LLM SEO Agencies: What They Do and How to Judge One

An LLM SEO agency works to get a brand cited, mentioned or summarized inside answers from ChatGPT, Perplexity, Gemini, Claude and Google AI Overviews, as well as ranked in Google's blue links. You judge one by what it produces, how it measures citations against a baseline, and whether it can show business impact rather than screenshots of a single prompt. As of October 2026, almost every SEO firm lists "AI search optimization" on its services page, which makes choosing an LLM SEO agency harder than it was. This guide is for marketing leaders who already run SEO and paid programs. It covers what these agencies do, whether you need one, a weighted scorecard, the deliverables and KPIs to expect, pricing models and the red flags that expose relabelled SEO retainers.

What an LLM SEO agency actually does

An LLM SEO agency changes what AI models say about your category by shaping the sources those models retrieve and quote. The labels vary. GEO (generative engine optimization), AEO (answer engine optimization) and LLMO (large language model optimization) all describe the same job of making a brand easy for AI systems to understand, trust and quote. Traditional search engine optimization improves how pages perform in search results; LLM SEO extends the target to the generated answer that sits above or instead of those results.

Traditional SEO vs LLM SEO

The traditional discipline still matters. Backlinks and on-page SEO remain part of search engine marketing, and Google AI Overviews draw heavily on pages Google already ranks. LLM SEO is extra work on top of that.

Where AI answers get their sources

Models answer from two places. One is training data, which a brand can influence only slowly, through widespread third-party coverage. The other is retrieval at answer time. With retrieval-augmented generation (RAG), the system runs a search, pulls passages and cites them. Retrieval is where most of the opportunity sits. Google's AI Mode also splits one question into several sub-queries (query fan-out), so a page can be cited for a question it never targeted.

Much of what gets retrieved is not on your site: YouTube videos and their transcripts, podcast and webinar transcripts, Reddit and community discussions, review platforms and third-party editorial articles. An agency that talks only about your blog is working on a fraction of the sources in play.

The operational service list

• AI visibility baselines: testing which buyer prompts already surface or cite the brand, then tracking changes over time.
• Answer-first content: pages that define the brand, its products and the category in short, quotable passages. A comparison page that states "X suits teams under 50 seats; Y suits regulated enterprises" is easier to cite than a page of adjectives.
• Structured data: JSON-LD schema (Organization, Product, Article, and FAQPage where the FAQs are genuine), so systems can parse entities, facts and page purpose.
• Entity consistency: aligning facts across your site, schema and third-party profiles such as G2, Clutch and LinkedIn. An entity is a distinct thing a model recognizes, like your company or product, and conflicting descriptions weaken it.
• Citation-gap work: finding queries where competitors get cited and you do not, then creating or refreshing the content that closes the gap.
• Technical discoverability: crawlability, rendering, internal linking, metadata and speed, so retrieval systems can reach and interpret pages.
• Off-site authority: earned mentions in editorial coverage, review sites, Reddit threads, video and podcasts.
• Measurement: weekly prompt and citation tracking, citation deltas, AI referral traffic and leads, ideally with controlled tests.

Do you need an agency, a consultant or an in-house team?

You need an agency when AI visibility requires technical fixes, content engineering, digital PR and multi-platform measurement that your team cannot run reliably. You do not need one if your SEO team already covers those jobs and the category is simple. The decision turns on team capacity, budget and content maturity, a trade-off we cover in detail in how enterprises choose agency or in-house team.

Signals that outsourcing makes sense

• AI answers describe your brand inaccurately or use outdated positioning.
• Competitors appear in AI Overviews and Perplexity citations for your category queries, and you do not.
• Your category is discussed heavily on Reddit and review sites, and nobody owns those surfaces.
• Leadership wants AI visibility tied to pipeline, and your reporting cannot separate it from organic search.
• You operate multiple sites, brands or regions that need consistent entity data.

How to judge an LLM SEO agency: a weighted scorecard

Judge every LLM SEO agency against the same weighted scorecard, so the decision rests on evidence instead of the most polished pitch. Score each criterion from 1 to 5, multiply by its weight and compare totals. The method works whether you shortlist three vendors or eight, and you can use it alongside our guide on how to compare AI search optimization agencies.

For example, an agency scoring 4 on business alignment (0.8), 5 on measurement (1.0), 3 on content (0.45), 2 on off-site (0.3), 4 on technical (0.4), 3 on governance (0.3) and 4 on vertical (0.4) totals 3.65 out of 5. A rival scoring 4, 4, 5, 5, 2, 3 and 4 totals 4.0, despite weaker technical depth. The weights are set to reflect where AI citations come from, which is why the rival's content and off-site scores outweigh its technical gap.

