Revolutionizing Multimodal Search In The Digital Marketing

Revolutionizing Multimodal Search In The Digital Marketing

For years, marketers have been building strategies around a clear and visible funnel. A marketing funnel traces a customer’s journey with a business. It provides a visual representation of conversions and turning leads into paying customers. Just as a funnel captures a large volume at the top and then guides it out from the bottom, the marketing funnel, too, attempts to catch the attention of as many leads as possible. Next, these leads slowly move through the various stages of a marketing funnel, finally leading to conversions, increasing brand loyalty, brand awareness, and higher sales.

Elias St. Elmo Lewis, an American advertising expert, introduced the marketing funnel model, which represents a customer’s journey and relationship with a business. Accordingly, every purchasing decision involves four steps: awareness, interest, desire, and action.

These strategies worked well in a web where behaviors were traceable, people clicked links, visited pages, signed up, bought a product, or bounced. Able to track almost all of it, and having attribution models aids in showing ROI to specific channels with varying degrees of accuracy and certainty.

What The Funnel Actually Is

The traditional marketing funnel breaks down customer journey into 3 core stages: top of funnel (TOFU), middle of funnel (MOFU), and bottom of funnel (BOFU), that marketers use to map content to each of these stages, creating clear pathways for users to follow from curiosity to conversion.

The top of the funnel contains awareness-level content introducing the brand or product to broad audience. For instance, blog posts, social media content, or explainer videos. The middle of funnel has consideration level content that helps users evaluate options, which further includes comparison guides, product demos, and email nurturing sequences. The third one is the bottom of funnel having conversion-level content aimed at driving action, such as purchase pages, pricing breakdowns, or testimonials.

Multimodal Search

Multimodal search is a method of retrieving information by combining multiple types of input data, such as text, images, audio, or video.

Multimodal search isn’t just about the difference between typing a query, speaking it loud, or snapping a photo, but about the way users fluidly engage across different platforms and media types to explore, evaluate, and decide.

Unlike traditional search, which relies primarily on text-based queries and metadata, multimodal systems analyze and cross-reference different data formats to understand user intent and deliver results. For instance, a user could search by uploading a photo of a plant, asking a voice question about its species, and adding a text note like “found in tropical climates.” The system processes all these inputs together to return accurate answers, with the approach mirroring how humans naturally use multiple senses or data types to seek information, making it more flexible than text-only methods.

A single purchase journey might involve googling a general topics, watching explainer videos on TikTok or YouTube, Watching explainer videos on TikTok or YouTube, Reading niche discussions on Reddit, browsing listings on Amazon, Comparing reviews on third-party blogs, and asking follow-up questions to an AI assistant. Even Amazon itself is leaning into AI-led search with Rufus, its generative shopping assistant. This is multimodal search.

Multimodal as the gateway for the Next Generation

Multimodal models are redefining what is possible with AI, processing not only text but also images, audio, and video, enabling new types of applications in customer support, content generation, document processing, and more. Unlocking a powerful new generation of AI capabilities, ones that can see, hear, and understand the world in ways traditional text models never could. But without the right operational foundation, these capabilities often remain stuck in prototypes.

An AI Gateway gives teams the structure they need to confidently integrate and scale multimodal models across the organization. It standardizes access, enforces security, tracks usage, and abstracts away the messiness of provider-specific quirks.

Gen Z (18-24 year olds) is currently the fastest-growing demographics using Google Search. Gen Z is growing up with tools that let them search the world visually, conversationally, and socially. They don’t see these modes as alternatives to traditional search; they see them as default behaviors.

For SEOs And Marketers

Personas and audience segmentations matters may be more than ever, but you can’t speak to people at just one stage or in one format. Mental availability is the core of any digital marketing strategy and is not about being everywhere for everyone, but being present across enough moments and modes that your brand is part of conversations while making decisions.

Thinking beyond the visible funnel means the chance to build familiarity and relevance. In a landscape where visibility is often obscured, casting a wider, more thoughtful net across intent types, platforms, and formats is how you maximize your odds of being chosen, even if never seen the full journey playing out.

Content distribution is important in both SEO and broader brand strategy. Messaging to be present wherever users are searching, reading, watching, or asking questions, which means treating website as one but not the only, SEO and AI optimization asset.