Data Extraction

How to Leverage Data Extraction for Shipping Labels: Tips for Efficiency & Accuracy

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How to Leverage Data Extraction for Shipping Labels: Tips for Efficiency & Accuracy

As the global data extraction market is projected to hit $4.90 billion by 2027, the spotlight is on optimising logistics. Inefficient and inaccurate data extraction from shipping labels is the core of many logistical headaches. It can tarnish brand reputation, increase costs from reshipping, and decrease customer loyalty. 

This article talks about the impact of precise and efficient data extraction on your business. Expect to uncover actionable insights and practical techniques to refine your approach to data extraction shipping labels. 

What is a shipping label?

A shipping label might seem like just a piece of paper, but it's a crucial tool in the shipping process. Think of it as the package's ID card. It tells where the package came from, where it's going, and how it should get there. 

Some essential details available on a Shipping Label are:

  • Sender and recipient information includes the names and addresses of the person sending the package and the person getting it. It's like the "To" and "From" on a traditional letter but for packages.
  • Package weight: This helps determine how much the shipping will cost and ensures the package is handled correctly.
  • Tracking number: This is super important. It's like a unique ID for your package. You can use this number to check where your package is and when it will arrive.
  • Barcodes: Machines use barcodes to automatically sort and track packages, speeding up the delivery process and reducing errors.

Everyone in the delivery chain uses shipping labels, including postal services, courier companies, and e-commerce. They help ensure your package gets to the right place without any mix-ups.

Key data points in shipping labels for extraction

Shipping labels carry essential information, and understanding their key data points is critical to any logistics automation solution

Here's a rundown of them and why they're crucial:

  • Sender and recipient information: This includes names, addresses, and sometimes contact information. It's crucial for routing the package correctly and ensuring it reaches the intended recipient. Logistics operations use this information to plan delivery routes and schedules.
  • Tracking number: This unique code allows the sender and recipient to follow the package's journey. Logistics companies need tracking numbers. They use them to update delivery statuses and handle customer inquiries. It resolves issues with lost or delayed shipments.
  • Package weight and dimensions: These details determine shipping costs and help plan transport. They ensure that vehicles are loaded efficiently and safely. In inventory management, knowing package size helps. It lets you use storage space better and plan for future inventory needs.
  • Postal barcode: This machine-readable barcode speeds up the sorting and routing process, reducing human error and increasing efficiency. It's especially crucial during peak shipping times when the volume of packages can overwhelm manual sorting processes.
  • Shipping class/service: This indicates the speed or type of service paid for (e.g., overnight, standard, ground). Logistics companies need to prioritise and schedule deliveries based on service level. This will help meet customer expectations and contractual obligations.
  • Package contents description: This information is only sometimes public due to privacy and security. However, dealing with regulations, customs, and inventory is crucial. Knowing what's inside can affect how the package is handled, especially if it contains fragile, hazardous, or perishable items.

The significance of efficient data extraction in logistics

Efficient data extraction from shipping labels is not just about moving packages faster but about smarter and more informed operations. Here's why it's so important:

  • Enhances tracking accuracy: Fast, accurate label data extraction allows real-time package tracking, keeping everyone, from warehouse staff to the end customer, in the loop.
  • Streamlines logistics operations: Efficient data extraction helps organise and manage the flow of goods. This means less time is spent on manual data entry and more time on getting packages where they need to go.
  • Improves customer satisfaction: Customers love knowing where their packages are and when they'll arrive. Accurate data extraction leads to better tracking updates and fewer lost or delayed shipments. It makes for happy customers.
  • Reduces operational costs: Efficient data extraction saves a lot of time. It also means fewer errors, which can be costly to fix. Lower operational costs can then be passed on to customers or reinvested in the business.
  • Scalability and flexibility: As a business grows, its logistics needs change. Efficient data extraction allows for scalability and flexibility in the supply chain, making it easier to adjust to new demands without skipping a beat.

