AnalyticsGA4 analysisIntermediateAnalyses your data

Landing-page conversion diagnostics from GA4 data

Identifies which landing pages underperform for their traffic and proposes testable hypotheses, including tracking and intent mismatches.

For: Performance marketers, Marketing analysts, Growth marketers · Works with: Google Analytics 4, Any capable chat model (ChatGPT, Claude, Gemini, others)

Public beta. This prompt was drafted with AI assistance and checked by automated rules, but it has not been reviewed or tested by a person yet. Treat it as a starting point and check the output. It is hidden from search engines while in beta. Use the “Was this prompt useful?” box to tell us what works.

Your prompt

Act as a conversion analyst. Diagnose landing-page performance using ONLY the GA4 data below for 1-30 Sep 2026. Conversion: form submission on /contact-sales confirmed by event 'generate_lead'. Main traffic sources of interest: paid search and organic. Data: Landing page | Sessions | Conversions /pricing | 3100 | 93 /features | 2400 | 24 /blog/guide | 5100 | 15 /demo | 800 | 64 Tasks: 1. State your assumptions (for example whether sessions are comparable across pages). 2. Compute conversion rate per landing page from the counts given, and flag pages with fewer than 150 sessions as low-confidence. 3. Identify pages whose conversion rate is well below the site average, showing the numbers. 4. For each underperformer, list possible reasons in three groups: tracking or measurement problems, traffic-intent mismatch, and page experience. Label every item as a hypothesis and say what data would test it. 5. Propose up to 3 A/B tests with a clear single change each. 6. List missing data (device split, source split, scroll or click data). Rules: do not invent benchmarks or competitor numbers. If data is missing or not provided, say so. Distinguish correlation from causation. Verify all calculations and recompute the site average yourself from the counts.

Customize

The fields start with example values so you can see how the prompt works. Everything stays in your browser.

Period.

How conversion is counted.

Traffic to focus on.

Low-confidence threshold.

Paste your table. The default is small fictional sample data so the preview works; replace it with your own export.

Example of what to expect

Illustrative only. It describes the kind of result this prompt aims for; real output varies by tool, model and run.

Conversion rates computed per page, low-confidence flags, underperforming pages with grouped hypotheses, three single-change test ideas, and a missing-data list. (Illustrative.)

Expected format: Assumptions, page table, underperformer analysis, test ideas.

How to use it

  1. Segment by source before drawing conclusions.
  2. Treat all reasons as hypotheses.
  3. Run one A/B test at a time per page.

Limitations

  • Landing-page differences may reflect traffic differences, not page quality.
  • Without session segmentation the diagnosis is shallow.

Platform notes

Google Analytics 4

Official docs read · checked 2026-10-11

GA4 exports and the interface can differ (sampling, thresholds, attribution, data freshness). State which one your numbers came from.

General notes on Google Analytics 4
  • The BigQuery export has daily events_YYYYMMDD tables and intraday tables; intraday lacks some fields, and late-arriving data can update a daily table for up to 3 days.
  • Exported data and the GA4 interface can differ; the export documentation links to separate comparison articles that we did not read.

Any capable chat model (ChatGPT, Claude, Gemini, others)

Official docs read · checked 2026-10-11

Works in any capable chat model. Paste a small anonymised export and recompute the key numbers yourself: chat models can misread columns or miscalculate.

General notes on Any capable chat model (ChatGPT, Claude, Gemini, others)
  • These prompts are plain text and work in any chat assistant. For analytics prompts, paste a small, anonymised export; a chat model can misread columns or miscalculate, so recompute key numbers yourself.

Source, license and attribution

Origin
Original by MarketerTools
Publisher
MarketerTools
License
Original work by MarketerTools, free to copy and use. Informed by the linked documentation; no third-party text is reproduced.
Platform assumptions checked
2026-10-11

Documentation and references behind this prompt

These informed the structure and the platform notes. A reference is not a license, and no third-party prompt text is copied here.

Spotted an attribution error, or are you a source owner with a request? Use the chat button at the bottom right and quote prompt ID ana-003. We will correct or remove it.

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