All case studies

    Generative Engine Optimization · Performance materials (anonymized)

    From uncited to the preferred answer in AI.

    A performance materials component supplier — a category leader in phase change materials for bedding, foam, and fabrics — was invisible when buyers, formulators, and OEM product teams asked LLMs which supplier to use. Wishbone rebuilt the brand's generative footprint. Within a quarter it was showing up as the preferred solution across every major answer engine.

    The engagement

    AI & GEO consulting for a performance materials supplier.

    Situation

    Buyers and formulators increasingly start their supplier research inside ChatGPT, Gemini, Claude, and Perplexity — not Google. When we ran the baseline, the client was not being cited in any of them for its own category. Competitors' claims and older third-party summaries were filling the answer window. Category leadership on the ground wasn't translating to category leadership in the models.

    What was broken

    • • Corporate site had thin structured data and weak entity definition — LLMs couldn't confidently attribute the brand's claims.
    • • Technology and product pages read like brochureware, not extractive answers.
    • • Almost no coverage in the press-syndicated outlets that ChatGPT, Gemini, Claude, and Perplexity actually trust as sources.
    • • No monitoring — the team had no idea what the models were saying, or which sources they were pulling from.

    What we did

    1. 01

      Ran a full generative visibility baseline across ChatGPT, Gemini, Claude, Perplexity, Google AI Overviews, and Copilot for buyer-intent prompts ("best PCM supplier," "phase change materials for bedding and foam," competitor comparison queries). The brand was effectively uncited — competitors owned the answers.

    2. 02

      Rebuilt the technical foundation for AI retrieval: structured data (Organization, Product, FAQ, Article schema), clear entity definitions on the corporate site, and canonical product/technology pages engineered for extractive answers.

    3. 03

      Executed a press-syndication and third-party citation program — placed technical announcements and product news in industry-syndicated outlets (trade press, industry magazines, financial newswires) so the brand's claims were being repeated by sources the LLMs trust and crawl.

    4. 04

      Set up an ongoing GEO monitoring loop: weekly prompt tracking across all six engines, citation source auditing, and content refreshes tied to which passages were actually being cited.

    Results

    Uncited → Cited

    Across ChatGPT, Gemini, Claude, and Perplexity

    Within one quarter

    Preferred solution

    Named in AI Overviews for category queries

    Google AI Overviews + Copilot

    Syndicated sources

    Cited by press-tier outlets the LLMs trust

    Trade + financial newswire coverage

    The brand moved from invisible to consistently cited across every major generative engine — and in several buyer-intent queries, it's now named as the preferred solution, with the models pulling directly from press-syndicated coverage the Wishbone program placed.

    Where the brand now shows up

    ChatGPTGeminiClaudePerplexityGoogle AI OverviewsCopilot

    Get started

    Want to be the answer in ChatGPT, Gemini, Claude, and Perplexity?

    Book a 15-minute intro and we'll walk you through where you're being cited today — and where you're not.

    Or send a quick brief

    Open contact form