LLM SEO: How to Influence the Sources AI Models Trust

TL;DR: LLMs rely on trusted sources to answer prompts. If your brand is cited in those sources, you increase your chances of being recommended. AgentMindShare identifies those sources so you can influence them directly — and track results over time via MCP and BigQuery export.

Why Sources Matter for LLM Recommendations

Unlike traditional search engines that rely heavily on backlinks and keyword signals, LLMs generate answers by synthesizing knowledge from a range of high-quality sources in their training data and live retrieval systems. When those sources mention your brand positively, your inclusion odds go up.

AgentMindShare focuses on:

Mapping the exact sources behind competitor mentions
Highlighting content and citation gaps
Delivering action plans to influence those sources

Identifying Trusted Sources

LLMs often reference:

Review platforms like G2, Capterra, TrustRadius
Industry publications and niche blogs
High-authority content hubs (Wikipedia, industry associations)
News outlets covering your category

With AgentMindShare, you see exactly which domains were cited for each tracked prompt and model.

Building Your Influence Strategy

Run scans for high‑intent prompts in multiple models.
Extract citations from answers where competitors appear.
Classify sources – owned media, earned media, third-party listings.
Prioritize by citation frequency, authority, and ease of influence.

Execute changes:

Update and optimize your owned content to match prompt intent.
Request profile updates or reviews on third-party sites.
Pitch journalists or editors of cited publications.
Track impact with recurring scans.

Using MCP for Seamless Execution

Through MCP (Model Context Protocol), AgentMindShare integrates directly with environments like Claude Code so you can:

Pull source lists in real time
Draft outreach templates or briefs in the same workspace
Push tasks directly to Jira, Asana, or Trello

Measuring Results with BigQuery Export

Export all scan data to BigQuery for integration with SEO analytics, PR tracking, and attribution models.
Build dashboards to correlate source changes with shifts in LLM inclusion.

GEO Optimization Considerations

Ensure regional publications and directories mention you in target markets.
Adapt content to local regulations and buyer terminology.
Track citations by market to localize outreach.

Benchmarks

Aim to be cited in ≥70% of the top 10 sources for each high-intent prompt in your market.
Expect measurable gains in LLM inclusion within 4–8 weeks of successful source updates.

Pitfalls to Avoid

Ignoring no‑click sources – Some citations won’t be obvious to the public; use AgentMindShare’s reports.
Treating all sources equally – Prioritize high-authority and high-frequency citations.
One-off fixes – Citations change; monitor continuously.

FAQ

Does this replace SEO? No, LLM SEO complements traditional SEO by targeting AI answer citations.
Can I run this process in Claude Code? Yes, via MCP.
Can my PR team use the data? Absolutely — BigQuery export makes it shareable and trackable.

Get Started

Find out which sources you need to influence today. Run your first scan, see the citations driving competitor mentions, and take action — all from within your existing workflow using MCP.