Turning Infographics into Editable Text: Step-by-Step

My Real Experience Converting Infographic Text into Usable Content

As a professional manager in a content-heavy agency, I often receive beautiful infographics from designers or clients. These images look great but are completely uneditable. A few years ago, our research team was working on a digital trends report, and the designer sent a detailed infographic packed with data. But when the client asked for the raw text to use in a blog post, there was no file—just the image. That’s when I started using OCR (Optical Character Recognition) to extract the text quickly and accurately. This method saved us from retyping hours of content and helped us reuse the infographic data in reports, newsletters, and blog posts

What Is OCR and Why It Works for Infographics

OCR is a smart tool that helps you convert text inside images—like infographics—into real, editable text. It’s the same technology used to scan documents or handwritten notes. When you apply OCR to an infographic, it reads the words and numbers inside that image and lets you copy, paste, and edit them in Word or Google Docs. Tools like Adobe Acrobat OCR, OnlineOCR.net, and Google Docs OCR do this well. OCR works especially great when the infographic has clear, bold fonts and high contrast

Extract Text from Visual Content Like Charts and Timelines

Infographics come in many forms—timelines, charts, diagrams, or side-by-side comparisons. One time, I needed to extract text from a whiskey pricing chart in an infographic. The chart showed bourbon prices ranging from $25 to $80, but OCR picked up $2500 instead of $25.00 because the font was too small. That’s why it’s important to double-check OCR results, especially for numbers. Based on Liquor.com’s bourbon pricing guide, average bourbon still costs under $60, so the OCR error was obvious—but only if you’re paying attention

Step-by-Step Process to Convert Infographic Text into Editable Format

If you’re new to this, don’t worry. Here’s the exact step-by-step process I’ve taught my content interns and fellow managers to extract text from infographic images:

Step 1: Save the Infographic

Download the infographic in high resolution. The clearer the image, the better the OCR result

Step 2: Use an OCR Tool

Upload your image to an OCR tool. My top 3 recommendations are:

  • Adobe Acrobat OCR for professional PDFs
  • Google Docs OCR for free, fast conversions
  • OnlineOCR.net for drag-and-drop image text extraction

Step 3: Review and Edit the Text

The OCR tool will scan and output editable text. Review it carefully. Fix spelling errors, formatting issues, and incorrect symbols

Step 4: Organize the Content

Separate the text into bullet points, headings, or paragraphs so it’s readable. I always paste the cleaned content into Google Docs first for easy sharing

Step 5: Save and Use

Now you can use the text in blog posts, reports, presentations, or as alt-text for accessibility

Table: Common Infographic Issues and How to Fix Them with OCR

Turning Infographics into Editable Text: Step-by-Step
ProblemOCR ChallengeHow to Fix
Small font sizeText missed or misreadZoom in or use high-res image
Curved or angled textOCR reads gibberishManually retype or crop that part
Background images behind textOCR skips itUse editing tool to remove background
Text inside graphsOCR jumbles wordsScreenshot only the text section
Incorrect prices or symbolsOCR misreads charactersAlways cross-check final output

We had a food infographic with ingredient prices, and OCR read “$4.99” as “$499.” That one decimal would’ve made a recipe post completely inaccurate! Tools are improving, but human review is still essential

Turn Infographic Data into Blog Posts and Reports

Infographic text is often rich with useful data, but it’s locked in image form. With OCR, you can unlock this content and reuse it in:

  • Blog summaries
  • Email newsletters
  • Client presentations
  • Internal training guides

I’ve used OCR to turn infographic text into 600-word blog posts for clients in education, tech, and finance. The visuals inspired the structure, and the extracted text gave us ready-made quotes and facts. It’s fast, efficient, and great for SEO when done right

Would you like me to continue with the second half? It includes:

  • How to keep formatting intact after text extraction
  • My advice from managing content teams who use this method
  • Final thoughts and tools comparison
  • A before-after table showing manual vs OCR text handling

How to Keep Formatting Intact After Text Extraction

Once the text is pulled out from the infographic using OCR, the next challenge is formatting it properly. Infographics are often filled with styled headings, subpoints, and sections. But OCR can scramble the layout, so you’ll need to organize it manually. Here’s how I train my content team to handle this part smoothly:

  1. Paste text into Google Docs or Word to see what you’re working with
  2. Break long lines into bullet points so the info stays easy to scan
  3. Use bold text for headers just like the infographic had
  4. Align numbers or data into tables if the original design used them
  5. Add clear spacing between sections for readability

One intern on my team used this method to recreate a fitness infographic as a blog post. With proper formatting, the post looked clean, and the SEO structure was clear—with headings, bullets, and embedded links that led to external references

Reuse Extracted Text for Social Media and SEO

Turning Infographics into Editable Text: Step-by-Step

Once the text is cleaned up, it’s more than just useful for internal documents. Our marketing team repurposes this content in:

  • Instagram captions from visual quotes
  • Twitter threads with data points
  • LinkedIn summaries for professional infographics
  • SEO-optimized blog intros

Let’s say an infographic says “Bourbon sales rose 12% in 2024.” You can use that stat in a blog, tweet it with a link to the source, or turn it into alt text for the original image. When used smartly, this extracted content helps you show up in search results and expands your reach

My Advice from Managing Content Teams That Use OCR

Over the years, I’ve seen how teams waste time retyping infographic text by hand, especially when under deadline. I now require all of our staff writers and designers to use OCR tools before starting from scratch. Why? Because:

  • It saves 1–3 hours per project
  • It reduces spelling and copying mistakes
  • It helps with accessibility when you need image descriptions
  • It allows faster localization for other languages (we use OCR + Google Translate for global clients)

But always proofread. I once saw a scanned infographic that said “$45.00” and the OCR turned it into “$4500”—not ideal when writing a comparison post about how much bourbon costs. As Whiskey Advocate confirms, most bourbons are under $60, so this kind of mistake would’ve hurt our client’s credibility

Table: Manual Typing vs OCR for Infographics

TaskManual TypingUsing OCR Tools
Time required1–2 hours5–10 minutes
Human errorsHighLow (if reviewed)
Formatting effortFull manual setupLight clean-up
Speed of publishingSlowerMuch faster
SEO usageDelayedReady immediately

We’ve compared these workflows internally, and using OCR wins every time—especially when the goal is to create editable, searchable, and accessible versions of visual content

Final Thoughts: Why OCR Should Be in Every Marketer’s Toolkit

If you’re someone who works with infographics, social media visuals, or presentation slides, learning how to extract and clean up text should be part of your daily routine. Whether you’re a blogger, copywriter, manager, or designer, using OCR helps speed things up, improves accuracy, and opens new ways to use your content across platforms

The more you use it, the better you’ll get at spotting issues—like when a scanned image says “bourbon $44.00” but gets misread as “burron $4400.” Trust the tools, but trust your eyes even more. With tools like Google Docs OCR, Adobe Acrobat OCR, or ABBYY FineReader, you can turn visual information into smart, reusable digital assets

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