When Sarah launched her print-on-demand shop on Etsy in early 2024, she thought she had found the perfect intersection of AI-assisted creativity and entrepreneurship. Using MidJourney to generate stunning botanical illustrations, geometric patterns, and abstract wall art, she built a catalog of over 200 products in just three months. Her shop was pulling in $4,000 per month, she had earned her Star Seller badge, and her reviews were glowing. Then, seemingly overnight, everything fell apart.

The First Warning Signs

It started with a single listing removal. Sarah received a notification from Etsy stating that one of her best-selling prints, a watercolor-style floral arrangement, had been flagged and removed for violating the platform's AI-generated content policies. She assumed it was a one-time mistake, disputed the takedown, and moved on.

Within a week, seven more listings were removed. Then twelve. Then thirty-two. By the end of the month, nearly half of her active listings had been flagged by Etsy's automated content detection system. Her shop's visibility tanked, and the revenue she had worked so hard to build dropped by 60% almost overnight.

The Star Seller Badge Disaster

For Etsy sellers, the Star Seller badge is more than a vanity metric. It directly impacts search ranking, buyer trust, and conversion rates. When Sarah's listings started getting removed in bulk, her order completion rate dropped below the threshold, and Etsy stripped her Star Seller status. The cascading effects were devastating:

  • Search visibility plummeted as Etsy's algorithm deprioritized her shop
  • Conversion rates dropped 40% without the trust signal of the Star Seller badge
  • Repeat customers started leaving reviews asking why listings they had favorited were gone
  • Monthly revenue fell from $4,000 to approximately $1,600 within six weeks

Sarah was watching her business crumble and had no idea why Etsy was suddenly targeting her shop when she had been operating the same way for months.

Digging Into the Root Cause

Sarah spent days reading Etsy seller forums, Reddit threads, and blog posts about AI content detection. She initially assumed that Etsy was using some kind of visual AI detector to analyze the style of her images. She even considered switching her workflow to incorporate more manual editing, thinking that heavy post-processing in Photoshop would make her images look less like AI output.

Then she discovered something that changed everything: the metadata.

What MidJourney Embeds in Every Image

When you generate an image with MidJourney, the output file is not just pixels. Embedded within the file's metadata are several data fields that explicitly identify the image as AI-generated:

  • EXIF data containing MidJourney's processing software tags
  • IPTC fields that may reference the generation process
  • XMP metadata with AI tool identifiers and in some cases partial prompt information
  • C2PA content credentials that modern AI tools increasingly embed to comply with transparency standards

Sarah had been downloading her MidJourney outputs and uploading them directly to her print-on-demand mockup generator, which passed the metadata through untouched. Every single product image in her shop was essentially wearing a digital name tag that said "I was made by AI." For a deeper look at exactly what data AI tools embed, see our complete metadata removal guide.

How Etsy's Detection System Works

Etsy does not publicly disclose the full details of its AI detection pipeline, but based on seller reports and community research, the platform uses a multi-layered approach. One significant layer is automated metadata scanning. Before any visual analysis even begins, the system reads the EXIF, IPTC, and XMP fields of every uploaded image. If those fields contain signatures from known AI generation tools, the listing gets flagged immediately. For a detailed breakdown of the Etsy-specific challenges, check out our post on why you can't sell AI art on Etsy without getting flagged.

This explained why Sarah's older listings, uploaded before Etsy ramped up its detection system, had survived initially but were now being retroactively caught in sweeps. The metadata had been there all along. Etsy simply had not been looking for it until its detection capabilities expanded.

The Solution: Stripping Metadata with AI Metadata Cleaner

Once Sarah understood that metadata was the smoking gun, the fix became clear. She needed to strip every trace of AI generation data from her images before uploading them. After testing several approaches, including manual EXIF editors and command-line tools, she found AI Metadata Cleaner and realized it solved the problem with minimal friction.

Sarah's New Workflow

Here is the step-by-step process she developed:

  1. Generate the design in MidJourney at the highest resolution available, using the upscale feature for print-quality output
  2. Download the image from Discord or the MidJourney web interface
  3. Post-process in Photoshop or Canva if needed, adjusting colors, adding text overlays, or combining elements
  4. Upload to AI Metadata Cleaner to strip all EXIF, IPTC, XMP, and C2PA data from the file
  5. Download the cleaned image and verify the metadata is gone using a metadata viewer
  6. Upload the clean image to her mockup generator and create the Etsy listing

The entire metadata cleaning step added less than 30 seconds per image to her workflow. For batch uploads, she used the batch processing feature to clean dozens of images at once.

Re-uploading Her Existing Catalog

The bigger challenge was dealing with the 200+ existing product images that still had metadata embedded. Sarah dedicated a weekend to downloading every product image from her shop, running them through AI Metadata Cleaner in batches, and re-uploading them to her listings. She documented her process:

  • Saturday morning: Downloaded all product images organized by collection (approximately 220 images)
  • Saturday afternoon: Ran all images through batch metadata cleaning, verified removal with spot checks
  • Sunday: Re-uploaded cleaned images to each listing, updating any that needed fresh mockups
  • Monday: Submitted appeals for her removed listings with the new clean images attached

The batch processing capability was essential here. Cleaning 220 images one at a time would have taken hours. With batch processing, she processed entire folders in minutes.

