How to Compare Supplier Quotes Fast: Extract PDF & Image Data into Excel

If you run a small business or manage procurement, you know the drill: three suppliers send their quotes as PDFs, one sends a photo of a printed sheet, and now you have to compare them. Manually copying prices, part numbers, and delivery terms into a spreadsheet takes the better part of an afternoon — and one mistyped figure can cost you real money.

This guide walks you through a faster way: extracting the data directly from those documents and images, then building a structured comparison table in Excel with minimal effort.

Step 1 — Collect All Quotes in One Place

Before you extract anything, get organized. Download or save every supplier quote — PDFs, scanned images, email screenshots — into a single folder. This small habit pays off immediately when you process them in bulk later.

• Rename files clearly: supplier-a-quote-june.pdf, supplier-b-quote-june.jpg, etc.
• Check that scanned PDFs are readable (not password-protected or blurred).
• Note whether each file is a native digital PDF or a scanned/photographed document — both are handled differently by extraction tools.

Step 2 — Extract the Data Without Manual Typing

This is where most of the time is saved. Instead of opening each file and copying figures by hand, use an automated extraction tool that reads the document and outputs structured rows and columns.

Tablola's PDF to Excel converter preset is built exactly for this. Upload your quote PDFs and the tool pulls line items — product codes, descriptions, unit prices, quantities, totals — straight into a spreadsheet. For photos or scanned documents, the scanned PDF to Excel preset applies OCR to read the content even when the source isn't a clean digital file.

• Upload multiple files at once to save time.
• Review the extracted rows quickly — AI extraction is accurate but a 30-second scan catches edge cases like merged cells or unusual table layouts.
• If a supplier sent a photo from their phone, the image to Excel converter handles JPG and PNG files the same way.

Step 3 — Standardize the Column Structure

Every supplier formats their quote differently. Supplier A calls it "Unit Price (USD)"; Supplier B writes "Price/Item"; Supplier C uses a different currency symbol. Before you can compare, you need a single unified table structure.

Set up a master sheet with columns that make sense for your business:

1. Item / Part Number
2. Description
3. Qty
4. Unit Price
5. Total Price
6. Lead Time
7. Supplier Name

Paste each supplier's extracted data into this master sheet, adding a "Supplier Name" tag to each row. If the column names differ slightly, use Tablola's AI editing features to rename or remap them in seconds — no formulas needed.

Step 4 — Build the Side-by-Side Comparison

With all quotes in a single structured table, comparison becomes straightforward. Create a pivot view or a summary sheet that groups rows by item and places each supplier's price in a separate column.

• Use conditional formatting to highlight the lowest price per line item in green — this makes the winning quote obvious at a glance.
• Add a "Price Difference %" column to quantify savings: =(SupplierA - SupplierB) / SupplierA.
• Don't forget lead times. Sometimes the cheapest supplier is two weeks slower — a factor worth surfacing in the same table.

If your team regularly compares purchase orders from multiple vendors, the purchase order to Excel preset automates the initial extraction step for that document type specifically, saving even more setup time.

Step 5 — Share and Decide

A clean Excel comparison table is easy to share with a manager, finance team, or business partner. Export as .xlsx or .csv and attach it to the approval email. Everyone sees the same numbers, in the same format, with no ambiguity.

• Lock the extraction columns to prevent accidental edits to the source data.
• Add a "Decision" column at the end where reviewers can mark their preferred supplier per line item.
• Save the template for next quarter — the structure rarely changes, only the data does.

Practical tip: If you receive quotes on a recurring basis (monthly restocking, seasonal purchasing), save the extraction preset as a workflow in Tablola. Next time, you drop in the new files and the structured table is ready in under a minute — no reformatting, no re-mapping columns from scratch.