Signals & Automations

Signals is your AI-visibility issues inbox — the things actually worth your attention, across every client, in one place. Instead of making you watch dashboards, CrunchJunkie continuously turns what it already measures into signals: a client's visibility dropping, a competitor overtaking them in share of voice, a GEO Audit score falling, a cited source going dead or being retracted, a product feed or product-page schema gap, a broken data connection, and the highest-priority "what to fix" actions. Open Signals from the AI Visibility menu for the agency-wide rollup, or the Signals tab inside a client for just that brand. The point of difference is accuracy. AI answers are non-deterministic — the same question can be answered differently minute to minute — so a naive alert that fires on any day-to-day wiggle just cries wolf. A change-over-time signal (like a visibility drop) is raised only when the change is BOTH materially large AND statistically significant given the sample size behind it. Every signal shows that sample size (n = runs) and a confidence score, so you always know how solid it is. A quiet inbox is genuinely good news, not a tool that's asleep.

The signals no AI-visibility-only tool can raise: ones that only fire when an AI-search-visibility change coincides with a change in your paid or analytics data — because CrunchJunkie has both in one place. Two ship today: "AI visibility & conversions both dropped" (AI-search visibility fell AND the AI-referred conversions in your GA4 fell over the same period — lost visibility costing real conversions), and "Paid spend up but AI visibility flat/down" (your ad budget is rising but you're not winning more AI-answer presence). Both are still significance-gated on the visibility side and carry a volume guard on the money side (a tiny account can't trip them), and the Evidence expander shows both sides' actual numbers. They only appear for clients that have the relevant sources connected — GA4 for the first, an ad account for the second. Because these read live ad-platform and GA4 data, they refresh on their own schedule (a couple of times a day) rather than instantly. Automate on them like any signal — a natural fit for the "Draft an action plan" or "Draft a report" actions.

Each signal carries a severity (Critical / Warning / Info), a plain-language explanation, and an Evidence expander showing the exact metrics or citations that produced it — nothing is a black box. You can Acknowledge a signal (you've seen it), Snooze it (it drops out for a week, then returns if still true), or Resolve it (you've handled it). Resolved and acknowledged signals are never re-raised within their period, so the inbox stays clean. Filter by Open, Resolved or All at any time. Signals is read-only and costs nothing — it runs on data you've already scanned, with no extra AI calls. Managing many clients? The Portfolio board (AI Visibility → Portfolio) is your triage view: every client on one screen with a health status — Off track (has a Critical signal), At risk (a Warning, or a goal meaningfully off target), or On track — sorted worst-first so the accounts that need you today float to the top. Click any client to work its signals. And a portfolio-level signal fires when the same problem hits many clients at once ("6 of your 12 clients' AI visibility dropped this week"), which usually points to a shared cause worth investigating across the board rather than one by one.

An Automation is a no-code rule: when a signal happens, do something. You pick the trigger (a signal type — e.g. "a competitor overtakes us" — with a minimum severity, for one client or all of them) and the actions. Phase-one actions are notify actions: email (you, your team, or any address), a Slack message (via an incoming-webhook URL), or a generic webhook to Zapier / Make / n8n / your own endpoint. Start from a template — Visibility guardrail, Competitor watch, Source health, Feed & schema health, Broken-connection guard, or Critical-only — and tweak it, or build one from scratch in the When → Then editor. Automations inherit the same no-noise guarantee: they only ever fire on signals that already passed the significance bar, and each signal triggers a given rule at most once, so you're never spammed. Every rule shows how many times it has fired and when it last did. Set one up under AI Visibility → Automations.

Beyond notifying, an automation can do a first draft of the work. Add the "Draft an action plan (AI)" action and, when a signal fires, Crunch writes a short, grounded plan for it — a one-line summary, the likely cause, and three to five concrete next steps — using your own AI key or Managed AI (so it's metered like any other AI feature, and free on your own keys). Crucially, nothing is sent to anyone automatically. The draft lands in the Approvals inbox (AI Visibility → Approvals), where you read it and either Approve — which emails the plan to the automation's recipients (or you) — or Dismiss. You're always the one who decides what goes out; there's no autonomous publishing. It's the "data → done" loop, with a human in the loop by design. The inbox doubles as a shared task queue: assign any item to a teammate, give it a due date and a working note, and mark it In progress while you work on it. You can also add your own ad-hoc tasks with "New task" — for follow-up work no automation triggered — and mark them Done when finished, so all your team's open AI-visibility work lives in one place.

Two heavier actions take the same draft-then-approve shape, so a signal can hand you a finished deliverable instead of a to-do. Draft a report (AI) builds a white-label report for the signal's client from its connected data sources and AI-visibility signals — the same composition as the report builder's "Draft with AI", including an executive summary. It lands in Approvals; when you approve, Crunch creates a shareable link and emails it to the recipients (on your own verified domain if you have white-label set up). You can open and edit the report in the builder before approving — nothing goes out until you do. Use it on a per-client rule so the report targets the right brand. Draft a content brief (AI) writes an evidence-grounded GEO content brief for the project's single biggest gap prompt — a question where the tracked brand is never mentioned across recent runs — with a target question, recommendations, a suggested structure, schema to add and proof to include, all grounded in what the winning pages actually do. It waits in Approvals until you send it. Both are AI actions, so they're metered exactly like report summaries (free on your own keys, counted on Managed AI), and both are strictly human-approved — CrunchJunkie never publishes or sends a report or brief on its own.

Automations are a paid feature: Starter includes 3 active rules, Pro 10, and Agency and Scale unlimited. Email and in-app signals work on every plan that has Automations; Slack and generic-webhook actions are available on Pro and above. Anyone on your team can create a rule (the same policy as connecting a data source). Prefer a gentler cadence? A weekly Signals digest emails the workspace owner a single low-noise roundup of the week's open signals — no setup required, and no email in weeks when there's nothing worth sending. Use the real-time Automations for the things you can't miss, and let the digest cover the rest. There's also a client-facing version: a Client digest (AI Visibility → open a client → Client digest) is a recurring, white-labelled summary sent to your client under your brand — weekly or monthly, with an outcome-led, plain-language AI narrative written from the client's AI-visibility trend and goal progress (grounded strictly in the numbers, generated once and saved, never regenerated per recipient). Send a test to yourself, approve the format once, and it recurs on your cadence to the client's contact email (or any addresses you set). It carries your workspace name and logo, with the CrunchJunkie footer removed on Starter and above.