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GEO Performance Case Study: Increasing AI Visibility for an Arizona Credit Union

Geear’s Inbound team partnered with an Arizona credit union to increase its visibility in large language models (LLMs). Using deep audience persona research through Gumshoe and SparkToro, we identified where AI responses under-represented the credit union and prioritized the highest-impact fixes. After homepage optimization, the credit union saw a 116% increase in average AI visibility and a 112% increase in average AI mentions.

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The Strategy

Our Hypothesis

We’ll increase LLM visibility by leveraging deep audience persona research through Gumshoe and SparkToro to:

  • Understand the Audience

    Learn how target members use LLMs to research financial products.

  • Assess AI Perception

    Identify how major LLMs currently perceive and represent the credit union.

  • Prioritize Tactics

    Recommend changes aligned with identified visibility gaps.

  • Implement Quickly

    Accelerate implementation by focusing on the highest-impact opportunities.

What We Implemented

Based on the research, we rolled out three GEO optimizations and measured each one through an AI traffic report and AI search visibility tracking:

Footer optimization: results measured June 23 to August 22, 2026

Homepage optimization: results measured September 1 to October 13, 2026

AI instructions page: early data tracked with the HubSpot AEO tool

Optimization 01

Footer optimization

Jun 23 – Aug 22, 2026

AI traffic report

+9%

Sessions

+16%

Users

+23%

New users

+29%

Engagement rate

+207%

Key events

+62%

Event count

+251%

Avg. session duration

AI Search +31%avg. AI visibility+31%avg. AI mentions

Optimization 02

Homepage optimization

Sep 1 – Oct 13, 2026

AI traffic report

+24%

Sessions

+24%

Users

+19%

New users

+3%

Engagement rate

+64%

Key events

+190%

Event count

+25%

Avg. session duration

AI Search +116%avg. AI visibility+112%avg. AI mentions

Optimization 03

AI instructions page

Important: too early to gauge real results, but here’s early data

HubSpot AEO Tool

ChatGPT Visibility:

Jumped from a 5%–7% baseline (during the period 9/06 to 9/27) to 25.3% on 10/4.

Gemini Visibility:

Climbed to 28% on 10/4, showing a parallel surge in discovery.

It’s worth noting that Gemini visibility in HubSpot keeps increasing progressively, without the high volatility we normally see in AI visibility, where the visibility goes up and down with every run.

Why We Believe This Worked

We believe the results were driven by our ability to identify specific gaps in the credit union’s LLM visibility and develop targeted recommendations based on actual audience research.

Rather than relying on broad GEO best practices, we focused on the opportunities most relevant to the credit union’s target audience and implemented improvements quickly, contributing to stronger visibility in AI-generated responses.

→ Audience insights

Understand how prospective members research products in LLMs.

→ Visibility gaps

Identify where AI responses under-represent the credit union.

→ Focused execution

Implement recommended tactics quickly.

Where We Go Next

Early results provide a foundation for refining our GEO strategies and establishing repeatable performance benchmarks.

Monitor: Track LLM visibility to identify which GEO tactics have the greatest impact.

Benchmark: Establish consistent performance measures for future GEO initiatives.

Connect to outcomes: Work toward connecting AI visibility gains to website traffic and conversions.

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