# AI Image Analysis Enrichment
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
Configure the property in this order:
{% hint style="info" %}
Set a product filter before activation. The **Enable automated background enrichment** toggle only becomes available after you define which products should be processed. This helps you validate results on a smaller subset before enriching a larger part of your catalog.
{% endhint %}
{% stepper %}
{% step %}
**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.
```
{% hint style="warning" %}
Image analysis prompts require more detail than text-based prompts. Be specific about visual markers, coverage percentages, and formatting requirements to ensure consistent results.
{% endhint %}
{% endstep %}
{% step %}
**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
{% endstep %}
{% step %}
**Set the product filter**
Use **Only for these products** to define which products are eligible for enrichment.
Start with a narrow subset so you can validate the generated values before scaling up:
* New products only
* A specific category or brand
* Products missing a target attribute
This filter is required. You can only activate enrichment after setting it.
{% endstep %}
{% step %}
**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
Adjust **Only for these products** or use **Add Filter** to test on specific product subsets and identify how well the analysis works across different product types.
{% hint style="warning" %}
Be specific about visual markers, coverage percentages, and formatting requirements in your prompt to ensure consistent results.
{% endhint %}
{% endstep %}
{% step %}
**Activate enrichment**
Turn on **Enable automated background enrichment** after your preview looks correct.
Once enabled, Crobox automatically processes only the products that match your filter during feed imports or re-indexing.
{% hint style="info" %}
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."
{% endhint %}
{% endstep %}
{% step %}
**Save and monitor enrichment**
1. Click **Save** to store your configuration
2. Turn on **Enable automated background enrichment** if you have not already done so
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.
{% endstep %}
{% step %}
**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.
{% endstep %}
{% endstepper %}
***
## 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
{% tabs %}
{% tab title="Image analysis not processing" %}
* Verify image URLs are publicly accessible (HTTPS) and in supported formats (JPG, PNG, WebP)
* Add or review **Only for these products** first, since activation depends on it
* 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
{% endtab %}
{% tab title="Inconsistent or inaccurate results" %}
* Refine your prompt with more specific visual markers and edge case examples
* Verify product images are clear and well-lit
* Test with a smaller product subset first to validate approach
{% endtab %}
{% endtabs %}
***
## 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](https://docs.crobox.com/how-to-guides/product-data/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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