After beginning a structured AEO program in July 2026, a metal plating company moved from little measurable presence in AI-generated answers to the leading position in its tracked competitive set. Meaningful gains appeared within two weeks of the first content rollout.
Results at a Glance
Across the measured period, the company ranked first on all five tracked AEO metrics. Its nearest competitor trailed by a wide margin in every category.
Metric | Metal plating company | Nearest competitor | Relative lead |
|---|---|---|---|
Visibility score | 31.7% | 12.0% | 2.6 times |
Mentions | 10,429 | 3,493 | 3.0 times |
Citations | 19,870 | 5,930 | 3.4 times |
Citability | 9.8% | 2.9% | 3.4 times |
Share of voice | 59.8% | 19.8% | 3.0 times |
Period-wide dashboard results across ChatGPT, Perplexity, Gemini, Google AI Overviews, Claude and Microsoft Copilot. Relative leads compare the company with the second-ranked competitor.
The B2B Search Challenge
Before the AEO program began, the company had little measurable visibility in the AI answers associated with its priority services. Most of June remained at or near zero across the tracked metrics, with only limited late-month movement before the July program launch.
That absence mattered because specialized B2B searches often happen early in the lead generation process. Engineers, procurement teams, OEMs and Tier 1 suppliers use detailed questions to identify capable vendors, compare technical processes, assess production capacity and find solutions to manufacturing problems. If a supplier is missing from the generated answer, it may never enter the initial consideration set.
This behavior is not limited to people who intentionally open an AI assistant. Google AI Overviews can place generated answers directly above traditional search results, so a prospect may use AI-assisted search without thinking of it as an AI interaction. The company needed its expertise to appear wherever prospective companies were forming a shortlist.
The AEO Strategy
The program began by tracking the questions that qualified prospects were likely to ask across six answer engines. Those prompts guided a steady publishing program of 15 original, client-approved articles each month.
Prompt Categories
- Direct supplier discovery, including searches for leading high-volume metal plating companies in the Midwest
- Automotive and Tier 1 supplier questions
- Specialized processes and capability questions
- High-volume production and scalability questions
- Problem-solving and consultation questions, such as how to reduce lead times in OEM metal finishing and plating
Content Development
Each article answered a specific tracked question with enough technical detail to be useful to a serious B2B buyer. The content focused on the company’s capabilities, applications and problem-solving knowledge rather than broad keyword coverage. Every article went through client review before publication, protecting technical accuracy while maintaining a consistent production cadence.
Distribution Across Relevant Platforms
The team distributed each content theme beyond the company website through Google Business Profile, Medium, LinkedIn articles and posts, and relevant Reddit discussions when an authentic contribution made sense.
This distribution expanded the number and variety of places where answer engines could encounter the company’s expertise. The website served as the primary owned source. Google Business Profile reinforced current business information within Google’s ecosystem. LinkedIn and Medium extended the content onto established publishing platforms that can surface in search and provide additional context around the company’s subject expertise. Relevant Reddit participation addressed questions in the language people use during peer research, without forcing a promotional mention where it did not belong.
No single channel guarantees inclusion in an AI answer. Together, however, these touchpoints made the company’s expertise easier to discover, understand and associate with the tracked topics.
Performance After Launch
The first meaningful improvements appeared in less than two weeks after the initial content distribution. The company has since maintained the top position across the measured competitive set.
Visibility
The company’s period-wide visibility score reached 31.7%, compared with 12.0% for the nearest competitor. Daily visibility rose to nearly 50% by September 18, while the three competitors shown in the analysis remained below 20%.
Share of Voice
The company captured 59.8% of tracked share of voice for the measurement period. The nearest competitor captured 19.8%, giving the company approximately three times the share of its closest rival. Although daily results fluctuated, the company held a clear lead throughout the post-launch period.
Mentions and Citations
The tracked models generated 10,429 mentions of the company and 19,870 citations connected with the monitored prompts. The nearest competitor recorded 3,493 mentions and 5,930 citations. This placed the company at roughly three times the nearest competitor for mentions and more than three times its citation count.
Citability
Citability reached 9.8% across the measured period, compared with 2.9% for the next-ranked company. The daily trend continued to strengthen through September, rising above 16% at its peak and ending just below 15%.
Website Traffic From AI Models
Website analytics also began recording visits from AI platforms. That traffic provides an important bridge between visibility and action: the company was not only appearing in generated answers, but also earning visits from people who wanted to investigate its capabilities further.
Why the Program Gained Traction
The results align with three practical choices. First, the program started with real buyer questions rather than a generic list of keywords. Second, it supplied technically specific answers at a consistent pace. Third, it distributed those answers across owned, professional and community platforms where search engines and answer engines could encounter supporting context.
The outcome was a broader and more consistent digital footprint around the exact topics that mattered to the company’s prospective customers.
What This Means for B2B Companies
AEO gives specialized B2B companies a way to compete for visibility before a buyer reaches a vendor’s website. The opportunity is especially important in technical industries, where buyers ask detailed questions about capacity, certifications, materials, processes and production challenges.
This case shows that meaningful movement can happen quickly when content is built around high-intent questions and distributed consistently. It also shows why AEO performance should be evaluated across several signals. Visibility, mentions, citations, citability, share of voice and referral traffic together provide a clearer view than any single metric alone.
Measurement Notes
Results cover July 1 through September 18, 2026, using a defined prompt set and competitive set across six AI platforms. Dashboard totals and percentages represent performance within that tracked environment and may change as prompts, model outputs and answer-engine behavior change. The timing of the gains aligns with the AEO rollout, but the analysis is observational rather than a controlled attribution study.
Build Visibility in AI Generated Search
Digital Cheddar helps B2B companies identify the questions their buyers are asking, develop useful content around those questions and distribute it where search engines and answer engines can find it. Contact us to explore how an AEO program could strengthen your company’s visibility across traditional search and AI-generated answers.
