Marketing Agencies

Marketing agencies are under pressure to prove that their work moves the needle—and as more users turn to AI assistants for recommendations and research, “ranking” is no longer enough. Clients want to know: Are we being cited when people ask AI about our industry? Are our competitors showing up instead? Agencies that can measure and improve AI visibility (GEO and AEO) gain a clear edge: they can show before/after citations, competitor gaps, and fix guides that directly improve client visibility in ChatGPT, Gemini, and Claude. This guide covers why AI visibility matters for agencies and how to implement it for your clients without huge refactors.

Common pain points

• Clients ask “Are we in AI search?” and you have no data or proof to show.
• Competitor visibility in AI answers isn’t tracked, so you can’t show gaps or opportunities.
• Reporting is manual or generic; there’s no white-label or client-ready AI visibility report.
• Fix recommendations are vague (“improve content”) instead of specific (schema, llms.txt, FAQ templates).
• No way to run periodic scans or track trends over time for multiple clients.

What to fix

Implement a repeatable AI visibility workflow: (1) Baseline—run an AI visibility readiness scan for each client and capture the score and top issues. (2) Fixes—use actionable fix guides (schema, llms.txt, FAQ sections) and prioritize by impact. (3) Proof—run follow-up scans and, where possible, track real AI citations (Pro) so you can show “we got you cited in X prompts.” (4) Reporting—use white-label or exportable reports to show clients progress and competitor gaps. (5) Consistency—schedule recurring scans so you can report on trends. Tools that combine free readiness checks with Pro citation tracking and competitor analysis fit this workflow best.

Checklist

• Run a free AI visibility readiness scan for each client and document baseline score and issues.
• Add Organization and, where relevant, LocalBusiness or Product schema to client sites.
• Implement or improve FAQ sections on key pages and add FAQPage schema.
• Add llms.txt (or ai.txt) to client site roots with clear description and citation preferences.
• Track competitor domains and run gap analysis: where are competitors cited and the client not?
• Create client-facing reports (PDF or dashboard) showing score, fixes applied, and citation changes.
• Schedule recurring scans (e.g. weekly or monthly) and include AI visibility in regular reporting.
• Use fix guides and templates (schema, meta tags, llms.txt) so implementation is repeatable.

Examples

Example 1—Retainer report: An agency runs a monthly AI visibility scan for a B2B client. They add Organization schema and an FAQ page, then re-scan. The next report shows a 15-point score increase and “Now cited for [topic]” with a screenshot of an AI answer. Example 2—Competitor gap: For an e-commerce client, the agency adds competitors to the project. The tool shows “Competitor X is cited for [product category] but your client is not.” The agency creates a dedicated landing page with comparison content and schema, then tracks citations in the next scan.

Frequently asked questions

Next steps

Run a free AI visibility check for one of your clients and review the readiness score and fix list. Implement the top 2–3 fixes (e.g. Organization schema, one FAQ page, llms.txt) and re-run the scan. If you need citation proof and competitor gaps, upgrade to a Pro or Agency plan. Share the results in your next client report. For more on GEO and AEO, read our blog and glossary.