Check that email images match approved text using OCR

Compares the text inside your email's images to what it should say and logs a pass or fail in a spreadsheet.

How the work actually flows

It branches. Every path runs; all paths must finish before it continues.

Pattern: Parallel Split (2) ยท Synchronisation (3)

flowchart TD trig>"campaign email submitted for review"]:::trig s0["download both images"]:::task s1["compare extracted text"]:::task s2["mark match or mismatch"]:::task s3[("log result to sheet")]:::store trig --> s0 s1 --> s2 s2 --> s3 gx{"+ ocr each image"}:::gate s0 --> gx p00["extract text via ocr"]:::task gx -->|"reference image"| p00 p10["extract text via ocr"]:::task gx -->|"actual image"| p10 jn{"+ merge extracted text"}:::gate p00 --> jn p10 --> jn jn --> s1 out[/"pass or fail qa record logged"/]:::out pay{{"catches mismatched images before send"}}:::pay s3 --> out out --> pay classDef task fill:#e7f6fe,stroke:#34b8f0,color:#2c2a29 classDef svc fill:#f6f8fa,stroke:#7c8795,color:#2c2a29 classDef mi fill:#e7f6fe,stroke:#0079a8,color:#2c2a29,stroke-width:2px classDef human fill:#fff,stroke:#0079a8,color:#0079a8 classDef store fill:#f6f8fa,stroke:#0079a8,color:#2c2a29 classDef trig fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigtime fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigdata fill:#8ad4f5,stroke:#0079a8,color:#06314c,font-weight:bold classDef gate fill:#fff,stroke:#e8a23d,color:#6b4708,font-weight:bold classDef out fill:#1f9d6b,stroke:#167a53,color:#fff,font-weight:bold classDef pay fill:#06314c,stroke:#021f33,color:#fff
Starts itA stepA record or sheetEvery pathWaits for allResultPayoff
Build size
Standard

A mid-size build with several tools working together.

Business functions
Email AutomationDocument Processing & OCRSpreadsheet & Database OpsFile & Cloud Storage
Connects
GmailDropboxOCR.SpaceGoogle Sheets

The problem it solves

When a hero image or banner in a marketing email has the wrong text or an outdated offer, it usually isn't caught until customers see it. Checking every image by eye before each send is tedious and easy to get wrong.

Who it fits

An email marketing or QA team that needs to verify campaign images before they go out.

How it works

  1. Downloads the approved reference image and the actual image used in the email
  2. Runs both images through OCR to extract the text inside them
  3. Compares the expected text to the actual text
  4. Marks the result as a match or a mismatch
  5. Writes the result back to a spreadsheet for your records
What you get

Campaign images that always match approved text

You get every email image checked against its approved text with OCR, and the pass or fail result logged automatically.

What you get

A spreadsheet audit trail showing which email images matched their approved text and which didn't.

What you need

A Gmail account, a Dropbox account, an OCR.Space API key, and a Google Sheets account.

We can build this. But should you?

The hard question is not how to build it. It is whether this is the right thing to build first.

That is what a Fractional Chief AI Officer figures out with you, before anyone writes a line of code.

Let's Talk Strategy

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