CASE STUDIES

How Summit 2x-ed their AI Referrals in 2 Months

How Summit 2x-ed their AI Referrals in 2 Months

Summit is a startup insurance brokerage based in Kelowna, Canada. Despite competing against massive, entrenched competition, Summit doubled their inbound traffic from ChatGPT, Copilot, and other AI models in as many months.

Summit is a startup insurance brokerage based in Kelowna, Canada. Despite competing against massive, entrenched competition, Summit doubled their inbound traffic from ChatGPT, Copilot, and other AI models in as many months.

Keller Maloney

Unusual - Founder

Oct 7, 2025

Customer | Summit Insurance

Summit (summitcover.ca) is a modern Canadian brokerage providing custom commercial, liability, tech & cyber policies for businesses of every shape and size. Insurance buyers ask complex, high-stakes questions and often turn to AI chatbots for clarity before they ever talk to a broker. In these “trust-the-expert” markets (insurance, healthcare, legal/tax, cybersecurity, enterprise IT), earning citations and referrals from AI models is decisive.

Impact (first 2 months)

  • Doubled model-driven traffic (from AI chatbots) to Summit’s site.

  • 264 verified visits from AI crawlers to Summit’s AI-optimized reference/wiki pages.

  • Largest lift observed from Microsoft Copilot, despite Summit focusing optimization on ChatGPT, Gemini, and Perplexity. This is consistent with Copilot being powered by OpenAI-family models (e.g., GPT-4o) and grounded on Bing’s search index, which favored Summit’s structured reference pages. (Microsoft Learn)

The Challenge

Insurance decisions are multi-variable (coverage types, exclusions, riders, claims process, regulatory requirements). Prospects routinely offload that complexity by asking AI assistants questions like “Do I need Builder’s Risk or Course of Construction?” or “What does cyber liability actually cover?” Generic marketing pages rarely get cited; models prefer neutral, fact-dense, well-structured sources. Summit’s goal: become the authoritative, citeable answer for the exact questions their buyers ask AI.

Why Summit Chose Unusual (AI Relations)

Summit resonated with Unusual's "AI relations" approach to AI visibility rather than AEO/GEO. Unusual was founded on the idea that LLMs are not search engines, and convincing an AI model to refer more traffic looks more like PR than SEO. For more reading about how Unusual's approach differs from AEO/GEO, read our article on the topic.

What made Unusual stand out:

  • Full stack. Unusual handles the full AI optimization workflow, from analyzing model behavior to planning strategy to creating/recommending content to updating it when things change.

  • Action bias. Analytics are useless unless they help you make decisions.

  • No guesswork. Discover patterns and ground recommendations in data and analysis.

  • Information-rich. Unusual does create quality, narrative, human content, but rather an AI reference manual so models could reliably quote canonical facts.

What Summit Got

  • Model-ready reference pages for high-intent topics: Product overviews (e.g., Builder’s Risk vs. Course of Construction), Pricing & eligibility, Security & compliance posture, Integrations (certificates, payments), and Comparisons (“D&O vs. E&O”).

  • Page archetypes and schema: Article/FAQ/HowTo/CaseStudy JSON-LD; definitive summaries, datum-dense tables, and visible “last updated” notes.

  • Authority placements: curated third-party sources (industry directories, association explainers) that models already surface, each pointing back to Summit’s canonical page.

Why Copilot Spiked First

Copilot’s answers are powered by modern OpenAI-class models and grounded via Bing for web evidence; when Bing indexed Summit’s new wiki, Copilot began surfacing and citing it more often—producing an outsized lift relative to other assistants. In short: Summit optimized for LLM trust signals; Copilot’s Bing-grounded retrieval found that content fastest. (Microsoft Learn)

Results

  • 2× model-driven traffic in 60 days, led by Copilot exposure.

  • 264 AI-crawler hits to AI-optimized pages in the same period—evidence that assistants were actively discovering and evaluating Summit’s canon.

  • Early signs of higher-quality inbound: prospects arriving from assistant-cited pages demonstrated deeper engagement (longer reads, lower pogo-sticking) and booked calls with more specific coverage questions.

How Unusual’s AI Relations Program Works

  • Diagnose model reasoning: inventory current citations, missing facts, and query paths.

  • Publish neutral, reference-grade content: structured, citeable, fast.

  • Earn authority: place corroborating facts where models already look.

  • Maintain freshness: visible versioning and update notes (models weight recency).

  • Bridge to pipeline: add clear “next step” modules on cited pages (Pricing, Compare vs. X, Book a consult).

Why This Matters in “Trust-the-Expert” Industries

When consequences are real (claims denied, compliance risk, legal exposure), buyers seek expert guidance and defer to authoritative sources—human or model. Insurance behaves like healthcare, legal/tax, cybersecurity, and enterprise IT: the source of truth wins the lead. AI assistants have become the new front desk; if they cite you, they effectively refer you.

“We made sure AI assistants found the right facts. Once our reference pages were live, agents started citing Summit, and qualified conversations followed.”

— Davis Gilbert, Founder & Managing Partner, Summit

About Unusual

Unusual is the leading AI Relations platform. The platform helps enterprises drive traffic from AI models by building model-ready reference content and placing corroborating evidence where assistants already look. Book a demo at unusual.ai.

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Last year, over 700 million conversations happened across AI chatbots about purchasing products. Those weren't searches—they were consultations. Something fundamental is shifting in how people make buying decisions, and it looks a lot less like googling and a lot more like asking a trusted friend for advice.

INSIGHTS

AI Models Are Becoming Influencers

Last year, over 700 million conversations happened across AI chatbots about purchasing products. Those weren't searches—they were consultations. Something fundamental is shifting in how people make buying decisions, and it looks a lot less like googling and a lot more like asking a trusted friend for advice.

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INSIGHTS

The End of Second Place: Why ChatGPT Recommendations Are Winner-Take-All

The shift from Google Search to ChatGPT as a personal, buying assistant means a shift from a ranked list of results to a single recommendation. For brands, this means that there is no "second place" when it comes to getting recommended by ChatGPT. Brands need to ensure that AI agents can find the specific information that they need to make a recommendation.

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INSIGHTS

The Web Is for Machines Now

The web is quickly becoming infrastructure for bots and AI agents to interact with the world (gather information, take actions like purchases). At the same time, human attention is in the middle of the greatest migration since its first migration online. We can assume that these trends are going to continue.