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SEO/PPC Opportunity

Finds queries you pay for but already rank for — and flags where budget should move.

Path A · Manual extracts Path B · MCP integration Guardrail-first

On a set cadence, this automation joins your Google Ads search terms, Search Console queries, and GA4 landing page data, then sorts every query into three lists: cannibalization (you pay for clicks you already earn organically), content gaps (high-intent paid queries with no organic coverage), and budget reallocation candidates. Each run ends in an action pack — a negative keyword list, landing page briefs for the top gaps, and a proposed budget shift — not just a dashboard.

The reason to run it on a cadence is drift: paid and organic pull apart every month as new search terms appear, rankings move, and seasons change. A one-off overlap audit decays; a recurring one keeps catching the overlap as it re-forms, and the accumulated negative list and brief backlog become a channel split you actually govern.

What it moves: Cuts paid spend on queries where organic already wins — the clicks you are paying for but could earn for free — and redirects that budget to genuine content gaps.
Path A · Manual

This version runs entirely on scheduled exports and one spreadsheet — no API work beyond your normal logins. It suits a marketer who owns both channels and can give the analysis part of a day each month. Every change is applied by hand, so the approval gate is you.

Path B · Integrated

The same loop, run by an agent over live connections: read-scoped access to Google Ads, Search Console, and GA4, a scheduled job that joins and classifies queries, and an approval gate before anything touches the account. It suits teams with clean conversion tracking that want the cadence enforced by the system, not the calendar.

Prerequisites.

Standard or admin access to the Google Ads account, with Google Ads Editor installed for batch changes
A verified Search Console property with at least 3 months of query history
A GA4 property with conversion tracking on the landing pages that matter
An agreed cross-channel baseline: one shared answer to which conversions count as SEO vs. PPC
New to the stack? Set up your environment first — data access, workspace, integration platforms, and the agent layer are covered once in Environments & tooling. Not sure where the waste is yet? An automated AuditDemand audit ↗ quantifies it before you build.

Build it with manual data extracts.

This version runs entirely on scheduled exports and one spreadsheet — no API work beyond your normal logins. It suits a marketer who owns both channels and can give the analysis part of a day each month. Every change is applied by hand, so the approval gate is you.

  1. Pull the three exports

    Export the Google Ads search terms report, the Search Console query report, and GA4 landing page performance, all for the same 3-month window. Drop each into its own tab of one workbook. If you track competitors, keep the domain list in a fourth tab for context.

  2. Normalize and join the queries

    Lowercase everything, strip match-type noise and near-duplicates, then join paid search terms against Search Console queries. For each matched query, line up paid clicks, cost, and conversions next to organic position, clicks, and CTR.

  3. Classify every query into three lists

    Cannibalization: strong organic position and you are still paying for the click. Gaps: paid queries that convert but have no organic coverage. Reallocation: spend concentrated where organic already carries the intent. Score each row by cost so the biggest overlaps rise to the top.

  4. Draft the action pack

    Turn the cannibalization list into a negative keyword list. Write short landing page briefs for the top gap queries — target query, intent, page angle. Add a one-paragraph budget note: what you would pause, what you would fund instead.

  5. Apply by hand with a change log

    Apply the negatives through Google Ads Editor as one reviewable batch. Log every change with the date and before/after values so you can reverse the whole batch if organic traffic does not pick up the slack. Next cycle, compare lists against this one — that trend becomes your channel attribution baseline.

Cadence: Monthly; a cycle takes roughly half a day once the workbook template exists.

Integrate it with MCP connections.

The same loop, run by an agent over live connections: read-scoped access to Google Ads, Search Console, and GA4, a scheduled job that joins and classifies queries, and an approval gate before anything touches the account. It suits teams with clean conversion tracking that want the cadence enforced by the system, not the calendar.

Google Ads (read-only API access or an MCP server; a scoped write path only for approved negative-keyword batches)
Google Search Console (API or an MCP server, read-only)
GA4 (Data API or a BigQuery export, read-only)
Google Sheets or Looker Studio (approval digest and audit log)
An orchestrator: n8n, Make, Zapier, or Claude with MCP servers
  1. Connect and reconcile the three sources

    Wire up Search Console, GA4, and Google Ads with read-only credentials. Before trusting the loop, run one pull and reconcile it against the reports you already use — if the numbers do not match your dashboards, fix that first.

  2. Write down the cross-channel baseline

    Agree which conversions belong to SEO and which to PPC, and encode that rule in the agent's instructions. Every recommendation gets scored against this shared model, so neither channel claims the other's wins.

  3. Schedule the gap-analysis run

    The orchestrator pulls the three datasets on your cadence, normalizes and joins the queries, and classifies each into cannibalization, gap, or reallocation. The agent drafts the negative keyword list, the gap briefs, and a proposed budget shift with the evidence rows attached.

  4. Hold recommendations for sign-off

    Each run posts a digest — to a Sheet, Slack, or email — listing proposed negatives, briefs, and budget moves with the data behind them. Nothing is applied until a human approves the batch. Rejected items are logged with a reason so the agent learns your thresholds.

  5. Apply within caps, log everything

    Approved negatives go live as one staged batch, via the API write path or exported to Google Ads Editor. Budget shifts above your per-cycle cap always escalate. Every applied change lands in an audit log with timestamp and before/after values, reversible as a batch.

  6. Review the loop monthly

    Sample the audit log, check the attribution baseline still holds, and tighten or loosen the classification thresholds. The overlap trend across runs is your evidence that the split between channels is actually improving.

Run it safely.

Google Ads Editor — batch-apply approved negative keywords as one reviewable, reversible change set
Google Search Console — organic queries, positions, and CTR for the overlap join
GA4 — landing page and conversion data to weight each opportunity by value
Google Sheets — the overlap workbook, approval digest, and change log
Claude with MCP servers — runs the join, classify, and recommend loop on the integrated path
n8n, Zapier, or Make — schedules the pulls and routes the approval digest
  • No auto-apply: negative keywords and budget moves ship only as an approved, staged batch — the agent recommends, a human releases
  • Set a per-cycle cap on budget reallocation; any proposed shift above it escalates for explicit sign-off
  • Every applied change is logged with timestamp and before/after values, and each batch is reversible in one step via Google Ads Editor or change history
  • Read-only scopes on Search Console and GA4 at all times; Google Ads write access limited to the negative-keyword path

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