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AI Image Analysis Enrichment

Enrich your product catalog by analyzing product images with AI-powered visual recognition that automatically extracts visual attributes like colors, patterns, styles, and materials.

AI Image Analysis properties use computer vision to identify visual characteristics from product photos, creating valuable structured data that enhances your catalog and improves product discovery.

Before you begin

  • Map your feed's image URL field to the system property "image" in your feed configuration

  • Create the output properties where visual attributes will be stored:

    • Use String type for complex data like color breakdowns with percentages

    • Use List type for categorical analyses (e.g., style categories) to guide the AI into pre-defined options specific to your business

  • Ensure image URLs are publicly accessible (HTTPS) and show clear product photos

Understanding image analysis properties

Image analysis properties work differently from text-based AI enrichment. Instead of analyzing product titles or descriptions, these properties examine actual product images to identify visual characteristics like:

  • Color composition - Primary, secondary, and accent colors with coverage percentages

  • Visual style - Design aesthetics, patterns, and style categories

  • Material appearance - Texture and material identification from visual cues

  • Structural features - Shape, silhouette, and design elements

The AI analyzes each product's image individually, making this enrichment method ideal for properties that require visual context rather than text interpretation.

Create your image analysis property

Navigate to Product Data > Properties and click Add Property to create a new image analysis property.

Configure basic settings

  1. Enter a descriptive Property Name (e.g., "Color Details" or "Visual Style")

  2. A Property Key will automatically pre-fill the field based on the name

    1. Property keys should be unique, short, and identifiable (e.g., "color_details" or "visual_style")

  3. Set the Value Type to Image Analysis (AI)

  4. Choose your Target Level:

    • Product - For attributes consistent across all variants

    • Variant - For attributes that differ by variant (e.g., if your variants are defined by different colors, select this so the enricher can analyze each image variant individually)

  5. Configure additional settings:

    • Turn on Lock being edited in the app if you want to prevent manual overrides of AI analysis

    • Turn on Mark as internal if you want to keep visual analysis data internal

Configure AI enrichment settings

1

Enable automated enrichment

Turn on the Enable automated background enrichment toggle to activate image analysis for all eligible products (defined int the property filter). Once enabled, Crobox will automatically process eligible product images during feed imports or re-indexing.

Image analysis runs automatically in the background after enabling. You'll see a progress indicator showing "Property is ready for being processed in the background."

2

Write your visual analysis prompt

Create a clear, specific prompt that defines what visual characteristics the AI should identify. Your prompt should include:

Essential components:

  • Property definition - What visual attribute to identify

  • Output format - How to structure the results (e.g., color breakdown, style category)

  • Visual markers - Specific visual cues the AI should look for

  • Coverage guidelines - Percentage thresholds or prominence rules

  • Constraints - What to include or exclude from analysis

Example prompt for color analysis:

Analyze the product image and identify visible colors with their coverage percentages.

Format: "primary_color:percentage|secondary_color:percentage|accent_color:percentage"

Instructions:
- Identify all colors visible on the main product body, accents, and details
- Calculate approximate percentage of total visible surface area for each color
- List colors in descending order by coverage
- Include only colors with ≥5% coverage
- Total percentages must sum to 100%

Use consistent color names: black, grey, navy, blue, green, olive, brown, tan, beige, orange, red, yellow, white, purple, multi-color

Coverage patterns:
- Primary: Usually 40-80%
- Secondary: Usually 15-40%
- Accents: Usually 5-20%

Example: "navy:80|white:15|gold:5"

Example prompt for style identification:

Classify the product's visual style based on design elements and aesthetic.

Categories: Modern, Classic, Vintage, Minimalist, Bold, Athletic, Elegant, Rustic

Consider:
- Overall design aesthetic
- Color palette complexity
- Pattern presence
- Structural elements
- Visual balance

Return only the single most appropriate category.

Image analysis prompts require more detail than text-based prompts. Be specific about visual markers, coverage percentages, and formatting requirements to ensure consistent results.

