Voice and visual search are shifting discovery from typed keywords to conversations and cameras, funneling buyers into AI answers, local results, and “see it, shop it” moments. Marketers should optimize for multimodal intent: structure product data, craft speakable answers, upgrade images, and deploy AI Workers to scale content, feeds, and testing.
Search has outgrown the search box. People now talk to devices while driving, point cameras at products in-store, and expect instant answers curated by AI. According to Google, Lens powers nearly 20 billion visual searches each month and is increasingly shopping-driven, while AI Overviews are changing how information and ads appear at the top of results. Meanwhile, zero-click searches are rising, compressing click opportunities but expanding “answer” exposure. This is not a channel tweak; it’s a behavior shift.
If you lead Marketing Innovation, your mandate is clear: redesign discovery for a multimodal world. In this guide, you’ll learn what’s changing, what to prioritize, and how to operationalize voice-and-visual readiness with execution systems—not just tools. You’ll see where schema and images matter, where concise answers win, how AI Overviews and Lens affect SEO and paid media, and how AI Workers help you do more with more.
Voice and visual search change marketing by moving discovery from typed queries and linear SERPs to multimodal journeys that start with a question, a photo, or a scene—and often end with an AI-curated answer before a click happens.
For a Head of Marketing Innovation, this creates a practical gap: your stack and workflows were built for keyword-input and click-through optimization. But your buyers now “search what they see,” ask natural-language questions, and accept summarized answers. Google reports Lens queries are one of Search’s fastest-growing types, with shopping intent embedded. Ads are also entering AI Overviews and Lens experiences, reshaping paid visibility. And the web is seeing more zero-click outcomes—SparkToro’s 2024 study found that a majority of Google searches end without a traditional click-through—so brand presence must win earlier in the journey.
Operationally, this means data quality, content structure, and asset depth now determine discoverability. Product feeds, images, transcripts, FAQs, and local profiles become ranking levers—alongside traditional SEO. It also means execution volume must rise: more variants, more FAQs, more snippets, and faster test-and-learn cycles. That’s why teams are moving beyond point tools to AI Workers that actually do the work across systems. The winners won’t just adapt pages—they’ll re-architect discovery for voice, vision, and AI-curated surfaces.
To win voice and visual search, you must structure information so AI systems, assistants, and Lens can identify entities, understand relationships, and present definitive answers and products quickly.
Multimodal intent is a buyer’s goal expressed through voice, images, video, or text, and you should map it by journey stage and input type (e.g., “What fits a 10x10 patio?” via voice; “Find this backpack” via photo; “Compare X vs Y” via text).
Start by cataloging top questions and scenes:
To make content speakable, write concise, 20–30 second answers, front-load conclusions, and mark eligible sections with speakable structured data where appropriate.
Use Google’s guidance on Speakable markup for eligible content types, and format answers like radio copy—clear, literal, and brand-safe. Keep sentences 12–18 words, use active voice, and include one data point or instruction. Publish expanded context below your speakable blurb to satisfy both AI Overviews and human readers. Reference: Google’s Speakable documentation.
You should use schema.org product, review, organization, FAQ, and how-to markup consistently, ensure product IDs are stable across your catalog, and synchronize attributes across PDPs, feeds, and sitemaps.
AI systems reward coherence. Ensure names, specs, and benefits match across your PDPs, Merchant feeds, and editorial pages. Add FAQs that mirror natural questions and provide definitive answers. Link to authoritative sources where relevant. This “content as data” approach becomes your new advantage—and it scales with the right AI execution strategy.
To convert visual search, you must optimize products and assets so Lens can identify items precisely, match them to a complete feed, and surface price, reviews, and availability instantly.
You optimize for Lens by upgrading image quality and diversity, enriching product feeds, and aligning PDP attributes with Google’s Shopping Graph fields to improve exact-match identification.
Google states people use Lens for nearly 20 billion searches monthly and that a significant share are shopping-related, with Shopping ads appearing alongside visual results to connect high-intent consumers to products. Make your products “camera-ready”:
Paid media should extend existing Search, Shopping, and Performance Max campaigns to surface in AI Overviews and Lens, with feed quality and creative variants driving eligibility and performance.
Google confirms ads now appear within AI Overviews (when relevant) and alongside Lens results. Your to-do list:
To capture voice search, you must publish concise, natural-language answers; strengthen local and product profiles; and ensure fast, mobile-friendly experiences that assistants can rely on.
You optimize local voice queries by perfecting your Google Business Profile, NAP consistency, hours, services, and reviews, and by publishing geo-specific FAQs and answer snippets.
Voice queries often resolve to local intent (“open now,” “closest,” “best rated”). Maintain accurate profiles and add question-and-answer sections that match real phrasing: “Do you install on weekends?” “Is parking free?” Create short, scannable service pages per location with embedded FAQs. Speed and Core Web Vitals still matter; assistants prefer fast, trustworthy sources.
