Credit Unions, How’s Your AEO? A Discoverability Diagnostic for the AI Era

The Humble FAQ Page Finally Gets Some Respect

FAQs are one of the most natural vehicles for citable chunks, but many institutions are not using them to their full advantage. The original purpose of a “frequently asked questions” page was to answer the questions people are most likely to ask. In practice, this has left many FAQ pages focused on housekeeping and directing traffic — questions like “How do I change my password?” or “Where can I download my tax forms?” While those are useful, the biggest AEO opportunities are found in product and service questions.

It helps to think about how people interact with different tools. A traditional search query might be “best CD rates.” An AI prompt, however, might sound more conversational: “What CD rate should I expect from a credit union right now, and how does that compare to a big bank?” FAQs written to match real questions can meet the needs of both types of search query.

Each FAQ response should follow the citable chunk model: restate the question, provide a clear answer, and include a supporting fact or explanation. Institutions should also move beyond the standard practice of providing a single global FAQ page. Each product or service page should include its own FAQs. Members researching auto loans will have different questions than those exploring home equity products.

To shape these questions, evōk encourages institutions to refer to their own conversations with members. “If you find that a lot of your members have the same sets of questions about your checking product,” Sifonte said, “that’s where your FAQs have to be.”

Ask yourself: Are your FAQs written the way a member would naturally ask a question, or the way a marketing team might phrase it in an internal discussion?

Schema Markup: The Bridge Between SEO and AEO

Schema markup is structured code that helps machines understand what a page contains. While users never see it, schema significantly influences how machines read your pages.

For AEO, the most relevant types are FAQ schema and Q&A schema. When implemented correctly, these structures clearly signal the relationship between a question and its answer. This allows AI systems to quickly locate the content they need without having to interpret large blocks of text.

Schema can also help resolve the perceived conflict between content produced for SEO and content produced for AEO. SEO traditionally rewards depth and comprehensive coverage, while AEO favors concise answers. A well-structured page can support both. For example, a 2,500-word educational article with properly implemented FAQ schema can satisfy Google’s preference for depth while also providing AI engines with clearly labeled answers they can easily extract.

Ask yourself: When was the last time your marketing and tech teams reviewed your site schema together?

Don’t Neglect Your Existing Content

Most institutions have years of content already published, including blog posts and articles, educational resources and explainers, and traditional marketing material. Each category reflects marketers’ evolving ideas about what consumers and members need or want. And much of it was written for a different search environment.

Adapting to AEO does not require ripping all of that out. Instead, prioritize updating and restructuring it. Start with content that already performs well. A 2022 article about debt consolidation, for example, can be made more AEO-friendly by adding a callout — a citable chunk — that highlights a clearly framed question, a direct answer, and a supporting statistic.

Speaking of statistics, including credible data can increase authority with AI platforms. But note that such data does not have to originate with the institution itself. Citing reputable sources, such as Federal Reserve data or industry research, can strengthen credibility while increasing the likelihood of citation. When an AI system surfaces a response that includes the data within your structured answer, your institution may still be credited as the source.

Ask yourself: Do you know how your website content is organized and when it was last reviewed or updated?

Measuring AEO: An Emerging Discipline

Until recently, AI engines were pretty much black boxes for marketers. Organizations could test prompts and observe responses, but they had limited insight into how often their brand appeared relative to competitors. But that’s increasingly changing as AI platforms have made APIs available for third parties to process anonymized answer engine data.

Today, marketers can begin measuring indicators such as citation frequency, citability scores, and share of AI voice. In simple terms: how often does an AI engine name your institution when it answers questions relevant to your products and markets?

“You shouldn’t be making decisions about content without understanding how you show up,” Sifonte said. Tools such as SEMrush now aggregate AI answer data to help marketers identify which questions trigger citations, how frequently brands appear, and where competitive gaps may exist.

Ask yourself: Are your marketing, sales, and product teams discussing how your institution appears in AI-generated answers?

As AI search continues to evolve, institutions that maintain strong discoverability will likely be those that clearly articulate their strategy and map their messaging to their target segments. Great content will continue to matter, but in a way that’s closer to what it was always supposed to be: useful and direct, aligned with what consumers are actually interested in. Institutions that pay attention to what current and prospective members are seeking and why will have the advantage.