amazon Seller Central is a platform that enables merchants to sell products on Amazon. It serves as the central hub for managing inventory, orders, pricing, and analyzing various performance metrics. Its portal provides sellers with the tools and reports needed to run their Amazon business effectively.
Why would you want to count days between dates in Amazon Seller Central?
Understanding the time intervals between different dates in your Amazon Seller Central data can provide valuable insights for your business operations and decision-making processes.
Here are some things you might want to do that would require counting days between dates:
- Track inventory turnover rates by calculating days between restocking events
- Monitor shipping performance by analyzing delivery timeframes
- Calculate product age in inventory to optimize storage costs
- Evaluate seasonal trends by measuring time between peak sales periods
- Assess customer behavior patterns through purchase frequency analysis
