What Is Multimodal Search in Google Search Console? A Complete Guide
Google Search is becoming less dependent on text-only queries. Users can now search using images, screenshots, photos, and combinations of visual and written information. Google Search Console has started reflecting this change by introducing a Multimodal option within the Web search type.
For SEOs, this creates a new way to understand how people discover websites through visual search behavior.
What Is Multimodal Search?
Traditionally, a user searches Google by typing a query such as:
“best running shoes for flat feet”
This is a text-based search because the search input consists only of text.
A multimodal search can involve more than text. For example, a user might upload a photograph of a pair of running shoes and ask:
“Where can I find shoes similar to these?”
The search involves a visual input plus a written question.
Google’s Search Console interface describes Web-multimodal searches as Web search results triggered by a query that uses an image, photo, or screenshot. Text-only queries are categorized as Web text-based searches.
This is important because the result is still part of Google Web Search. It is not automatically Google Image Search.
How Does Multimodal Search Work?
A simple way to understand it is:
User provides visual input
↓
Google analyzes the image/photo/screenshot
↓
User may add text or a question
↓
Google interprets the combined information
↓
Google retrieves relevant Web results
↓
A website may receive an impression or click
↓
Search Console can attribute that Web-search activity to the site’s performance
For example, imagine a person sees an interesting pair of running shoes while watching a video.
They take a screenshot and upload it to Google.
They then ask:
“What shoes are these and where can I buy them?”
Google can use the screenshot as part of understanding the search.
If a running-shoe retailer’s product page appears as a Web result and receives a click, that activity can potentially be represented within Web → Multimodal in Search Console.
Where Does the Multimodal Data Come From?
This is one of the most important things to understand.
The data does not mean that Google has taken information from your website’s images and placed it into a “multimodal” report.
Instead, the classification describes the type of search interaction that generated the Web result.
There are two different sides to the process.
The user’s side
The user provides Google with:
- A photo
- An image
- A screenshot
- Potentially accompanying text
The website’s side
Google can then return Web results containing:
- Product pages
- Category pages
- Articles
- Guides
- Other relevant Web pages
Search Console reports performance when your website appears in Google’s search results. Google explains that the Performance report can be filtered by search type and analyzed using metrics such as clicks, impressions, CTR, and position. (Google Help)
Therefore, Multimodal is primarily describing the searcher’s input, not the format of your website’s content.
Multimodal Search vs Text-Based Search
Consider two people looking for running shoes.
Text-based search
A person types:
“black running shoes for marathon training”
Google processes the text query and returns relevant results.
Search Console can classify this as:
Web → Text-based
Multimodal search
Another person has a photo of a particular running shoe.
They upload the photo and ask:
“Find me something similar to this.”
Google can use the visual input together with the written question.
A resulting Web search interaction can be classified as:
Web → Multimodal
The difference is therefore not necessarily about what the website looks like. It is about how the search was initiated.
Multimodal Search Is Not the Same as Google Image Search
This is where confusion can easily happen in Search Console.
Google Search Console separates different search types.
For example:
| GSC Search Type | Basic meaning |
|---|---|
| Web → Text-based | Web search using text-only input |
| Web → Multimodal | Web search involving visual input such as an image, photo, or screenshot |
| Image | Performance from Google Image Search |
| Video | Performance from Google’s video search results |
| News | Performance associated with Google News search |
Google specifically treats Image Search separately from Web Search. (Google Help)
So if someone searches Google Images for:
“black running shoes”
that does not automatically become a Multimodal Web search.
Likewise, if someone uploads a photo and gets Web results, that doesn’t mean the interaction should be analyzed as Google Image Search.
An Example From the Fashion Industry
Let’s use an example from the fashion industry.
Imagine someone sees a jacket worn by an actor in a video.
They don’t know the brand.
Instead of trying to describe the jacket using words, they take a screenshot.
They upload the screenshot to Google and ask:
“Where can I buy a jacket like this?”
Google can analyze visual characteristics such as:
- Color
- Shape
- Clothing type
- Patterns
- Design characteristics
- Other visual signals
It can then return relevant Web pages.
A fashion retailer selling a similar jacket could appear in those results.
If the retailer receives an impression or click, that search activity could contribute to its Web → Multimodal performance in Search Console.
The important point is that the retailer did not necessarily receive the visitor because the user typed the exact product keyword.
The visual appearance of the product helped initiate the search journey.
What Data Can You Analyze in Search Console?
Once you select:
Performance → Search results → Search type → Web → Multimodal
you can analyze the available performance information using the normal Search Console dimensions.
Depending on the data available, useful dimensions include:
- Queries
- Pages
- Countries
- Devices
- Dates
And the main metrics include:
- Impressions
- Clicks
- CTR
- Average position
Google’s Performance report supports filtering and comparison across multiple dimensions. (Google Help)
This makes Multimodal potentially useful as a separate SEO segment rather than combining it with all Web traffic.
Why Should SEOs Care About Multimodal Search?
Search behavior is becoming more visual.
A user may not always know the correct words to describe what they are looking for.