The Recovery: Results After Metadata Cleaning

The results were not instantaneous, but they were dramatic and consistent.

Week One

Within the first week after re-uploading cleaned images, Sarah noticed that no new listings were being flagged. This was the first time in over a month that she had gone seven consecutive days without a takedown notice. Her existing appeals were being reviewed, and three of her highest-selling listings were restored.

Month One

By the end of the first month:

  • 85% of her appealed listings had been restored
  • Zero new flags on any listing with cleaned metadata
  • Daily views increased 45% as her shop began recovering in search rankings
  • Revenue climbed back to $2,800/month from the $1,600 low point

Month Two

By the second month, the recovery was nearly complete:

  • All remaining listings restored through the appeals process
  • Star Seller badge reinstated after meeting the metrics threshold for the qualifying period
  • Revenue reached $4,200/month, actually surpassing her pre-flagging peak
  • Customer reviews started flowing in again as visibility returned to normal

The revenue recovery beyond her previous peak was partly due to the fact that during the crisis, Sarah had continued creating new designs. Once the shop's visibility was restored, she had a larger catalog than ever, and the new designs had been uploaded clean from the start.

Practical Tips for Other Print-on-Demand Sellers

Based on her experience, Sarah developed a set of best practices that she now shares with other POD sellers in her community:

1. Never Upload Raw AI Output Directly

This is the single most important rule. No matter which AI tool you use, whether it is MidJourney, DALL-E, Stable Diffusion, or Leonardo AI, always clean the metadata before the image enters your product pipeline. See our comparison of AI tool metadata signatures to understand what each tool embeds.

2. Build Metadata Cleaning Into Your Standard Workflow

Do not treat metadata cleaning as an afterthought or something you do only when there is a problem. Make it a mandatory step in your production process, just like resizing or color correction. The extra 30 seconds per image is negligible compared to the cost of a flagged listing.

3. Clean Metadata Before It Enters Your Asset Library

If you use a digital asset management tool or even just organized folders to store your designs, make sure images are cleaned before they enter that system. This prevents you from accidentally grabbing an uncleaned image months later and uploading it to a new listing.

4. Audit Your Existing Catalog

If you have been selling AI-assisted designs without cleaning metadata, assume that every image in your shop contains flaggable data. Schedule a weekend to download, clean, and re-upload everything. It is tedious but far less painful than dealing with rolling takedowns.

5. Keep Original and Cleaned Versions

Maintain a folder structure that separates your raw AI outputs from your cleaned production files. The originals can be useful for future editing or upscaling, but they should never be uploaded directly to any marketplace.

6. Test Before Bulk Uploading

Before you re-upload your entire catalog with cleaned images, test with a few listings first. Upload cleaned versions of previously flagged designs and wait a few days to confirm they pass through without issues. This gives you confidence before committing to the full migration.

7. Document Your Process for Disputes

If a listing does get flagged despite having clean metadata, having documentation of your workflow helps with appeals. Screenshot your metadata cleaning process and keep records showing that the images have been stripped of AI identifiers.

Understanding the Broader Etsy Landscape

Sarah's experience is far from unique. Etsy has been progressively tightening its enforcement of AI content policies throughout 2024 and 2025. The platform has invested heavily in automated detection systems that scan both new uploads and existing listings. For sellers using AI tools as part of their creative process, understanding how these systems work is not optional; it is a business survival skill.

The key insight from Sarah's story is that metadata is often the first and easiest signal that detection systems look for. Visual analysis techniques, which try to identify AI-generated images by their pixel patterns and artifacts, are computationally expensive and less reliable. Metadata scanning, by contrast, is fast, cheap, and definitive. If your image file says it was made by MidJourney, the platform does not need to guess.

This also means that metadata cleaning is the most effective single step you can take to protect your listings. You can spend hours trying to make your AI art look less like AI art through post-processing, or you can spend 30 seconds removing the data that tells the platform exactly how the image was made.

Lessons Learned

Sarah's story illustrates several important truths for anyone selling AI-assisted creative work online:

  • Platform detection is real and getting more sophisticated every quarter
  • Metadata is the lowest-hanging fruit for detection systems, and cleaning it is the simplest defense
  • Recovery is possible but takes time and requires a systematic approach
  • Prevention is far cheaper than recovery, both in time and lost revenue
  • Building good habits early means you never have to go through the painful catalog audit process

If you are a print-on-demand seller using AI tools to create designs, take the time to clean your metadata now, before you find yourself in Sarah's position. The AI Metadata Cleaner makes it fast and straightforward, whether you are processing a single hero image or batch cleaning your entire product catalog. Visit our use cases page to learn more about how other creators are protecting their work.