Generative engine optimization services for better AI visibility

Answer engine optimization, or AEO, and generative engine optimization, or GEO, describe overlapping work to improve visibility in generated answers. The useful question is what needs to change so your business is represented accurately and your content can serve as a credible source.

A citation, a brand mention, and a recommendation are different outcomes. An assistant can link to a useful article without recommending the company behind it. A brand can also be mentioned without a link. I keep those outcomes separate when setting priorities and reporting progress.

The platforms differ too. Google AI Overviews, ChatGPT Search, and other answer engines do not produce identical answers or draw on exactly the same sources. A single response is a snapshot, not a permanent ranking.

I map the questions people ask when they are discovering a problem, comparing providers, and deciding what fits their situation. Those questions should reflect your actual services, audience, geography, and strengths.

The initial research looks at whether your business appears, which competitors or sources are visible, what the answers say, and which parts of your own site support those subjects. Content and competitor gaps are considered together.

This creates a practical starting point. If an assistant cannot understand what you offer, clearer business and service information may matter more than another article. If the right sources discuss competitors but not you, relevant independent coverage may be worth investigating.

I review whether important pages are accessible, understandable, and clear about the questions they answer. Service descriptions, industry expertise, useful comparisons, and documented examples help explain when the business is relevant.

The content work can include new pages, improvements to existing material, clearer answers, supporting sources, author information, and internal links. Relevant structured data should accurately describe visible content. It is not a special pass into AI results.

Technical checks are matched to the platform. For example, discovery requirements for Google search features and access for ChatGPT Search are not interchangeable. I review the relevant controls rather than assuming that allowing every AI crawler is necessary.

Independent references help customers evaluate a business outside its own website. Relevant publications, credible directories, expert contributions, and genuine reviews can provide useful context about what you do.

Link building follows the same quality standards as the wider service. I do not promise that buying a certain number of backlinks will produce an AI recommendation. Links, unlinked mentions, and citations are assessed as different signals and outcomes.

For a local business, profile accuracy, review practices, citations, and useful location content may form part of the plan. For a national manufacturer, those activities may be less important than technical capability pages and credible industry coverage. The mix follows the business.

For the same national legal practice, AI brand visibility increased from 3% in the June 2026 baseline window to 11% in the September 10 to October 9 window across eight monitored nonbranded questions. Its position moved from 13th to first among 15 tracked firms. This is a defined monitoring sample, not a claim of universal AI leadership.

Fourteen contacts were tracked as ChatGPT referrals between January and September 2026: 12 forms and two calls. That window begins before the AI-focused work, so all 14 are not attributed to that work. They are tracked referrals, not signed cases.

For a national personal injury practice, estimated monthly organic visits increased from about 220 to 1,800 across matched September 10 to October 9 comparison windows in 2025 and 2026. These are third-party traffic estimates, not inquiry counts. The work combined practice and location content with authority building.

The latest case study connects those measures with source content, authority, and technical accessibility. It keeps the platform observations separate from search estimates and actual contact actions.

The reporting approach defines which questions and platforms are being monitored and how often the observations are collected. It separates mentions, linked citations, and the accuracy of the business description.

Where identifiable AI referral visits and inquiries are available, I review those alongside visibility. There are limits to attribution, particularly when a person reads an answer and contacts the business later through another channel.

The goal is a clearer picture of whether your presence is improving for relevant questions and what needs attention next. You should understand the sample behind a percentage instead of being asked to trust a single impressive response.

Explore the anonymous case studies for the work, reporting windows, and context behind these results.