Most teams should start by improving pages AI platforms already know about, then create net-new content to fill clear gaps. Prioritize using AI-specific signals—citation consistency, agent traffic, and Influence Score—alongside business intent, not just traditional SEO metrics.
Optimize an existing page when: - AI agents already crawl it. Pages with high agent traffic but few or inconsistent citations are the fastest wins. - The page’s intent roughly matches the prompt. Misalignment that can be fixed with structure, clarity, or depth is a good candidate for updates. - Technical issues are the bottleneck. If audits flag access controls, JavaScript-dependent content, slow delivery, or token bloat, fix those first. - You already earn some brand citations but lose consistency. Tighten content quality and alignment to hang on to the citation more reliably.
Create a new page when: - No page on your site addresses the prompt. Fill obvious content gaps rather than stretching a page far from its core intent. - Existing pages are too constrained to pivot. If the title, metadata, and on-page structure fight the prompt, a focused new asset is faster. - Competitors or low-substance sources dominate. Build a more authoritative, structured alternative designed to displace them. - You need a purpose-built format. AI often prefers concise, well-structured answers with clear headers, tables, and FAQs—sometimes easiest to achieve on a new, dedicated page.
Weigh impact versus effort using Influence Score and prompt importance. A high-Influence opportunity with thin competing content is low-hanging fruit; a well-built, highly authoritative competitor page may not be worth the near-term push.
1) Check which pages AI already knows about
Use agent traffic and site maps to find pages LLMs are visiting. High traffic + low citations signals “improve, don’t replace.”
2) Audit access, delivery, and content quality
Resolve robots.txt or access issues, ensure content is available without JavaScript, reduce load time and token bloat, and fix mismatches between page title/description and on-page content.
3) Analyze citations to spot gaps
Track citation consistency to see which sources win for each prompt and where your brand is missing. Use Influence Score to prioritize pages and sources that matter most across multiple relevant prompts.
4) Choose your content path
- Improve: Strengthen structure, answer clarity, depth, schema, and recency. Add short FAQs aligned to tracked prompts.
- Net-new: Create focused, prompt-matched content with clean structure and authoritative evidence.
5) Measure impact
Monitor changes in citation consistency, brand share of voice, and agent traffic over 2–3 week windows to confirm movement vs. one-off fluctuations.
Monitoring-only tools are useful for visibility and benchmarking. They help you learn where you stand, what sources AI cites, and how performance changes over time. They’re a solid fit if you’re early in AI search, have a small set of prompts, or need tighter governance before scaling content updates.
Platforms that also help generate or optimize content and deliver AI-friendly versions compress the full loop from insight to action. Look for workflows that:
Keep a human-in-the-loop. Use generation and optimization to accelerate drafts and structure, then apply editorial rigor to avoid “slop” and preserve brand quality.
Consider a dedicated AI visibility tool if: - Your buyers use AI assistants to research your category. - Competitors frequently appear in AI responses for your core prompts. - Your site is JavaScript-heavy or slow, and you need clarity on how agents actually consume it. - You need cross-model coverage, trend tracking, and clear impact metrics like citation consistency and agent traffic. - You want a scalable workflow to prioritize and validate changes across many prompts and pages.
Doubling down on SEO/content can work if: - You’re early, tracking a small prompt set, and can manually sample AI responses. - Your team already executes well on crawl-friendly, well-structured, expert-led content. - You accept that LLM behavior differs from traditional search, and without AI-specific telemetry, you may optimize blind.
For a deeper primer on AI search strategy, see the Guide to AI search.
Core capabilities: - Broad model and platform coverage to compare performance across ecosystems. - Prompt tracking at scale with tagging by funnel stage, persona, region, and topic clusters. - Citation analytics with citation consistency and an Influence Score to balance frequency and breadth. - Competitive benchmarking and share of voice across prompts and platforms. - AI agent traffic analytics and site maps to see what agents crawl most. - Technical audits covering access controls, content delivery without JavaScript, speed, and token weight. - Content optimization workflows that map pages to prompts, personas, and schema, with clear, editable recommendations. - An AI-friendly delivery layer to serve fast, structured, non-JS content to agents when needed. - Alerts, reporting, and data export for stakeholders and systems. - Governance and security: roles, review workflows, and change history.
Vendor considerations: - Demonstrated industry experience and customer proof. - Transparent pricing options and implementation support. - Clear roadmap and responsiveness to model/platform changes.
Prioritize in this order:
1) High agent-traffic, low-citation pages. These already have crawler attention; optimization lifts citation win-rate fastest.
2) Pages tied to high-intent, later-funnel prompts (comparisons, evaluations, pricing, integrations).
3) “Close to winning” pages with inconsistent citations where small structural fixes can stabilize wins.
4) JS-heavy or slow pages that agents struggle to read; create token-light, JS-free versions to improve retrieval.
5) Competitor-displacement opportunities where the cited page is substance-light or misaligned with the prompt.
6) Evergreen hubs and comparison pages that influence many adjacent prompts.
Quick checklist for each page:
- Does the title/description match the on-page answer?
- Can agents read the full answer without JavaScript, in under five seconds?
- Is the content concise, structured with clear headers, tables, and FAQs?
- Does it include fresh data, expert POV, and unique facts?
- Is schema present and accurate?
A B2B data infrastructure team tracks, “What’s the best tool for real-time data pipelines?”
- They find a product overview page with high agent traffic, low citations, and a middling audit. They fix access and delivery issues, tighten structure, and add a short FAQ.
- For a related prompt, “How do data pipeline tools handle schema changes?” they have no relevant page. They publish a focused explainer with examples and a comparison table.
- They monitor citation consistency and share of voice for both prompts over the next few weeks to validate lift.
Use Influence Score to focus on sources and pages that impact multiple relevant prompts, then weigh impact vs. effort: - Start with thin, surface-level cited sources and pages whose titles/descriptions don’t match content. - If the cited source is a competitor, plan to improve or create content to displace it. - If a trusted third-party domain appears across many prompts, outreach for a placement is often faster than competing head-on.
Helpful resources:
- Explore AI visibility and insights in Monitoring & Insights.
- Learn how to deliver AI-friendly versions of key pages with the Agent Experience Platform (AXP).
- Dive deeper into technical vs. content tradeoffs in Insights (Chapter 3).