How to Extract Data from Images into Excel: A Step-by-Step Guide

Every week, countless hours are lost retyping numbers from photos of receipts, screenshots of tables, or scanned reports into Excel. Whether you work in finance, logistics, procurement, or operations, the problem is the same: the data is trapped inside an image, and copy-paste simply does not work. This guide walks you through exactly how to break that barrier—quickly and accurately.

Short answer: The fastest way to extract data from images into Excel is to use an AI-powered tool that reads the visual content, identifies the table structure, and exports it as a properly formatted spreadsheet. Tools with ready-made presets—such as those for receipts, invoices, or bank statements—cut setup time to near zero.

Why Manual Retyping Is Costing You More Than You Think

Manual data entry from images is not just slow—it introduces errors that compound downstream. A single transposed digit in an invoice amount or a missed row in a purchase order can trigger hours of reconciliation work. Studies on data entry error rates consistently put human accuracy at around 96–99%, which sounds high until you consider that a 1% error rate across 500 rows means 5 wrong cells per sheet.

Beyond accuracy, there is the simple opportunity cost. Time spent retyping is time not spent on analysis, decisions, or higher-value tasks. Automating image-to-Excel extraction eliminates both problems at once.

What Types of Images Can Be Converted to Excel?

Modern AI extraction tools handle a surprisingly wide range of image sources:

• Photos of printed documents – receipts, delivery notes, purchase orders taken with a smartphone camera
• Screenshots – tables copied from web pages, dashboards, or desktop applications
• Scanned PDFs – documents where the text layer is an image, not selectable text
• Exported report images – PNG or JPG exports from legacy ERP or accounting systems
• Handwritten tables – structured handwritten data (accuracy varies by legibility)

The key requirement is that the data should have a recognisable table structure—rows, columns, and headers. Unstructured free-form text is harder to map into a spreadsheet automatically.

Step-by-Step: Extracting Image Data into Excel with Tablola

Step 1 – Choose the Right Preset

Rather than configuring an extraction from scratch, start with a preset that matches your document type. Tablola offers ready-made presets for the most common use cases. For photos of receipts, the Receipt Photos to Excel preset pre-configures the field mapping—vendor, date, amount, tax—so you do not have to define them manually. For delivery notes, the Delivery Note to Excel preset handles line items, quantities, and unit prices out of the box.

Step 2 – Upload Your Image or Batch of Images

Drag and drop a single image or upload multiple files at once. Tablola processes JPG, PNG, and PDF image files. If you have a folder of scanned documents, bulk upload saves significant time compared to processing files one by one.

Step 3 – Review the AI Extraction Preview

The AI analyses the image, detects the table structure, and presents a preview of the extracted data before you download anything. This is the moment to spot any misread cells—unusual fonts, low-contrast scans, or rotated images occasionally trip up even good OCR engines. Make inline corrections directly in the preview grid if needed.

Step 4 – Export to Excel or CSV

Once the preview looks correct, export to .xlsx or .csv. The Image to Excel Converter preset produces a clean, column-aligned spreadsheet ready for further analysis. If you need CSV for import into another system, the PDF to CSV Converter preset works the same way for PDF-based image sources.

Step 5 – Use AI Table Editing for Post-Extraction Clean-Up

Raw extractions sometimes need light clean-up: removing a header row that got duplicated, standardising date formats, or merging multiple image exports into one master table. Tablola's AI table editor lets you describe the change in plain language—"merge all sheets and sort by date descending"—and applies it without requiring formula knowledge. For combining output from multiple documents, the Merge Multiple Documents into One Table preset automates the consolidation step entirely.

Tips for Better Extraction Accuracy

• Shoot straight: Capture photos as flat and perpendicular to the document as possible. Perspective distortion is the single biggest source of OCR errors on phone photos.
• Use good lighting: Even, diffuse light reduces shadows that obscure digits. Avoid flash directly on glossy paper.
• Scan at 300 DPI or higher: For scanned documents, 300 DPI is the practical minimum for reliable character recognition.
• Crop tightly: Remove excessive white space or background clutter before uploading. It helps the AI focus on the actual table region.
• Match the preset to the document type: Using the correct preset improves field mapping accuracy because the model already knows what columns to expect.

Common Use Cases by Industry

Image-to-Excel extraction solves real problems across many functions:

1. Accounts payable: Processing stacks of supplier invoices photographed by field staff or received as image-only PDFs.
2. Logistics: Digitising delivery notes and goods-received notes from warehouse photos.
3. Expense management: Converting receipt photos into itemised expense reports automatically.
4. Procurement: Extracting line items from purchase order images for spend analysis.
5. Research & compliance: Pulling tabular data from scanned regulatory filings or historical paper records.

Frequently Asked Questions

What image formats does Tablola support for extraction?

Tablola accepts JPG, PNG, and PDF files (including scanned PDFs where the content is image-based rather than text-based). You can upload individual files or batches. For scanned PDFs specifically, the Scanned PDF to Excel Converter preset is optimised for documents that lack a selectable text layer.

How accurate is AI-based image-to-Excel extraction?

Accuracy depends primarily on image quality. Clean, well-lit, high-resolution images of printed documents typically achieve very high accuracy—often 98% or above at the cell level. Low-quality phone photos or heavily compressed images will produce more errors. The built-in preview step exists precisely so you can catch and fix any mistakes before the data reaches your spreadsheet.

Can I process many images at once instead of one at a time?

Yes. Tablola supports batch processing, and the Merge Multiple Documents into One Table preset is specifically designed to combine the extracted data from many source files into a single consolidated Excel output—useful when you have a month's worth of receipts or invoices to process in one go.