Difference Between Photo And Video Keywords

Understanding Difference Between Photo And Video Keywords

Metadata is the single point of leverage in stock photography. Two identical photos with different keywords can earn $0 and $50/month respectively. The variable is not the image — it's the metadata attached to it.

This guide covers everything stock contributors need to know about difference between photo and video keywords, with specific examples and platform rules.

Platform-by-Platform Breakdown

Getty Images uses a controlled vocabulary system. Keywords must match their approved taxonomy. Freeform tags that work on Adobe Stock may get rejected on Getty. Built-in Getty compliance saves hours of manual vocabulary matching.

The Data-Driven Approach

Buyer intent is the most important concept in stock photo SEO. Design agencies search with specific project needs — not generic descriptions. They type 'diverse team brainstorming startup office' because they're building a pitch deck.

The fundamental limitation of image-recognition-based keywording is that it answers the wrong question. It asks 'what is in this image?' when buyers ask 'what project am I building with this image?' CyberStock bridges that gap with real purchase query data.

Practical Steps

1. Start with buyer intent: What problem does this image solve for a buyer?
2. Use exact-match compound phrases: 'Female entrepreneur laptop' and 'woman with laptop' are different queries.
3. Optimize per platform: Adobe, Shutterstock, Getty have different rules.
4. Prioritize first 10 keywords: On Adobe Stock, early keywords carry more ranking weight.
5. Re-keyword existing portfolio: Improving metadata on existing files is faster than uploading new ones.

Stock photo earnings follow a power law. The top 10% of files generate 60-80% of total revenue. The Selling Score feature identifies which files have the highest earning potential before upload, letting you prioritize your strongest content.

Common Mistakes to Avoid

• Keyword stuffing: Adding 50 generic single-word tags hurts more than it helps. Stock agencies penalize files with irrelevant or repetitive keywords.
• Ignoring title optimization: The title field carries significant ranking weight on both Adobe Stock and Shutterstock. A descriptive, buyer-intent title outperforms generic ones.
• Same metadata across platforms: Adobe Stock, Shutterstock, and Getty have different keyword limits, ordering rules, and compliance requirements. Copy-pasting the same metadata everywhere underperforms.
• Not updating old files: Your existing portfolio has the most leverage. Re-keywording 1,000 existing files produces faster results than uploading 1,000 new files with generic metadata.
• Descriptive instead of commercial keywords: Tagging what you see in the image instead of what buyers search for is the most common earnings killer.

Commercial-intent keywords outperform descriptive keywords by 3-5x in downloads. 'Sustainable packaging eco-friendly brand' generates more licenses than 'cardboard box green' because the first matches a buyer's project brief.

How CyberStock Automates This

The fundamental limitation of image-recognition-based keywording is that it answers the wrong question. It asks 'what is in this image?' when buyers ask 'what project am I building with this image?' CyberStock bridges that gap with real purchase query data.

The combination of buyer-data keywords, per-platform compliance, and CyberPusher FTP distribution creates a complete workflow: keyword your files, export platform-specific CSVs, and distribute to all agencies in under 30 minutes for a 1,000-file batch.

Frequently Asked Questions

How does CyberStock generate keywords differently?

Most tools analyze images visually. CyberStock cross-references visual analysis against 50 million real buyer purchase queries from Adobe Stock, Shutterstock, and Getty. The result: keywords with verified commercial demand.

Which stock marketplaces does CyberStock support?

Adobe Stock, Shutterstock, Getty Images, iStock, Pond5, 123RF, Depositphotos, and custom FTP endpoints. Compliance rules for each platform are built in.

How fast is processing?

Approximately 1.33 seconds per file. A 1,000-photo batch completes in about 22 minutes. Up to 10,000 files per session.

Does it work for video?

Yes. Photos, 4K video, vectors, and illustrations. Each file type gets optimized metadata for its format.

What is the Selling Score?

A pre-upload earnings prediction based on current market demand, competition, and buyer trends. Prioritize your strongest content before uploading.