Generative Engine Optimization Services: What to Expect

Generative engine optimization services measure how ChatGPT, Perplexity, Gemini, Claude and Google AI Overviews describe your category, then change those answers through new content, technical fixes and mentions on the sources those engines cite. Buyers usually arrive with a specific problem. A head of demand gen asks ChatGPT for "the best cloud security platforms for a 2,000-person company," sees three competitors named, and finds their own brand missing from an answer a prospect may read before visiting any website.

Offerings sold under this label in October 2026 range from self-serve tracking tools to fully managed programs, so the label alone tells you little. Good generative engine optimization services give you four things: a baseline you can trust, a plan to change it, people who do the work, and remeasurement you can audit. This guide covers what each stage should produce, how the delivery models differ, and the warning signs in a weak proposal.

What generative engine optimization services actually cover

The work splits into three jobs: measuring how AI answer engines represent your brand, producing the assets those engines cite, and governing that work so it stays accurate. GEO, also called answer engine optimization (AEO), is reshaping how buyers discover, evaluate and shortlist vendors, which is why so many SEO agencies and software companies have relabelled their existing products.

Providers fall into four groups:

• Self-serve trackers: software your team runs to monitor mentions, citations and share of voice across AI engines.
• Enterprise platforms: tracking plus content workflows, usually with vendor-assisted onboarding.
• Consultants: audits and strategy, with execution handed back to your team.
• Managed programs: a vendor team that diagnoses, produces, publishes and reports.

Answers from these engines are probabilistic. The same prompt can return a different shortlist an hour later, and a model update can move results overnight. A provider who promises a fixed placement is promising something no one controls. For the wider program design, see our enterprise GEO program guide.

A good engagement starts with a diagnosis

The diagnosis is a measured baseline of which prompts matter, what the engines say, and which sources they cite. The prompt set should mirror how buyers actually ask, grouped into prompt families:

• Category: "best endpoint security for mid-market companies"
• Comparison: "CrowdStrike vs SentinelOne for a 500-seat team"
• Problem: "how to stop credential phishing without retraining staff"
• Evaluation: "is [brand] worth it," "[brand] pricing," "[brand] alternatives"

Log every answer with the same fields: engine, prompt, date, brands mentioned, order of mention, recommendation language, cited URLs, and source type (your site, a competitor, Reddit, review sites, media). Run each prompt several times per engine. For example, five runs per prompt across four engines gives 20 observations per prompt instead of one screenshot. The diagnosis then sorts each gap into a state, because each state needs a different fix.

The diagnosis should also include a technical audit, because engines can only cite what they can fetch and parse. This is where GEO and SEO overlap most:

• Crawlability: robots.txt rules for GPTBot, OAI-SearchBot, PerplexityBot and ClaudeBot, plus CDN or WAF rules that silently block bots.
• Rendering: key content present in server-rendered HTML, since many AI crawlers do not execute JavaScript.
• Structured data: Organization, Product, Review and Article schema that matches what is visible on the page.
• Canonicals and faceted pages: one indexable URL per comparison or product, with no parameter duplicates.
• Internal linking, freshness and entity signals: visible update dates, named authors and consistent product naming.

Diagnosis needs an execution path

Before you sign, ask who will turn the diagnosis into published pages, fixes and placements. A dashboard showing that a competitor holds, say, 40% of citations for your category changes nothing until someone writes the page, earns the mention and ships the fix. The models below differ mainly in who owns that execution.

To choose a model, work through these questions in order:

1. Do you have writers and editors with spare capacity? If yes, a tracker or platform may be enough.
2. If not, can your monthly marketing budget fund outside production? If yes, consider a managed program.
3. Do you need an outside view before committing budget? Start with a consultant audit.
4. Will GEO become a permanent function? Plan an in-house hire, and keep a vendor in place while you recruit.

What to expect in the first 90 days and every month

Month one should produce a category map and baseline, month two the first shipped assets, and month three a remeasurement against the baseline. A typical phased engagement runs like this:

1. Days 1–30: prompt map, baseline report, source-gap audit, technical issue list and agreed claim guardrails. Your stakeholders are the SEO lead, brand, legal and the analytics owner.
2. Days 31–60: the first content briefs and pages ship, technical fixes are ticketed, and outreach or community work begins on the sources that already get cited.
3. Days 61–90: the first remeasurement using the same prompts and sampling, then a reprioritised backlog.

After launch, a good provider delivers the same items every month:

• Citation share and mention movement by prompt family, with the changes explained
• Assets shipped, with URLs and publish dates
• Technical fixes completed and still open
• Experiments run, each with a hypothesis and result
• Decisions needed from your team, each with an owner

Each workstream needs a named owner, or the work stalls:

Commercial terms come in four shapes: a one-off audit, a project (for example, 20 comparison pages), a monthly retainer, or software plus services. Pin the scope down in writing. Our guide to what belongs in the statement of work lists the clauses to include.

How to measure progress and spot a weak proposal

Measure GEO at three levels (visibility, operational output and business outcomes), and treat any proposal that reports only the first as incomplete.

• Leading indicators: citation share, mention rate, recommendation rate and source mix for each prompt family.
• Operational indicators: pages shipped, fixes closed, placements still live, and approval turnaround time.
• Business outcomes: AI referral sessions, branded search lift, self-reported attribution ("heard about us from ChatGPT") and sourced pipeline.

Red flags in a weak proposal:

• A single visibility score with no prompt-level detail behind it
• A prompt set of a few dozen queries for a multi-product category
• Single-run sampling presented as a reliable trend
• A plan that only rewrites existing pages, with no technical or off-site work
• Fabricated authority: fake reviews, aged accounts or pages produced at volume
• No approval gate, claim review or audit trail

Fabricated authority is an old pattern. In Wired's words, one popular SEO tactic involves creating thousands of pages of realistic-looking text with links to a client's page. Governance matters even more in regulated verticals:

• Healthcare and finance claims get legal review before publication.
• SaaS comparison pages carry accurate, current competitor pricing.
• Ecommerce product data matches the catalogue.

Where Tellr fits

Tellr is a premium earned-visibility agency that runs GEO as one managed program for enterprises spending $10k+ a month on marketing, typically at companies worth $500M+ or with 200+ employees. Its senior team does the work on Tellr's own platform:

• A category map of the threads, queries and AI answers that matter in week one, then an agreed brief and guardrails in week two
• Comparison pages, reviews and answer-shaped articles, built from your knowledge base and published to your CMS
• Guideline-checked Reddit replies behind an approval gate, with an audit trail of what was placed where
• Weekly tracking of which domains Google and its AI Overviews cite for each query, with a monthly program review
• Paid-media ad intelligence and ready-to-run creative

Teams that want a dashboard to run themselves will find a managed program the wrong shape.

Questions to ask a GEO agency or tool vendor

Ask about methodology first, then execution ownership, governance and the business case.

• Methodology: How many prompts are in the set, how often is each one sampled, which engines are covered, and are answers collected by API, browser session or panel?
• Execution: Who writes, who approves, who publishes, and what ships in the first 60 days?
• Governance: How are claims checked, and what is the takedown process if something goes wrong?
• Business case: Which pipeline metric will the monthly report tie visibility to?

The right purchase leaves you with a baseline you trust, a backlog someone is actually shipping, and a report your CFO would accept. Generative engine optimization services that deliver those three things earn their budget. Services that deliver only a dashboard are a tracker sold at a higher price.

FAQ