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↘ Decay queue

Decay queue

Revenue-weighted decay with root cause diagnosis.

A ranked list of URLs losing AI citations, crawls, or SERP position. Each row pairs revenue-at-risk with a three-way root cause diff (Peec citation · logs crawl · GSC SERP).

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For:In-house brandEnterpriseAgency activator

app.peecockpit.pro/decay

Revenue at risk

$38k

top 50 URLs

Decaying URLs

128

28d split-window

Fastest cluster

data residency EU

−8.2 SoV

Top root cause

stale citations

no refresh in 60d

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Apply: create_prompt 'best PIM for EU'

GSC 980 imp/mo · matched /solutions/pim

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Apply: create_brand 'contentful'

new entrant · alternatives-to cluster

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Reject: create_topic 'general-saas'

low confidence · wide spread

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Apply: create_tag 'eu-ai-act'

BERTopic outlier cluster

Revenue at risk

$38k

top 50 URLs

Decaying URLs

128

28d split-window

Fastest cluster

data residency EU

−8.2 SoV

Top root cause

stale citations

no refresh in 60d

What it does

Why this surface exists.

Prioritize fixes by revenue impact, not by raw impression drop
Identify the exact root cause before writing a brief. Citation loss ≠ SERP drop ≠ crawl drop
Close the loop with a retrack at T+14 so you know the fix worked
Avoid spending a week refreshing content when the real issue is a canonical leak

Workflow

The chain that runs behind the page.

4-step composite. Every tool call is logged for the tracked_id audit.

Split-window GSC

28-day split-window impression drop per URL from GSC Wizard.

GSC · searchanalytics

Revenue weighting

Per-URL revenue-at-risk = |imp_drop_pct| × 28d landing-page revenue from GA4. Fallback synthetic when GA4 offline.

GA4 · landing page revenue

Three-way root cause

For each decaying URL, diff Peec citation delta, logs crawl delta, and GSC SERP delta side-by-side.

Peec · get_url_reportLogsGSC · Inspection

Queue the workflow

Each row has a recommended workflow (refresh, recrawl, schema patch, canonical fix) routed to the action queue.

Action queue

Datasources used

Where the numbers come from.

Each datasource has a provenance chip on the live dashboard, so you always know whether a number came from a live MCP call, a cached snapshot, or a fallback.

GSC Wizard

Reach

Impressions, clicks, average position by query and page.

Top queries per URLImpressions vs clicks (zero-click gap)28-day position driftDecay candidates split-window

Peec AI MCP

Citation

Citations, share of voice, sentiment, search-query fan-out, prompt suggestions.

Brand mentions per model · per clusterShare of voice deltasCited URLs + url_classificationsearch_queries fan-out

Server access logs

Crawl

AI bot crawl activity (GPTBot, ClaudeBot, PerplexityBot, OAI-SearchBot, Google-Extended).

Per-bot last-hit timestampHits per URL per dayNon-200 errors for AI user-agentsEmerging crawler detection

GA4 / Adobe / PostHog

Revenue

Sessions, engagement, conversion, revenue, segmented by canonical AI source.

AI-referral sessions by sourceConversion rate · AOV · time-to-convertRevenue per AI-cited pageSampling flag above ~10M events/day

All 6 datasources →

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Decay queue

Why this surface exists.

The chain that runs behind the page.

Where the numbers come from.

Where this connects.

Join the early-access list