Webinars
Speakers: Chris Leone, Kristin Harrison, Nick D'Amato
AI tools now sit at the start of the member journey. ChatGPT passed one billion monthly users this summer, Google AI Overviews appear on roughly half of all searches, and about half of Google searches end without a click to another site. In this session, Geear CEO Chris Leone and SEO/GEO lead Nick D'Amato, moderated by Director of Business Development Kristin Harrison, explain how large language models (LLMs) find and recommend credit unions, what Geear's tracking data shows, and how to measure visibility when clean attribution is no longer an option.
1. SEO still matters because LLMs rely on search results.
When ChatGPT, Gemini, or another LLM can't answer from its training data, it searches Google and Bing. Free ChatGPT users trigger web searches more often than paid users, so weak search visibility leads to weak AI visibility.
2. One prompt becomes several searches.
LLMs split a question into multiple sub-searches, a process called query fan-out. In a live demo, a question about first-time mortgages at a Memphis credit union produced four searches. Three named specific credit unions the model already associated with Memphis.
3. The goal is to become a consensus brand.
Your position in an AI answer is hard to predict from one prompt to the next. Whether you appear at all is much more consistent. Once an LLM associates your brand with a topic, it goes directly to your site for current details like rates.
4. Location and product type shape credit union visibility.
Geear tracks 30+ prompts per credit union across more than a dozen clients. The data shows:
The best place to start: checking, auto loans, and local relevance.
5. Product pages are among the most cited pages for credit unions.
Use them to explain what makes you different, including how you compare to banks, member testimonials, and community involvement. Add schema, write descriptive titles, URLs, and meta descriptions, and make conversion easy, since every organic visitor counts more as traffic declines.
6. Freshness counts.
In one report Geear reviewed, 75% of cited pages had been updated within the past year and 88% within two years. Revisit your most competitive pages every three to four months.
7. Off-site reputation is back in play.
LLMs check reviews, social media, and local mentions to confirm what your website says. Local PR, reviews, and community coverage strengthen the connection between your brand and your market.
8. Change how you measure impact.
LLM referral data in Google Analytics is incomplete. Many AI-influenced visitors land in direct traffic or search your name later. Track these instead:
9. Track AI visibility by segment, not by single prompts.
Tools like Gumshoe and HubSpot's AEO tool show whether your brand is mentioned (named in the answer) or cited (your page linked). Group prompts by persona and product to spot trends, and include your city and state in each prompt, since these tools don't search from your location.
10. Schema shouldn't slow your pages.
From the Q&A: schema is lightweight. If product pages load slowly, look at large images, video, or interactive elements. Speed matters because an LLM may skip a slow page during a fan-out search.
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