Tracking Multimodal and Image Search Traffic in Google Search Console
The New Reality of Visual Search Analytics
Google Search Console has introduced a dedicated multimodal filter, finally allowing SEOs to separate visual-driven traffic from standard web results. As user behaviour shifts toward visual-first discovery, understanding how to interpret Google Search Console reports is no longer just about blue links. This update is a direct response to the rise of Google's visual shift, where tools like Google Lens and Circle to Search are changing how users interact with your content.
What is Multimodal Search Traffic in GSC?
Multimodal search traffic refers to queries where a user combines different input methods—typically text and images—to find information. In the context of the GSC performance report, the multimodal filter isolates clicks and impressions originating from visual discovery features.
Previously, this data was often buried within general image search metrics. By using the new filter, you can now see exactly how often your assets appear in Lens results or through AI-assisted visual lookups. This is critical for e-commerce managers who need to justify the ROI of high-quality product photography and structured data implementation.
How to Use the Multimodal Filter in Google Search Console
Accessing this data is straightforward, but you must be precise with your segmentation to avoid skewed results. Follow these steps to isolate your visual search performance:
- Open your property in Google Search Console.
- Navigate to the Performance report in the left-hand sidebar.
- Click on the Search type filter at the top of the report.
- Select Web (if you want to see multimodal results embedded in standard search) or Image.
- Look for the Appearance filter and select the Multimodal option.
Once applied, the report will update to show only those queries where your content was surfaced via visual search features. If the filter is greyed out, it typically means your site has not yet received traffic from these specific visual channels.
Interpreting Your Visual Search Data
Once you have isolated the data, do not just look at total clicks. You need to compare your visual performance against your standard organic traffic. Use the following table to help categorise your findings:
| Metric | Why It Matters | Actionable Insight |
|---|---|---|
| High Impressions / Low Clicks | Poor visual relevance | Optimise alt text and image quality |
| High CTR | Strong visual appeal | Replicate style for other products |
| Low Visibility | Missing structured data | Audit schema markup for products |
Remember that as you optimise content for Google AI Overviews, your visual assets will play an increasingly large role in how Google understands your site's entities.
Technical Considerations for Visual Search
Tracking is only half the battle. If you find that your multimodal traffic is stagnant, the problem is rarely the reporting tool—it is the technical foundation. Ensure your images are properly indexed, served in modern formats like WebP or AVIF, and wrapped in descriptive Product or ImageObject schema. Without these signals, Google’s algorithms struggle to connect your visual assets to the user's intent, regardless of how well you track the results.