Common challenges in extracting data from shipping labels

Several challenges can complicate the data extraction shipping labels process. Here are some of them:

  • Varied label formats and designs: Shipping labels differ significantly across carriers and regions, presenting a challenge for standardised data extraction. The lack of uniformity can lead to errors and inefficiencies in processing.
  • Poor print quality and label damage: Labels may become illegible due to poor printing quality or physical damage during transit. This results in the loss of critical information, complicating tracking and delivery efforts.
  • Complex information and symbols: Shipping labels contain dense information and symbols. Each is critical for handling and routing packages. Misinterpretation or misreading of this data can lead to significant operational disruptions.
  • Environmental factors: External conditions such as exposure to weather, dirt, and handling can degrade label integrity. This environmental impact can render data unreadable, leading to processing delays and increased error rates.

Preparing shipping labels for effective data extraction

Preparation ensures that data extraction shipping label processes are efficient and error-free. Here's a checklist to ensure your shipping labels are ready for effective data extraction:

  • Standardize label formats: Adopt a uniform format for all your shipping labels. This consistency helps automated systems quickly recognise and extract data, reduce errors, and speed up processing. Consider adopting industry standards or creating a company-specific template that meets all logistical requirements. Proper document pre-processing can significantly enhance this step.
  • Ensure high print quality: Clear, legible print is essential for accurate data extraction. Use high-quality printers and check that all text and barcodes are sharp and easily readable. Regular maintenance of printing equipment can prevent ink smudging or fading issues.
  • Implement quality control measures: Establish a system for checking the quality of printed shipping labels. This could include manual checks or automated scanning to detect and correct errors before packages leave the facility.
  • Train staff on best practices: Educate your team on the importance of accurate shipping label information and proper label placement. Training should cover handling and applying labels to avoid damage or misplacement. It will ensure that labels are readable throughout the shipping process.

Best practices for managing extracted data from shipping labels

Data extracted from shipping labels must be managed effectively for logistics operations to remain efficient and effective. Here are some strategies to ensure that the extracted data serves your business well:

  • Validate and verify data: Proper document analysis ensures data quality and reliability. Implement checks to ensure the data extracted from shipping labels is accurate and complete. This might involve cross-referencing information with existing records or software detecting anomalies or inconsistencies.
  • Secure storage: Consider implementing a robust data export system to facilitate secure and efficient data handling. Also, use encrypted databases and ensure only authorised personnel can access this information. This helps prevent data breaches and maintains the privacy and security of business and customer information.
  • Regular audits: Conduct periodic audits of the extracted data to ensure its accuracy and integrity. This can help identify any issues or discrepancies early on and prevent them from affecting logistics operations.
  • Integration with logistics software: Seamlessly integrate the extracted data with your existing logistics systems and databases. This ensures that all parts of your supply chain use up-to-date and accurate information, leading to more coordinated and efficient operations.

Conclusion: Enhancing supply chain efficiency through data extraction

Standardising label formats and ensuring high print quality can greatly improve shipping operations. It increases their accuracy and efficiency. Moreover, integrating this data with logistics software amplifies these benefits. Even so, realising these benefits requires the right tools and technologies. In this context, Docsumo takes centre stage.

Docsumo's platform offers an intelligent data extraction solution for shipping labels. It enables businesses to automate and optimise their data-handling processes. Start using Docsumo for efficient shipping label data extraction.


Q1. Is it possible to automate the extraction of data from handwritten shipping labels?

Advanced OCR and AI can automate data extraction from handwritten shipping labels. These tools are designed to recognise and interpret various handwriting styles. However, the accuracy can vary based on the legibility of the handwriting and the sophistication of the technology used.

Q2. What technologies best extract data from complex shipping labels with multiple barcodes and information fields?

The best technologies for extracting data from complex shipping labels include OCR for text recognition, AI for understanding context, and machine learning for improving accuracy over time. Additionally, barcode scanners and image processing are crucial. They decode multiple barcodes and sort through many fields well.

Q3. How do I handle data discrepancies from shipping labels found during extraction?

Data errors during data extraction for shipping labels must be verified using a verification system. This could involve staff manual checks, cross-referencing with existing databases, or using software that flags inconsistencies for review. Addressing discrepancies promptly ensures the data's reliability and maintains the logistics process's integrity.

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Written by
Sourav Mohanty

Product marketing enthusiast by day, guitarist by night - that's Sourav in a nutshell. With over 4.5 years of experience helping B2B and B2C startups shine, they've got the marketing mojo to make even the most complex products sound like the best thing since sliced bread. If you're looking for someone who can make data-driven decisions while keeping things fresh and funky, then you are at the right place

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