10 Types of Documents Businesses Should Extract Data From

Every business receives and produces large numbers of documents: invoices, receipts, purchase orders, reports, and many others. These documents contain important information such as dates, prices, product details, and transaction records.

However, when documents remain in PDF or image format, the data inside them is difficult to analyze or reuse.

By extracting the information from these documents and organizing it in Excel, companies can turn static files into structured data that can be searched, filtered, and analyzed.

In this article, we look at the most common types of documents that businesses should extract data from.

1. Supplier Invoices

Invoices are one of the most important documents for any company. They contain key information such as supplier name, invoice number, date, product details, quantities, prices, and VAT totals.

Extracting invoice data allows businesses to track spending, analyze supplier relationships, and simplify accounting workflows.

2. Expense Receipts

Expense receipts are commonly used for employee reimbursements and expense tracking. Typical receipts contain information such as merchant name, transaction date, purchased items, tax values, and the total amount.

Extracting receipt data into Excel allows finance teams to track expenses more easily and prepare expense reports faster.

3. Purchase Orders

Purchase orders contain detailed information about planned purchases from suppliers. Key fields include supplier name, ordered products, quantities, agreed prices, and delivery dates.

Extracting this information into Excel allows procurement teams to monitor supplier orders and track purchasing activity.

4. Bank Statements

Bank statements contain a complete record of financial transactions. Typical data includes transaction dates, payment descriptions, debit/credit amounts, and account balances.

Extracting bank statement data into Excel makes it easier to reconcile payments and analyze cash flow.

5. Financial Reports

Companies often receive financial documents such as quarterly reports, budget reports, and expense summaries. These documents frequently contain tables that must be analyzed in spreadsheets.

Extracting the data automatically allows analysts to work with financial data immediately without manual copying.

6. Product Catalogs

Suppliers sometimes provide product catalogs in PDF format. These catalogs may include product names, codes, descriptions, and prices.

By extracting this information into Excel, businesses can build product databases and compare supplier pricing.

7. Delivery Notes

Delivery notes confirm that products have been shipped or delivered. They usually contain product names, quantities delivered, delivery dates, and order references.

Extracting delivery data helps operations teams track shipments and verify supplier deliveries.

8. Contracts

Contracts often contain structured information such as contract numbers, parties involved, dates, and payment terms.

Extracting key fields from contracts can help businesses manage agreements and track obligations.

9. Inventory Reports

Inventory documents may include tables listing product names, quantities in stock, and warehouse locations.

Extracting this data into Excel allows companies to monitor inventory levels and manage stock more efficiently.

10. Shipping Documents

Logistics teams often handle shipping documents containing shipment numbers, destinations, product quantities, and shipping costs.

Extracting this information makes it easier to analyze logistics performance and shipping expenses.

Automate Document Data Extraction

Tools like IntoExcel allow businesses to extract data from many types of documents automatically.

With IntoExcel you can:

upload PDFs, images, or scanned documents
select the fields to extract
generate structured Excel files instantly

IntoExcel can also extract line items, meaning each product or item from a document can appear as its own row in Excel. This makes the data immediately usable for accounting, analysis, and reporting.

Try IntoExcel

If your team regularly works with documents containing valuable data, automating extraction can save a significant amount of time.

👉 Try intoExcel

Upload your document and receive a structured Excel file in seconds. You can begin with free extractions to test the system.

Final Thoughts

Many business documents contain important data that remains difficult to analyze when stored as PDFs. By extracting this information into Excel, companies can transform static documents into structured datasets that support better decision-making.

With modern AI tools, extracting data from documents is now fast, accurate, and scalable.