Revenue Leak Detection
Surface hidden revenue loss caused by broken landing pages, bot traffic, and decaying channels. All prompts use the SealMetrics MCP server only.
MCPs required: SealMetrics MCP Best for: CMOs, Ecommerce Managers, Sales & Direct Directors Difficulty: Basic to intermediate
SEAL-001 — High-bounce landing pages with traffic
You are a senior web analyst with access to the SealMetrics MCP for site {site_id}.
Context:
- Today is {today}.
- Time range: last 30 days vs previous 30 days.
- We want to surface landing pages that are bleeding revenue because of poor first impression.
Task:
1. List every landing page that received more than 500 entrances in the last 30 days AND has a bounce rate above 70%.
2. For each page, return: URL, entrances, bounce rate, conversion rate, conversions, micro-conversions, % delta vs previous 30 days.
3. Rank by "lost entrances" = entrances × bounce_rate.
4. For the top 10, propose 3 plausible hypotheses for the high bounce (intent mismatch, slow load, broken layout, weak headline, irrelevant traffic source).
Output format: a markdown table sorted by lost entrances desc, followed by the top 10 hypotheses block.
SEAL-002 — Pages with traffic but zero conversions
Using SealMetrics MCP for site {site_id}, find every page that received more than 200 visits in the last 14 days and has zero conversions AND zero micro-conversions.
For each page return:
- URL, page type (landing or internal), entrances, pageviews, bounce rate, average time on page, top 3 traffic sources.
After the table, propose 2 optimization hypotheses per page (CTA clarity, content depth, intent mismatch, technical issue).
Order the table by entrances desc. Limit output to 25 pages max.
SEAL-003 — Bot and agent traffic cost estimate
For site {site_id}, retrieve bot and agent-suspected traffic from SealMetrics MCP for the last quarter (last 90 days).
Compute and report:
1. Total sessions classified as bot or agent_suspected.
2. Distribution of those sessions by traffic source (top 10 sources).
3. % of total entrances that were bot/agent.
4. % of paid traffic (utm_medium = cpc/paid/ppc) that was bot/agent.
5. If I tell you my average paid CPC ({avg_cpc}€), estimate the wasted ad spend on bot traffic alone.
Format: 1 summary table + 1 narrative paragraph with the wasted spend estimate flagged in bold.
SEAL-004 — Channel decay alert
Using SealMetrics MCP for site {site_id}, compare conversions and revenue by channel (utm_source / utm_medium) for the last 30 days vs the prior 30 days.
For each channel return:
- Channel name, entrances current vs previous, conversions current vs previous, revenue current vs previous, % delta on each metric.
Highlight every channel with a conversion drop greater than 20%. For each highlighted channel, also list the campaigns (utm_campaign) responsible for the bulk of the drop.
Output: 1 main table sorted by revenue lost desc, plus a "campaigns to investigate" section underneath.
SEAL-005 — Catastrophic landing pages audit
For site {site_id}, query SealMetrics MCP for the last 30 days and return every page with ALL of the following:
- More than 100 visits
- Bounce rate above 85%
- Zero micro-conversions
Columns: URL, entrances, bounce rate, average time on page, top traffic source, content group (if available).
Sort by entrances desc. Mark with "🔴 KILL" any page with zero conversions across the last 90 days, "🟡 FIX" the rest.
Then propose: a) which pages to deindex/redirect, b) which pages to rewrite, c) which pages to test with a different audience.