Consider these searches:
“What is this type of chair?”
“Find shoes similar to this.”
“Where can I buy this dress?”
“What camera is this?”
“Find a similar backpack.”
Describing a visual object accurately with text can be difficult.
An image can communicate information that would otherwise require a long search query.
This creates an additional discovery path for websites.
What Does This Mean for SEO?
Multimodal search does not mean that traditional keyword SEO is becoming irrelevant.
Text remains an important part of search.
Instead, SEO increasingly needs to account for both:
What users type
and
What users show Google.
This makes several areas of optimization more important.
1. Product and Content Images
Images should clearly represent what is being discussed on the page.
For example, an ecommerce product page should contain useful, relevant product photography rather than generic decorative images.
2. Image Context
Google can understand images in the context of the surrounding page.
Relevant:
- Product names
- Headings
- Descriptions
- Captions
- Alt text
- Structured data
can help establish what the image represents.
This doesn’t mean adding keywords unnaturally. The information should accurately describe the content.
3. Product Page Quality
A visual search may lead to a product page, but the page still needs to satisfy the user.
A strong product page should clearly communicate:
- What the product is
- Its important characteristics
- Available variations
- Price
- Availability
- Specifications
- Supporting images
- Other useful information
4. Structured Data
For ecommerce websites, appropriate structured data can help Google understand information about products and other page entities.
Multimodal search doesn’t eliminate the importance of technical SEO. It adds another potential discovery path on top of the existing search ecosystem.
What Multimodal Does NOT Tell You
There is an important limitation.
Seeing Multimodal impressions does not tell you exactly what image the user uploaded.
Search Console isn’t necessarily giving you a report saying:
“This particular screenshot caused this impression.”
You should therefore avoid interpreting the data too literally.
For example:
Multimodal impressions increased 30%
doesn’t automatically mean:
“Google understands our product images 30% better.”
It means the website received more visibility from searches classified within that Web-multimodal segment during the selected period.
Search Console data is aggregated and can also have reporting limitations such as anonymized queries and data truncation. (Google Help)
Multimodal Search vs Image SEO
These two concepts are related but different.
Image SEO
The goal is to make images useful and discoverable in search.
This includes:
- Relevant images
- Descriptive filenames
- Appropriate alt text
- Image quality
- Page context
- Technical accessibility
- Structured data where appropriate
Multimodal SEO
There isn’t a single official “multimodal SEO checklist.”
Instead, the broader objective is to make your website and its content understandable when users discover it through visual search interactions.
That means combining:
Image understanding + page context + product/content information + traditional SEO
rather than treating the image as an isolated asset.
How to Analyze Multimodal Performance
A practical workflow is to start with four questions.
1. How much Multimodal visibility do we have?
Check:
Impressions → Web → Multimodal
This establishes whether the segment is generating meaningful visibility.
2. Which pages receive that visibility?
Open:
Pages
This can reveal whether Multimodal visibility is concentrated around:
- Product pages
- Category pages
- Editorial content
- Guides
- Other page types
3. Which queries are associated with it?
Open:
Queries
This can help identify the language Google associates with the Web results.
However, don’t assume that every underlying visual input will be completely represented as a conventional text query.
4. Which pages actually receive clicks?
Compare:
Impressions → Clicks → CTR
A page with substantial impressions but very few clicks deserves further investigation.
A Simple Reporting Framework
SEO teams can add a small section to their monthly Search Console report:
| Search segment | Impressions | Clicks | CTR | Avg. position |
|---|---|---|---|---|
| Web – Text-based | — | — | — | — |
| Web – Multimodal | — | — | — | — |
| Image | — | — | — | — |
The purpose isn’t to assume that one segment is inherently more valuable.
Instead, it allows the SEO team to understand how different types of search behavior contribute to organic visibility.
What Should SEO Teams Do Now?
There is no need to create a completely separate SEO strategy just because this filter exists.
A more practical approach is to incorporate Multimodal into existing SEO analysis.
Technical SEO
Make sure important pages are crawlable and indexable.
Image optimization
Use relevant, high-quality images and descriptive supporting information.
Content
Explain products, concepts and entities clearly using natural language.
Product pages
Provide enough textual and visual information for Google and users to understand the product.
Structured data
Use appropriate structured data where applicable and keep it consistent with visible page content.
Search Console monitoring
Track Web-Multimodal separately to establish a baseline and identify changes over time.
Final Takeaway
Multimodal in Google Search Console represents Web search activity where the search query involves visual input such as an image, photo, or screenshot.
It should not be confused with Google Image Search.
The data comes from Google’s search-result performance data, not from Google Analytics or from a website’s own image analytics.
The most useful way to think about it is:
Text-based search tells you how people find your website by describing what they want. Multimodal search gives you visibility into Web searches where people can also show Google what they are looking for.
For SEO teams, the new filter provides another way to segment organic search behavior and understand whether pages are appearing when users begin their search with visual information.
As visual search experiences continue to develop, monitoring this segment alongside traditional Web and Image Search can help establish how much of a website’s organic visibility comes from different search behaviors.
