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The Live Signal Reports

Three screens in the GEO Suite are never "generated" — they're just always current. Between monthly Lab sessions, these are what attendees should actually be checking.

Every module so far has centered on reports you run against a chosen date range — Q&A Analysis, Citation Monitor, Keyword Visibility. That's the right frame for the once-a-month working session this guide is built around. But three screens in the suite don't work that way at all: AI Referral Analytics, Q&A Insights, and Web Content Quality are live tables, always reflecting whatever has happened up to the second you open them. The Toolbox already flags AI Referral Analytics as one of these; this module is where the other two earn a proper walkthrough, because attendees consistently ask "wait, can I see the actual conversation?" during the live baseline exercise — and the honest answer is yes, in more detail than most people expect.

Why This Gets Its Own Module​

The four measurement pillars in What We Measure in the Lab are built around reports — a snapshot you generate, compare, and re-run. The live signal reports answer a different need: "something looks off in the aggregate number — show me the actual row it came from." A weak theme cluster in Q&A Analysis is an average; Q&A Insights is the one specific conversation that dragged it down. A concerning quickScore in Site-Wide Sweep is a whole-site rollup; Web Content Quality is the one page that's actually the problem. Facilitators should treat these three screens as the "drill into it" answer any time a report-level number prompts the question "okay, but which one?"

Q&A Insights: The Conversation Behind the Score​

Q&A Insights is the live, ungrouped table of every question and answer, each already carrying the same 1–100 quality score Q&A Analysis later rolls into its theme clusters. Run this exercise live:

  1. Open Q&A Insights and sort by score, ascending.
  2. Pick the lowest-scoring row. In one real example, a garbled question — "i want chatbot where based on users msg i want to open dif..." — scored 75, next to a clean, well-scoped question like "how do i find bot embed code" scoring a perfect 100. The gap is instructive on its own: quality score tracks how well-formed and answerable the question was, not just how the bot responded.
  3. Click the Conversation icon. This opens the full multi-turn transcript, each answer showing its Sources count — proof of exactly what content the bot drew from, not just that it produced an answer.
  4. Watch for the AI Referral Source panel. When a conversation started from a visitor who arrived via a generative AI answer engine, the transcript view shows Engine, Engine Type, and Referrer Domain (e.g. chatgpt.com → ChatGPT) alongside Landing Page and full Device & Visit Details — down to the visitor's browser, OS, country, and exact visit timestamp.

Talk track: this is the moment to connect two modules the room has already seen separately. AI Referral Analytics told the room "43.5% of AI-referred sessions came from ChatGPT" as an aggregate. Q&A Insights is where that number stops being abstract — say out loud: "that 43.5% isn't a statistic, it's individual visitors, and here's literally what one of them asked us after ChatGPT sent them to our pricing page."

Watch for: attendees assuming this level of detail requires custom analytics tooling. It doesn't — it's one click from a report they were already looking at.

Web Content Quality: Finding the Page Before You Audit It​

Web Content Quality is the live, per-page list of every ingested page's quality score — the same ingest-time signal Site-Wide Sweep calls geoScore in its own weakest-pages table, just searchable and sortable on demand instead of bundled into a whole-site report.

Run this exercise live:

  1. Open Web Content Quality and filter for the lowest scores — in the real sample used throughout this guide, pages scoring 70–75 rendered an amber Needs work badge, immediately distinguishable from the blue Strong badge on 80+ pages.
  2. Copy the source URL of the weakest page in the list.
  3. Immediately pivot to URL Analysis and run it against that exact URL — this is the same page-selection step covered in the Optimization Playbook, just sourced from a live table instead of a Site-Wide Sweep PDF.

Talk track: frame Web Content Quality as the smoke detector and URL Analysis as the inspection. A room that has just run Site-Wide Sweep in the Live Exercise already has a "weakest pages" table — this is the same idea, just live and always current, useful for the weeks between full sweeps.

Watch for: conflating this score with URL Analysis's 19-section GEO Score. They measure different things at different depths — Web Content Quality is a single ingest-time signal; URL Analysis is a full structural and citeability audit. Don't let the room treat a "Strong" badge here as "no further optimization needed."

The Pattern to Name Explicitly​

Say this once both exercises are done: every live signal report exists to answer "which specific one?" after an aggregate report already told you "something's off." Q&A Analysis flags a weak theme — Q&A Insights shows the exact conversation. Site-Wide Sweep flags a weak site average — Web Content Quality shows the exact page. AI Referral Analytics shows a traffic aggregate — Q&A Insights shows the exact visitor. None of the three live screens replace the reports they drill into; they're the zoom lens sitting next to them.

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