The Challenge
Buyers no longer start on Google alone. They ask ChatGPT, Perplexity and Google AI Overviews things like window replacement cost or best windows for a cold climate. This client was never mentioned in those answers, and on top of that they were quietly losing classic organic ground too.
We audited the content for both Google and the AI engines, and the reasons were clear. Neither had anything to grab:
- Content was thin and read like a product brochure
- There was no FAQ content and no structured data
- No comparison content existed for the choices buyers weigh
- Nothing was written in the answer-shaped way AI engines can quote
- There was no interactive tool to earn engagement or citations
The Solution
We improved the same fundamentals across search experiences: useful answers to buyer questions, crawlable comparison guides, accurate pricing context, valid structured data, and a custom estimator. AI visibility and organic performance were measured separately.
- Answer-first content for real buyer questions
- FAQ, Product and LocalBusiness schema
- Writing shaped the way AI engines quote
- An interactive window cost estimator
- Comparison guides like vinyl vs fiberglass
- Double vs triple pane explainers buyers search
- An llms-friendly content structure across the site
- AI-visibility tracking to see where we appeared
Content organized around real buyer decisions
We replaced vague brochure copy with concise answers, assumptions, comparisons, and supporting detail for questions buyers actually ask. The format made the pages easier to scan and created clearer passages for search systems to interpret, without guaranteeing selection or citation.
- Answer the question up top: each page begins with a direct answer, then explains assumptions and trade-offs so the short passage remains accurate when read on its own.
- Structured accurately: FAQ, Product, and LocalBusiness markup was used only where it matched visible content and the actual entity. It provided context, not a citation promise.
- Comparison content: guides like vinyl vs fiberglass and double vs triple pane match the exact comparisons buyers ask AI about, so we show up in those answers.
- One clear entity: consistent naming and structure give the engines a business they can trust and attribute, which is what turns a mention into a citation.
A cost estimator that earns engagement and links
Buyers want a ballpark price before they talk to anyone, and a tool that gives it earns time on site and links that both Google and AI engines notice. We built one and wired it into the wider SEO plan.
- Instant price range: visitors configure window type, size and options and get an instant estimate, so the highest-intent question gets answered on the page.
- First-party utility: the estimator answered a high-intent pricing question and supported qualified inquiries. Engagement was treated as a usage metric, not a direct ranking claim.
- A reason to link: a genuinely useful estimator earns links and mentions, which builds the authority that lifts organic clicks.
- Documented price context: the supporting content states assumptions behind each range, giving visitors and search systems more complete information than a number alone.
How We Did It
01. Question research
Mined the real buyer questions people ask Google and AI engines about windows, doors and cost, using Semrush and answer-engine research.
02. Answer-first content
Rewrote key pages to lead with concise, quotable answers to those exact questions.
03. Schema injection
Added valid FAQ, Product, and LocalBusiness structured data where it matched the visible content, then tested the markup independently from AI citation checks.
04. Comparison guides
Built comparison content like vinyl vs fiberglass and double vs triple pane to match how buyers weigh their options.
05. Calculator and tracking
Built the interactive cost estimator and set up AI-visibility tracking to measure where the brand appeared.
The Results
Repeated tests began showing the client in some AI answers and Google AI Overviews for the documented buyer questions. Organic clicks rose about 110% over the same period, while estimator use and earned links were recorded as supporting outcomes rather than proof that one channel caused another.
| AI answer citations | Gained for target questions |
| Organic clicks | +110% |
| Cost estimator engagement | Strong |
| Build time | 3 to 6 Months |
Services & tools used: SEO and AEO audit, schema markup (FAQ, Product, LocalBusiness), comparison content, custom calculator, and Semrush.
seo and aeoAI visibility was treated as an observation, not a permanent rank
Repeated prompt tests showed where the company appeared during the reporting period. Organic clicks and AI citations were monitored as different outcomes because neither guarantees the other.
- Record the platform, prompt, location, and test date for every citation check.
- Keep prices, specifications, and comparison content current.
- Use structured data for clarity and eligibility, not as a citation promise.
Frequently Asked Questions
How we verified organic and AI-search visibility
Two visibility datasets were reviewed
Traditional performance was checked through organic click trends and engagement with the cost estimator. AI visibility was checked separately by repeating the target buyer questions and recording whether the company appeared as a cited or named source in the returned answers.
Why AI citations require ongoing checks
AI answers can change by platform, model, location, wording, and date. The citation examples and 110% organic-click increase describe the observed period, not permanent placement. Organic growth and AI mentions should be monitored separately because one does not guarantee the other.
Editorial review: Gilmedia strategy team. First published August 6, 2026.
Primary references
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Services in this project: SEO · AI Search Optimization

