The Rise of Conversational Search

The last decade has seen a seismic shift from keyword‑based queries to natural‑language interactions. Today, users often ask a smart speaker or a chat interface for product recommendations, and the assistant’s response becomes the new SERP. In that context, a brand’s visibility is no longer measured by Google rankings alone but by its presence in the recommendation lists of the most popular large‑language models (LLMs).

Enter SpottedBy.AI

SpottedBy.AI positions itself as the first tool that quantifies that visibility. The service crawls a brand’s website, generates a library of relevant prompts, and queries five major LLMs—ChatGPT, Gemini, Claude, Perplexity and Grok—to determine where the brand appears in their recommendation lists. Results are delivered in under thirty seconds, with a dashboard that tracks historical performance, competitor positioning and geographic variations.

How It Works

  1. URL Submission – A user pastes the brand’s homepage and selects a target location. No account is required for a quick test.
  2. Prompt Generation – The system creates search queries tailored to the brand’s industry and product catalog.
  3. Real‑Time Analysis – Each LLM is queried in parallel; the tool records the rank of the brand’s link in the assistant’s recommendation list.
  4. Insights Dashboard – Users can view current rankings, compare against competitors, and monitor changes over time.

The process is transparent: the tool does not scrape the assistants’ internal data but relies on the public API responses that the assistants return to the user.

Why Traditional SEO Is Insufficient

Search Engine Optimization has long focused on keyword density, backlinks and site architecture. While those factors still matter, conversational assistants use proprietary ranking algorithms that prioritize relevance, user intent and conversational context. A brand that ranks well on Google may still be invisible when a user asks, "Which electric bike should I buy for city commuting?" The assistant’s recommendation list is the new “top‑five” that drives click‑through.

Implications for Developers and Marketers

  • Content Strategy – Optimizing for AI assistants means crafting FAQ‑style content, structured data and concise product descriptions that align with typical user queries.
  • Performance Monitoring – Real‑time dashboards allow teams to react quickly to changes in assistant algorithms or competitor activity.
  • Geographic Targeting – Since assistants can surface region‑specific recommendations, brands can tailor messaging for local markets.

A Case in Point

A mid‑size outdoor gear company used SpottedBy.AI to benchmark its visibility against five competitors. The dashboard revealed that while the company’s Google ranking was 12th for "mountain hiking boots", it appeared only in the third slot of ChatGPT’s recommendation list for the same query. Armed with that insight, the brand revised its product pages to include clearer call‑to‑action phrases and updated its FAQ section. Within a month, the brand’s ChatGPT recommendation rank improved to first place.

Looking Ahead

As LLMs evolve and new assistants enter the market, the need for visibility tracking will only grow. Tools that can translate conversational intent into actionable SEO strategies will become indispensable. For developers building AI‑integrated products, understanding how content surfaces in assistants will inform everything from API design to user experience.

“AI assistants are becoming the primary discovery channel for consumers. Brands that ignore this shift risk falling behind.” – Product Lead, SpottedBy.AI

Source: SpottedBy.AI (https://www.spottedby.ai/)