Multimodal Search: The Future of Google Ranking

Multimodal search refers to the ability to search using a combination of input types—text, voice, images, and even video—to retrieve relevant results. Google has been investing heavily in this area, integrating AI-powered tools like Google Lens, Search Generative Experience (SGE), and MUM (Multitask Unified Model) to understand and respond to complex, layered queries.

In the coming years, multimodal search will fundamentally reshape how users interact with search engines—and how websites are ranked. For SEO professionals, this is a wake-up call.

Why Multimodal Search Matters for SEO

• More Complex Queries: Users are asking richer, layered questions that span formats (e.g., “What’s this ingredient? [image]” + “How to cook it?” [text/voice]).
• AI Interpretation: Google's models like MUM understand meaning across different media types, not just keywords.
• Shifting SERPs: Results may include image carousels, short video clips, AI summaries, maps, and more—all above traditional blue links.

According to Google, MUM is 1,000 times more powerful than BERT, and can analyze both language and imagery to deliver deeper insights.

How to Optimize for Multimodal Search

Here are five practical steps to future-proof your SEO:

1. Use Structured Data (Schema)

Markup helps Google understand what your content represents (e.g., recipes, products, reviews), making it easier to integrate in multimodal results.

2. Optimize Images and Videos

• Use descriptive file names and alt text
• Compress images for faster loading
• Add video transcripts and closed captions
• Host videos on both your site and YouTube for double exposure

3. Target Visual Intent

Create content for visual queries, such as infographics, tutorials, product close-ups, and step-by-step visuals.

4. Improve Content Context

AI understands context better than ever. Write clearly, using natural language, headers, and internal links to build topical authority.

5. Embrace Voice Search SEO

Voice is a key modality. Use conversational keywords, answer questions (featured snippet style), and ensure fast mobile performance.

The Role of AI and MUM

Google's MUM model can:

• Translate across 75+ languages
• Understand nuances in image + text queries
• Compare and recommend content across formats

This means traditional text-heavy SEO strategies alone won’t be enough. You’ll need a multimedia-first content approach.

The Future: Multimodal + Personalization

Expect search to get even more:

• Conversational (via SGE and AI chatbots)
• Visual (Google Lens is growing rapidly)
• Location-aware (hyperlocal results through Google Maps & AR)
• Personalized (based on device, history, context)

Websites that cater to this layered intent will win higher rankings and better visibility in rich results.

FAQs

Q1: Will text SEO still matter in a multimodal world?

Yes, but it must be supported with images, video, and structured data for better context and engagement.

Q2: Is optimizing for image search worth it?

Absolutely. Image search contributes over 20% of all web search traffic, especially for ecommerce and lifestyle content.

Q3: How does Google choose which content appears in multimodal search?

Google prioritizes content that is high-quality, context-rich, and well-structured with schema markup, fast loading times, and media diversity.

Q4: Should I invest in AI tools for SEO?

Yes. AI tools help generate multimedia content, optimize for voice/image, and simulate user queries across modalities.