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How to Export Asset Metadata from Bynder

Bynder is one of the most popular DAM platforms for brand management. Here's how to get your asset metadata into a spreadsheet for quality assessment.

Built-in Export
Yes (CSV)
Admin Required
Standard user
Best Output
CSV
Time to First Export
5-15 min
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The short answer

Bynder has a built-in metadata export feature. From the asset library, you can select items and export their metadata as a CSV file. For automated or large-scale exports, the Bynder API provides full programmatic access.

1

Bynder UI - CSV Export

EasyBest for: Marketing teams, brand managers, content teams, DAM administratorsOutput: CSV~5 minutes

Bynder allows users to select items in the library and export their metadata as a CSV file. No files are downloaded, only the metadata. This is the fastest way to get a metadata spreadsheet and requires no technical setup.

1
Log in to your Bynder portal. Navigate to the Asset Library and use filters, collections, or search to find the assets whose metadata you need. To assess your full library, use a broad search or browse without filters.
2
Select the items whose metadata you want to extract. You can use Select All to grab everything in the current view, or pick specific items.
3
Click the Export metadata option from the actions menu (three dots or toolbar). Choose CSV as the export format.
4
Download the CSV file. It includes all metadata properties configured in your Bynder portal: name, description, tags, copyright, custom metaproperties, dates, and more.
Metaproperties are key
Bynder's custom metadata fields are called "metaproperties." These are the brand-specific fields your organization has configured (brand, campaign, usage rights, region, etc.). The CSV export includes all metaproperties that are populated on each asset. Ask your Bynder admin to review the metaproperty configuration if fields are missing from the export.
Scoping your export
You can run multiple targeted exports to assess different parts of your library separately. For example, export one brand or collection at a time, or compare recently uploaded assets against older ones. Each export produces a standalone CSV that MQS can assess independently.
2

Bynder REST API

TechnicalBest for: Developers, IT teams, automated pipelinesOutput: JSON to CSV~20-30 minutes

The Bynder API provides complete access to all asset data including metadata, metaproperties, tags, and usage information. It supports pagination, filtering, and sorting, making it ideal for large-scale or automated exports.

1
Get API credentials from your Bynder portal: Settings → Advanced → API tokens. You need an OAuth2 token or a permanent token with read access.
2
Install the Bynder SDK: pip install bynder-sdk (or use direct HTTP requests as shown below).
3
Run the script below to list all assets with metadata and export to CSV.
python
import requests
import csv

PORTAL = "your-portal.bynder.com"
TOKEN = "your_api_token"
HEADERS = {"Authorization": f"Bearer {TOKEN}"}

def list_all_assets():
    """List all assets with pagination."""
    all_assets = []
    page = 1
    limit = 250
    while True:
        resp = requests.get(
            f"https://{PORTAL}/api/v4/media/",
            headers=HEADERS,
            params={
                "page": page,
                "limit": limit,
                "orderBy": "dateCreated desc",
                "total": 1,
            },
        )
        data = resp.json()
        assets = data if isinstance(data, list) else data.get("media", [])
        if not assets:
            break
        all_assets.extend(assets)
        page += 1
        if len(assets) < limit:
            break
    return all_assets

assets = list_all_assets()

with open("bynder_metadata.csv", "w", newline="") as f:
    writer = csv.writer(f)
    writer.writerow([
        "ID", "Name", "Description", "Type", "Extension",
        "File Size", "Width", "Height", "Created", "Modified",
        "Tags", "Brand", "Copyright"
    ])
    for asset in assets:
        writer.writerow([
            asset.get("id", ""),
            asset.get("name", ""),
            asset.get("description", ""),
            asset.get("type", ""),
            asset.get("extension", ""),
            asset.get("fileSize", ""),
            asset.get("width", ""),
            asset.get("height", ""),
            asset.get("dateCreated", ""),
            asset.get("dateModified", ""),
            ", ".join(asset.get("tags", [])),
            asset.get("brandId", ""),
            asset.get("copyright", ""),
        ])

print(f"Exported {len(assets)} assets to bynder_metadata.csv")
Including metaproperty values
The API response includes a property_* or propertyOptionsdictionary with your custom metaproperty values. To include these in your CSV, iterate over each asset's metaproperty keys and add them as additional columns.
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A note about Bynder Analytics

Bynder's Analytics section provides usage reporting: downloads, views, shares, and user activity. It does not export asset metadata fields. For metadata export, use Method 1 (UI export from the asset library) or Method 2 (API).

What metadata fields can you export?

FieldUI ExportBynder API
Asset name
Description
File type / extension
File size
Dimensions (W x H)
Created date
Modified date
Tags
Custom metaproperties
Brand / sub-brand
Copyright info
Usage rights / expiry
Download count
Collections
Derivatives / renditions
Public share links
!
Known limitations
  • Metaproperty options vs. values: Bynder metaproperties use option IDs internally. The UI export shows human-readable labels, but the API may return option IDs. You may need to map option IDs to labels using the /api/v4/metaproperties/ endpoint.
  • Video and document assets: Bynder stores video and document-specific metadata (duration, page count, etc.) that may not appear in the standard CSV export. The API provides the most complete metadata for all asset types.
  • Archive and waiting room assets: Assets in the archive or waiting room (approval queue) may not appear in standard library exports. Filter by status in the API to include these.

You have your metadata export.
Now score it.

Upload your CSV or Excel file to MQS and get a structural metadata health score out of 100 with dimension breakdowns and actionable diagnostics.

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