How Zing Credit Union improved its AI visibility by addressing competitors

Category: Credit Unions for Business Banking · Denver Metro
Platform: MetriFi GEO
Baseline Visibility: 66.67%
Achieved Visibility: 85.71%
Time to Impact: 2 days
Outcome: WIN

The challenge

Zing Credit Union offers business banking services in the Denver Metro area like checking accounts, lending, treasury management and are competitive with any option in the market. But when local business owners turned to AI tools like ChatGPT to ask “what are the best credit unions for business banking in Denver?”, Zing wasn’t consistently showing up in the answer.

This is an increasingly common problem for financial institutions. AI assistants don’t pull from paid listings or social profiles. Instead, they synthesize information from content that exists on the web. If a credit union isn’t represented in that content, it doesn’t get mentioned. And if it doesn’t get mentioned, it effectively doesn’t exist in that moment of discovery.

MetriFi GEO was used to measure the baseline: how often was Zing appearing in AI responses to Denver business banking queries? The starting point was 66.67% — meaning Zing was getting mentioned in roughly two out of every three relevant AI responses. Good, but not consistent. The goal was to close that gap.

The insight that shaped the approach

The instinct for most organizations when thinking about content is to lead with their own story. Talk about your strengths, your products, your differentiators. Minimize or ignore the competition.

This experiment suggests that instinct may work against AI visibility.

AI tools are built to give users complete, trustworthy answers, not brand pitches. When someone asks an AI assistant which credit unions are best for business banking in Denver, the AI is likely to name multiple institutions. It will often mention Bellco, Ent, and Elevations Credit Union because they are legitimate answers to the question. Content that acknowledges those institutions may appear more comprehensive than content that omits them.

In this experiment, the more effective approach was to create honest, comprehensive content that covered the category, including where competitors were strong, while positioning Zing accurately within it. The results suggest that when AI systems looked for sources related to the category, this balanced content was more likely to support mentioning Zing alongside other relevant institutions.

What was done

A long-form article was published covering business banking credit union options in the Denver Metro area. It named and described Bellco, Ent, Elevations, and Zing, covering each institution’s relevant strengths for business members, such as branch access, account structure, and local market presence.

Zing was included honestly. Where it was competitive, that was stated specifically. Where others had an edge in a particular area, that was acknowledged too.

The content was structured to match how AI systems commonly process and cite information, using clear factual claims, institution-specific details, and named local context. There were no superlatives without backing and no vague differentiators.

MetriFi GEO tracked the visibility scores before and after the content was published.

The result

Within two days of publishing, Zing’s AI visibility in Denver business banking queries increased from 66.67% to 85.71%, an improvement of roughly 19 percentage points. That’s the difference between appearing in two out of three AI responses and appearing in six out of seven.

The visibility increase occurred quickly after publication. One possible explanation is that AI systems were able to discover and reference the new content soon after it became available. However, this experiment was not designed to isolate the specific mechanism behind the improvement, so the observed increase should be interpreted as an association rather than definitive proof of causation.

What this experiment demonstrates

Mentioning competitors can be an effective strategy for AI visibility. In this case study, AI visibility improved after publishing balanced, comparative content that acknowledged multiple institutions within the category. While this experiment does not prove that including competitors alone caused the improvement, it suggests that comprehensive, category-focused content may increase the likelihood of being mentioned alongside other relevant organizations.

AI visibility is measurable. MetriFi GEO establishes a baseline, runs prompts against AI providers, and measures changes over time. This experiment produced a measurable improvement in visibility within the testing window.

In this case, visibility changed much more quickly than is typical for traditional SEO. The results suggest that AI visibility may respond more rapidly to newly published, relevant content, although additional testing would be needed to determine how consistently this occurs across different organizations and topics.

Specificity matters more than volume. One well-structured, locally relevant article moved the needle. The content didn’t need to be exhaustive. It needed to be accurate, specific, and useful to someone genuinely trying to answer the question.

A note on what this doesn’t tell us

This experiment ran over a short window with a limited number of AI prompt responses. The result is directionally significant but not a guaranteed permanent lift. AI visibility requires ongoing content. As more institutions publish more content, the landscape shifts. A single article establishes a position. Maintaining it requires continued effort.

Because this was a single experiment, we cannot conclude that including competitors alone caused the improvement. Other factors, including normal variation in AI responses, model updates, or other changes occurring during the testing period, may also have contributed to the observed increase.

MetriFi GEO is a measurement and content experimentation tool. It shows what’s working and what isn’t. The strategic decisions, including what to publish, how to frame it, and which category questions to target, still require judgment and knowledge of the institution.