Facilitator Guide: Get Found in AI Search
You are a digital agency delivering an AI-visibility engagement to your client, using the ai12z platform. This guide is how you prepare, deliver, and follow up.
Download the ai12z AI Discoverability Workshop deck (.pptx)
The client-facing slides that pair with this guide — customize with your agency's branding before presenting.
This guide and the slide deck do two different jobs — you need both, and they're not interchangeable:
| This Facilitator Guide | The PowerPoint Deck | |
|---|---|---|
| Audience | You, the agency — never shown to the client | The client, projected or screen-shared live |
| What it contains | The full methodology, real example data and numbers, talk tracks, delivery-track decisions, pre-work checklists, and guardrails | A condensed, visual walkthrough — the on-screen version of what you're saying |
| When you use it | Before the session, to prepare — and as your reference during it | During the live session itself, as what's actually on screen |
| How you use it | Read it, don't read from it out loud | Click through it, customized with your agency's branding |
If a client would find a page confusing or overly internal (facilitator notes, product-comparison framing, pricing mechanics), it belongs in this guide, not the deck. If it's a number, a finding, or a talking point the client should actually see, it belongs in the deck, sourced from this guide.
Every page in this guide assumes you're running this for a client — not for your own internal team, and not as an ai12z employee running a customer-facing webinar. It gives you the full talk track, the real report data to demonstrate with, the exact ai12z screens to pull up, and the questions clients actually ask, organized around a single operating model: Measure → Improve → Prove.
Who This Is For
Digital agencies and consultants delivering an AI-visibility assessment — and the recurring service built on top of it — to their own clients. If you're looking for ai12z's own reference documentation on what each report does, start at the GEO Suite Overview instead; this guide is about how to deliver that suite as a client engagement, not what each report measures in isolation.
No prior GEO/AEO experience is assumed on your part or your client's. This guide works whether your client has never heard of Generative Engine Optimization or already reads industry coverage of it weekly.
The Operating Model: Measure → Improve → Prove
| Verb | What It Means | What It Looks Like |
|---|---|---|
| Measure | Establish a real, numbers-backed baseline — not an opinion about how visible the brand "feels" | A Citation Monitor health score, a Q&A Analysis GEO score, an Agent-Readiness score |
| Improve | Fix the highest-leverage, most concrete gaps first — not everything at once | Publishing a generated llms.txt, adding FAQPage schema, fixing a pricing inconsistency, filling a comparison-content gap |
| Prove | Re-run the same saved list or report and show the delta | Re-running a Citation List after a fix; a GEO Trend Comparison between two periods |
This is the same loop The ai12z Advantage describes at the platform level — your engagement is that loop, run once with the client in the room, structured so they can see you repeat it every month afterward.
What Your Client Leaves With
Four concrete deliverables — say these explicitly when you scope the engagement, because they're what you're actually selling:
- A working explanation of how AI answer engines discover, cite, and recommend brands — specific to their industry, not a generic slide.
- Their own highest-value content, brand, and technical gaps — not a checklist, an actual prioritized list from The Live Session.
- A saved measurement baseline — a Citation List and/or Keyword List that didn't exist before the engagement, ready to re-run next month.
- A prioritized 30-day roadmap — ranked, effort-tagged, modeled on the 30-Day Roadmap template.
Setting Expectations Honestly
Two things worth saying to a client before you start, because unmanaged expectations are the fastest way to lose credibility mid-engagement:
- The baseline you build will not be flattering. Every real example used throughout this guide — a Citation Monitor "Emerging" tier score of 32/100, a Site-Wide Sweep finding that 49% of pages have images missing dimensions, an AI Footprint finding of zero Wikipedia presence — came from a real, otherwise-healthy company. A weak first baseline is the normal starting point, not a sign the client's marketing team has failed.
- The live session produces a plan, not finished work. It ends with a prioritized list and a scheduled re-test date, not a rebuilt website. See The 30-Day Roadmap for what actually happens between sessions.
Format at a Glance
| Cadence | Baseline assessment once per new client; monthly re-testing after that |
| Prep time | Reports run asynchronously before the session — see Pre-Work & Guardrails |
| Live session length | 60–75 minutes — see The Agenda |
| Format | A live working session interpreting a baseline you've already built, not a from-scratch build in front of the client |
| Prerequisite | Which track your client is on — see Delivery Tracks — determines what you can prepare beforehand |
| Output | A citation baseline, a first Citation List and/or Keyword List, a categorized gap list, and a prioritized 30-day roadmap with a scheduled re-test date |
What Makes This Credible
This guide isn't built on hypothetical best practices. Every exercise runs against the same reports documented in the GEO Suite Overview, and every example in this guide is drawn from real report output — real ai12z.com data, the same data referenced throughout the reference pages. When this guide says "a real Citation Monitor run showed a competitor beating the brand with 19% share of voice on three uncited category queries," that's not a hypothetical — it's the literal example used in Citation Monitor, and it's exactly the kind of finding you'll surface for your own client.
Guide Modules
| # | Module | What It Covers |
|---|---|---|
| 1 | Facilitator Guide Overview (this page) | The operating model, what your client leaves with, format at a glance |
| 2 | Why This Matters Now | The discovery shift from links to answers; SEO vs. GEO/AEO, framed for a client conversation |
| 3 | The ai12z Advantage | Why ai12z's chatbot-layer ownership makes this a loop, not a one-time audit |
| 4 | Delivery Tracks | Prospect/new-client vs. existing-customer engagements — what you can run for each |
| 5 | Pre-Work & Guardrails | Intake questionnaire, required prep, privacy rules, fallback demo, deliverable template |
| 6 | The Agenda | The live session's run of show, and what happens before it |
| 7 | What You'll Measure | The four measurement pillars, annotated by which track each is available in |
| 8 | The Live Session | Interpreting the prepared baseline with your client and building the roadmap |
| 9 | Optimization Playbook | The five fix categories, each with a real before/after example |
| 10 | The ai12z Toolbox | Every report used across this guide, and when to reach for each |
| 11 | The 30-Day Roadmap | Week-by-week plan your client takes home |
| 12 | The Agency Service Model | Packaging this into sellable, recurring services — including implementation |
| 13 | Close & Handoff | Wrap-up checklist and next steps by track |
Related Documentation
- Get Found in AI Search: Program Overview — Back to the program landing page
- GEO Suite Overview — The full reference documentation for every report this guide uses
- Consolidated Action Plan — Where the live session's output ends up after the engagement