Questions to ask in every pitch

1. Which prompts will you track, and how did you choose them? Good answers reference buyer research, search data and sales calls, grouped into prompt clusters (sets of related queries with the same intent).
2. How do you handle model volatility? AI answers vary between runs and model versions. Strong agencies run each prompt repeatedly, log the model version and report trends rather than single results.
3. What do you produce versus recommend? Get a list of shipped deliverables per month.
4. How do you separate AI visibility from SEO results? If both sit in one traffic chart, attribution will be guesswork.
5. What off-site work do you do, and what will you refuse to do? The refusal list (fake reviews, bought upvotes, aged accounts) tells you as much as the service list.
6. What data access do you need? Expect requests for Google Search Console, GA4, CMS access and your brand knowledge base.
7. Who owns the outputs? Content, prompt sets and tracking history should stay with you if the contract ends.
8. How do you coordinate with our SEO, PR and content teams? Look for a named owner and a weekly working rhythm.

What a good agency delivers in the first 90 days

A good agency delivers a baseline, a prompt map and a source-gap analysis in month one, a test plan and published content in month two, and measurable citation movement with a reporting dashboard by the end of the first quarter. Write these milestones into the contract; our guide to what belongs in the statement of work lists the clauses.

1. Month 1: audit and map. Technical and entity audit, prompt map by cluster, a competitor citation map showing which domains each AI surface cites, source-gap analysis and agreed brand guardrails.
2. Month 2: test and ship. A test plan with control prompts that receive no intervention, a content roadmap prioritized by citation gap, the first published pages, and an off-site placement strategy covering review sites, communities and editorial targets.
3. Quarter 1: measure and adjust. A dashboard with week-over-week movement, a review of which content and placements earned citations, and a revised roadmap for quarter two.

The KPIs that matter

• Citation frequency: how often your domain is cited for tracked prompts.
• Brand mention rate: how often the brand is named in answers, cited or not.
• Competitive share of answer: your citations and mentions as a share of all brands in the category answer.
• Source diversity: the mix of own site, review sites, Reddit, social and editorial sources citing you.
• Positioning and sentiment: whether answers describe you as the leader, an alternative or a cautionary example.
• Answer accuracy: whether pricing, features and positioning in answers are correct.
• Business signals: AI referral traffic, branded search lift, direct traffic, assisted conversions and prompt-cluster performance against pipeline.

How strategy should vary by platform

Each AI surface retrieves sources differently, so the tactics should differ by surface.

Pricing, engagement models and red flags

LLM SEO agencies sell monthly retainers, project-based audits, custom-scoped managed programs and, less often, performance-based deals. The right model depends on whether you need advice, production or both. The red flags below matter more than the price tag.

Common engagement models

Self-serve AI visibility trackers cost less than any of these and suit small teams that will do the work themselves. At enterprise scale, weigh the retainer against the pipeline lost while competitors own the answers.

Red flags

• Guaranteed placement in AI answers. No vendor controls what ChatGPT or AI Overviews say.
• No control groups. Without untouched prompts, citation gains cannot be separated from model updates.
• No off-site plan. AI answers lean on Reddit, reviews and editorial sources, and an on-site-only plan ignores them.
• No prompt examples or tracking method. If they cannot show which prompts they run, how often and on which models, the numbers are unverifiable.
• Rankings presented as citations. Ranking third on Google is not the same as being cited in the AI Overview above it.
• FAQ stuffing. Bolting twenty generic FAQs onto every page is not answer engineering.
• Blended reporting. AI visibility and organic SEO are collapsed into one traffic number.
• Growth-hack tactics. Bought upvotes, aged Reddit accounts and fake reviews create brand and platform risk.

Checklist for vetting case studies

1. Baseline period stated, with dates.
2. Prompts tested listed, with the number of queries.
3. Control group design explained.
4. Results recent enough to reflect current model behavior.
5. Market segment comparable to yours.
6. Business impact measured in leads, pipeline or revenue, not only citations.

How Tellr runs AI visibility for enterprise teams

Tellr is a premium earned-visibility agency that runs AI visibility as one governed program on its own platform. It puts enterprise brands inside the Reddit threads, Google results, AI answers and ad feeds their buyers read. Each week it tracks the category's queries on Google, recording the organic results, the AI Overview and the discussions block, and labels every cited domain as your site, a competitor, Reddit, review sites or references. That data decides the work. Tellr writes comparison pages, reviews and answer-shaped articles to be quoted by ChatGPT, Perplexity and AI Overviews and publishes them to your CMS, and it also produces guideline-checked Reddit replies and ready-to-run ad creative. Tellr is built for marketing teams spending $10k+ a month at companies worth $500M+ or with 200+ employees. It is not the right fit for a launch that needs results within three weeks.

• A category map of threads, queries and AI answers in week one; the brief and guardrails in week two
• Claim guardrails and an approval gate before anything goes live
• An audit trail of what was placed where, with takedown support
• Weekly reporting and a monthly program review
• No upvote buying, aged accounts or fake reviews

Choosing by company type

Company type decides which capability to prioritize. Small teams should buy tools and build skills, while complex, regulated or multi-brand companies need a managed program with governance. Use the matrix below to set your shortlist before you run the scorecard.

Whatever your profile, run the same process. Confirm you need outside help, score every vendor on one weighted rubric, insist on baselines and controls, and contract for deliverables rather than promises. The best LLM SEO agency for your company is the one that ships the content, earns the off-site mentions that move your citation share, and proves it with numbers tied to pipeline.

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