The best formats are direct-answer paragraphs, bulleted steps, short how-tos, and structured FAQs that restate the question in the first sentence.
Follow a “radio first” editing pass: remove hedging, front-load the answer, and keep to 20–30 seconds. Where eligible, add Speakable markup. For top questions, pair the short answer with a deeper guide. GWI reports continued growth in voice assistant usage and younger cohorts adopting multi-device queries—another reason to ensure continuity from spoken answer to visual confirmation to purchase. Reference: GWI: Voice search trends.
To measure marketing impact as clicks compress, you must track upstream visibility (impressions, appearances in AI surfaces), downstream outcomes (store visits, calls, conversions), and the speed/volume of iteration.
KPIs should expand to include surface-specific impression share, asset eligibility rates, product match precision, time-to-launch, and iteration velocity across channels.
SparkToro’s 2024 study highlights the growth of zero-click searches; this demands proxy metrics that capture value before the click and blended models that connect exposure to outcomes. Track:
You can prove ROI by combining controlled tests (geo or audience holdouts), MMM, and platform signals (impressions, store visits, calls), triangulated with conversion lift from feed and content upgrades.
Run before/after tests when shipping schema, feed enrichments, or image overhauls. Use holdout regions for PMax changes tied to AI Overviews and Lens. Socialize early wins via executive-ready summaries (an ideal job for an AI Worker) and reinvest gains into higher-ambition experiments—your CFO will back what you can measure.
To operationalize multimodal readiness, you should deploy AI Workers that create, enrich, validate, and publish the content, feeds, and assets your stack needs—continuously and compliantly.
AI Workers change execution by doing the work end-to-end: drafting FAQs, generating speakable blurbs, creating image variants, enriching product feeds, validating schema, and pushing updates into your CMS and Merchant Center.
Unlike assistants or point automations, AI Workers plan, reason, and act inside your systems. They shrink time-to-launch from weeks to days, and keep catalogs and content synchronized—critical for Lens and AI Overviews. Pair them with oversight tiers for brand safety and auditability. See how to design GTM execution around workers: AI Strategy for Sales & Marketing and the AI Workers for Marketing & Growth resource.
The first 60-day roadmap should target high-feasibility, high-impact items: top 50 FAQs with speakable answers, top 200 PDP feed enrichments, image variant expansion for Lens, and local-profile content fixes.
Use an Impact × Feasibility ÷ Risk score to pick three initiatives, then publish weekly progress and KPI lift. For a practical framework, see Marketing AI Prioritization: Impact, Feasibility & Risk. If governance is a concern, route customer-facing copy through approvals while letting enrichment and tagging run autonomously. You’ll bank speed, consistency, and coverage within 30–60 days—and build the case to scale.
Generic automation improves steps; AI Workers add capacity that continuously adapts content, assets, and feeds to how people actually search—with voice, with cameras, and inside AI-curated experiences.
Most “AI features” still stop at suggestions, leaving humans to stitch steps together. That model fails when the surface area explodes: more FAQs, more how-tos, more image angles, more schema updates, more feed fields. AI Workers flip the equation: they execute end to end, with memory, reasoning, guardrails, and audit trails. In a world where Google reports surging Lens usage and AI Overviews affect what people see first, the cost of slow follow-through rises daily. The companies that win won’t just understand multimodal intent—they’ll operationalize it, turning content and product data into a living system that updates itself. That’s how you truly do more with more.
If you’re ready to turn voice-and-visual intent into measurable pipeline—without adding headcount—let’s map your 60-day plan across schema, feeds, image variants, speakable answers, and AI surfaces.
Voice and visual search aren’t “future trends”—they’re here, reshaping discovery flows and ad inventory now. Your playbook is straightforward: structure content for answers, enrich product data for identification, expand image coverage for Lens, and evolve KPIs for AI-curated surfaces. Then scale the work with AI Workers that execute—so you can reallocate human time to strategy, creativity, and innovation.
For deeper dives on execution systems and safe scaling, explore how to deliver AI results (not AI fatigue), learn to ship no-code AI automation fast, and consider upskilling your team to lead the AI workforce you’re building.
No, but they expand SEO into multimodal optimization that relies more on structured data, concise answers, image quality, and feed health—plus measurement that values impressions and eligibility in AI surfaces.
Often yes for simple queries; however, visibility and ad opportunities in AI Overviews and Lens increase if your content and feeds are optimized, and many buyers still click for depth, price, and trust.
Ship a 60-day plan: top 50 FAQs with speakable answers, schema and PDP/feed cleanup for top 200 SKUs, image variant expansion for Lens, and local profile fixes—executed by AI Workers with approvals where needed.
Sources and further reading: