Search is no longer a single act performed in a single place. People speak queries to voice assistants in their kitchens, photograph products they want to buy, and get answers from AI platforms before they ever visit a brand’s website. Each of these behaviours is a search – and each follows a different set of rules. Brands still thinking in terms of keywords and rankings are optimising for a version of search that’s already being replaced.

Voice search has moved past novelty. In India, Swiggy and Zomato support voice-enabled reordering. Domino’s India allows customers to place orders through voice commands. For brands, this means the structure of content matters as much as the content itself. Conversational, question-based phrasing – written the way people actually speak – is what voice assistants pull from. Structured data helps AI systems understand context without ambiguity. The brands cited in voice responses are the ones that wrote answers, not copy.

Visual search is following the same trajectory. Myntra’s image search lets shoppers upload a photo and surface similar products instantly. IKEA’s app matches furniture from a real-world photo to items available in-store. Google Lens and Pinterest have trained users to expect this experience everywhere. For this to work, product images need high-quality visuals, accurate alt text, and clean metadata – not for aesthetics, but because that’s how AI classifies and recommends what it sees.

The most effective discoverability strategies today are multi-modal. They combine SEO fundamentals with GEO frameworks, voice-optimised copy, and image metadata – all working together so AI systems can understand and surface a brand across every channel where search happens. At The Social Lions, we build these systems using social listening data from Reddit and Quora to understand how audiences actually talk, so the content we create is written in the language AI learns from.