Early results at a glance
in AI visibility among tracked brands
AI visibility growth (from baseline)
Increase in Generative AI Conversions (Quarter over Quarter)
AI Visibility (Across LLMs)
About our client
Our client is a large benefits and supplemental health carrier serving employers and brokers across dental, vision, life, disability, accident, paid family and medical leave, and absence management.
Scope of work: AI Search Optimization, SEO strategy, technical optimization, content strategy and production, prompt and LLM analysis, reporting, and integrated communications support.
Background
As AI-generated answers began influencing how benefits providers are discovered, the company faced a visibility challenge that traditional search reporting did not fully capture.
Its offering was broad, but the story was not yet organized around the practical questions brokers and employers ask when they compare carriers, evaluate administration, or look for a partner that can simplify benefits decisions. Competitors were already appearing in AI answers and citations, while the company’s own content was underrepresented in the source set.
The opportunity was to make the company easier for both people and AI systems to understand: not simply as a provider with a large product portfolio, but as a clear, credible, broker-focused partner with a distinct point of view.
Goals
- Establish a measurable baseline for AI visibility, source usage, and AI-referred activity.
- Expand presence across high-intent broker, employer, and member prompts.
- Build a repeatable owned-content system that AI engines could retrieve and cite.
- Clarify the company’s differentiation through plain-English, decision-stage content.
- Connect AEO, SEO, technical improvements, and communications around the same authority themes.
The method
Start with prompt and source analysis
Avenue Z analyzed 100 AI prompts across ChatGPT, Google AI Overviews, and Perplexity, reviewing 43,087 citations to understand where the company appeared, where it was absent, and which content formats AI systems favored.
The analysis showed that owned content was central to the category’s answer ecosystem. Product pages, articles, and listicles represented the majority of cited URLs, creating a clear opportunity to improve the company’s own source footprint rather than relying on brand mentions alone.
Build a broker-focused content engine
The team prioritized content around the questions most relevant to brokers and employers, including how to choose an ancillary carrier, how integrated benefits work, how to switch providers, and how a carrier’s technology and service model affect the buying experience.
That strategy produced a repeatable library of answer-first guides, FAQs, and supporting page improvements. The New Broker Playbook and A Broker’s Guide for Mid-Sized Employers became recurring leaders in LLM retrievals, showing that the program was building authority across multiple owned assets rather than one isolated page.
Make the digital story easier to retrieve
Avenue Z refined high-impact owned pages, including the homepage, brokers page, broker FAQs, employers page, and members page. The work focused on clearer differentiation, structured answers, stronger internal relationships between pages, and a more consistent explanation of why the company was a credible choice.
Performance was tracked through AI visibility, source usage, retrievals, organic search, and AI-referred activity. This created a feedback loop for deciding which topics to expand, which pages to improve, and where visibility was growing without equivalent click or conversion gains.
Extend authority through communications
AEO was supported by a broader earned, owned, and performance-media program. The same broker-centered narratives informed PR, social, and sales-support materials, helping the company present a more consistent story across AI answers, search results, and human conversations.
Results
The program moved from baseline measurement to measurable AI-search growth. AI visibility increased from 5% in January to 31% in September, a gain of 27 percentage points and more than six times the starting level. The company’s own website also became a much more frequent source in tracked AI answers: source usage increased from 5% in January to 54% in September.
AI-referred activity grew alongside visibility. The channel recorded 63 sessions and 43 conversions in February, the first month with complete data, and reached 86 sessions and 65 conversions in September. August reporting also showed 81 AI sessions and 53 conversions, with the company’s domain used as a source in 52% of tracked answers.
The content system was a meaningful part of that shift. In August, blogs accounted for three of the top five pages driving AI retrievals, reinforcing the value of broker-focused educational content as both a visibility asset and a source AI systems could use in answers.
Organic search performance was more mixed, which makes the distinction important: impressions increased in August while clicks and CTR declined. The program’s clearest gains were in AI visibility and source usage, while converting broader search exposure into clicks remained an active optimization opportunity.
The business impact and next step
Avenue Z helped create a clearer operating system for modern search by connecting broker-focused content, technical SEO, AI visibility measurement, and authority building. Results show stronger AI visibility and source usage, while click efficiency and share of voice remain areas to monitor.
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