3

Define inputs and outputs

Inputs:

  • Select Image as your input source

  • The system automatically uses the product's primary image URL

  • Ensure your product feed includes valid, accessible image URLs

Outputs:

  • Select the property where visual analysis results will be stored

  • For complex analyses (like color breakdowns), use String type properties

  • For categorical analyses (like style identification), use List type properties to guide results into pre-defined categories specific to your business

4

Test with preview

Validate your image analysis setup before enabling enrichment across your catalog.

  1. Click Fetch Preview Values to analyze sample products

  2. Review the preview table showing product images, titles, and AI-generated results

  3. Compare results against what you see in the product images to verify accuracy

Use Add Filter to test on specific product subsets and identify how well the analysis works across different product types.

Be specific about visual markers, coverage percentages, and formatting requirements in your prompt to ensure consistent results.

5

Save and monitor enrichment

  1. Click Save to store your configuration

  2. Enrichment begins automatically in the background

  3. Monitor the status indicator: Changed > Active > Completed

Image analysis processes approximately 100-120 products per hour, so larger catalogs may take several hours to complete.

6

Review and refine results

After enrichment completes, check quality by navigating to Product Data > Catalog and reviewing your image analysis property alongside product images. If needed, refine your prompt based on any edge cases discovered, then click Remove enriched data and save to re-run enrichment with improved instructions.

Best Practices

  • Prompt clarity: Be visually specific about what to look for, not what to read. Define clear boundaries with percentage thresholds and categorical options.

  • Image quality: Use clear, well-lit product photos with neutral backgrounds. Avoid lifestyle images, multiple products, or low-resolution photos.

  • Property organization: Use descriptive names for properties and create separate properties for each distinct visual attribute. Use List type for pre-defined categories specific to your business.

Prompt examples

Color palette extraction

Extract colors and coverage percentages for accurate color-based filtering and discovery.

Prompt approach:

Analyze the product and return: "primary:percentage|secondary:percentage|accent:percentage"
Include only colors with ≥5% coverage; total must sum to 100%.
Style classification

Categorize products by visual design aesthetic for style-based recommendations and curation.

Prompt approach:

Classify from: Modern, Classic, Vintage, Minimalist, Bold, Athletic, Elegant
Return the single best match based on design elements.
Pattern recognition

Detect visual patterns for pattern-based filtering and trend-based merchandising.

Prompt approach:

Identify dominant pattern: Solid, Striped, Plaid, Floral, Abstract, Geometric, Camo, Animal Print
Return "Solid" if no pattern is visible.

Troubleshooting

  • Verify image URLs are publicly accessible (HTTPS) and in supported formats (JPG, PNG, WebP)

  • Confirm "Enable automated background enrichment" is toggled on to ensure new products receive image analysis enrichment

  • Check that input is set to "Image" and output properties are configured

FAQs

How long does image analysis take?

Image analysis processes approximately 100-120 products per hour. A 1,000-product catalog typically takes 8-10 hours.

What image formats are supported?

JPG, PNG, and WebP formats via publicly accessible HTTPS URLs.

Can I combine image analysis with text-based enrichment?

We recommend ensuring your output properties are unique to either the image analysis or text-based enrichment properties to ensure you can QA enrichment values with ease. Use image analysis for visual attributes and text-based enrichment for descriptive attributes.

Can I manually edit AI-generated values?

Yes, unless "Lock being edited in the app" is enabled. Manual edits may be overwritten if you re-run enrichment.

How do I re-process products after updating my prompt?

Click "Remove enriched data" to clear results, update your prompt, and save. Enrichment restarts automatically.

What happens if products don't have images?

Products without valid image URLs will not be accurately analyzed during enrichment.

What's next

  • Use visual attributes in Product Finder experiences for enhanced filtering within experiences and share product highlights with users in personalized Campaigns

  • Complete with AI Enricher Properties to enrich and create comprehensive product data for your experiences

  • Track enrichment performance in property and refine prompts based on results

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