B2B GEO Consulting & Generative Engine Optimization Services

On-page

Language models lean heavily on the same web ecosystem that powers traditional search. Weak SEO fundamentals limit your AI search visibility before you even start. Our on-page work covers:

• Bot Rendering & Crawlability
  Resolve the rendering gaps, bot blockers, and access issues that prevent GPTBot, PerplexityBot, ClaudeBot, and Google-Extended from reading your content.
• Semantic Structure
  Proper heading hierarchy, semantic HTML, and structured data that help AI models identify your products, services, and brand as distinct entities.
• Architecture & Internal Linking
  Clean URL patterns and a linking architecture that reinforces topical authority. AI models read those signals the same way search engines do.
• Content Organization
  Clear topic structure and well-defined sections AI tools can parse and cite without misreading your offering.
• Technical Performance
  Page speed, mobile usability, and indexation fixes. The same work that benefits traditional SEO also unblocks AI tools.
• Continuous Upkeep
  Ongoing monitoring as your site evolves, your CMS updates, and AI crawlers change behavior.

On-page

Past the fundamentals, this tactical layer focuses on what AI models are really citing, and why.

We study which pages AI tools reference for the prompts your buyers are using: which formats earn citations, which topics surface most often, and where competitors get pulled in and you don’t. That intelligence informs new content grounded in observed patterns rather than generic “AI optimization” advice.

For B2B technical and industrial companies, certain patterns hold. Technical spec content, application-focused pages, service pages, case study pages, and decision-stage buyer guides earn more citations than top-of-funnel awareness content. We identify which of those formats matter most for your category and prioritize accordingly.

The work itself covers content gap analysis, prompt-to-content mapping, answer-first restructuring of existing pages, and editorial tightening so content stays technically accurate and AI-readable. The goal is not just to rank. It’s to become a credible source AI systems cite by name.

Where the On-Page Work Happens

• Prompt-to-Content Mapping
  Match the prompts your buyers are using to the pages on your site that should be answering them. Surface the gaps where no page exists at all.
• Section-Level Optimization
  Identify which parts of a page AI tools pull from, and how (direct quote, paraphrase, factual reference). Optimize at the section level, not just the page level.
• Engine-Specific Tailoring
  ChatGPT, Perplexity, Google AI Overviews, Gemini, and Copilot each pull from different sources and weight signals differently. We tailor by engine.
• Competitive Citation Analysis
  Where competitors get pulled in and you don’t is your most actionable opportunity. We close those gaps prompt by prompt.
• Iterative Refinement
  AI behavior shifts. New model versions change what gets cited. Our work is ongoing, and our recommendations evolve as the data does.

OFF-SITE

AI models don’t just pull from your website. They pull from publications, directories, social platforms, technical forums, and review sites in your category. Off-site signals shape whether your brand surfaces at all, and they serve traditional SEO at the same time.

• Source Identification
  We map the publications, directories, and content formats AI tools actually cite for your category, then build off-site strategy around those proven sources rather than chasing generic link metrics.
• Placement Strategy
  We recommend specific placements structured to match observed citation patterns: directory listings, comparison content, expert roundups, and trade publication features. Some are free editorial coverage worth pursuing, and others are paid placements worth the spend. We help you tell the difference, identify the outlets, and prioritize outreach so your team isn’t chasing every directory that emails them.
• Community & Forum Presence
  AI models pull from Reddit, industry subreddits, technical forums, and the social platforms your buyers actually frequent. We identify where your audience gathers and where contributions, mentions, or thoughtful presence will compound, not where to spam.
• Brand Consistency
  Inconsistent NAP information, outdated descriptions across directories, and conflicting messaging on third-party sites confuse both search engines and AI models. We audit your external footprint so AI tools get a single, accurate story.

VISIBILITY MONITORING

Here’s where we differ sharply from most agencies pitching AI search services: we don’t promise rankings. Anyone telling you their tool will get you to “position #1 in AI search” is selling something that doesn’t exist.

AI outputs are probabilistic, not deterministic. Ask ChatGPT the same question ten times and you’ll often get ten different answers, with different brands cited in different orders. There’s no stable ranking to optimize toward, only patterns to observe over time.

What we can do is measure directional progress with discipline, including:

• Mention Frequency Over Time
  Across many prompts, run repeatedly, how often does your brand surface? More mentions over time across more relevant prompts is the signal that matters, not a single snapshot.
• Citation Source Tracking
  Which pages and domains are AI tools pulling from when they reference your category? That data, covering yours, your competitors’, and the third-party sources that come up most, drives both on-page priorities and off-site targeting.
• Sentiment & Accuracy Checks
  Being mentioned isn’t the same as being recommended. We monitor how your brand is characterized, whether positively, neutrally, or critically, and whether AI tools are repeating accurate information or surfacing outdated claims.
• AI-Driven Traffic Analysis
  GA4-based reporting on sessions, engagement, and conversions from AI search sources. This is the most concrete data point we have, because it measures real downstream behavior rather than guessing what AI is saying.
• Prompt-Level Spot Checks
  We sample full AI responses across engines for the prompts that matter most. The variability matters, because seeing how the same prompt produces different outputs is itself useful intelligence.
• Reasonable Reporting Cadence
  Monthly reviews covering directional changes in visibility, citation patterns, and AI-driven traffic. Quarterly strategic recalibration as models evolve and buyer prompts shift. No false precision, and no manufactured ranking charts.