AnalyticsGA4 analysisIntermediateAnalyses your data

GA4 traffic-quality check: engagement vs conversion by source

Separates sources that bring visits from sources that bring valuable visits, ranking by engagement and conversion with sample-size warnings.

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 marketing analyst. Using ONLY the GA4 data below, assess traffic quality by source/medium for last 28 days. Goal: qualified demo requests. A "good" visit means: an engaged session that views pricing or the demo page. Data: Source/medium | Sessions | Engaged sessions | Demo requests google / organic | 5200 | 3300 | 52 newsletter / email | 900 | 700 | 31 linkedin / paid | 1500 | 520 | 12 reddit / referral | 160 | 70 | 1 Tasks: 1. State assumptions, including how you treat rows with very low sessions (use this threshold: 200 sessions). 2. Rank sources by quality using the metrics provided; show the formula or logic you used, and the numbers. 3. Flag sources where high volume has low engagement or conversion, and sources where small samples make a ranking unreliable. 4. Suggest 3 follow-up checks (for example landing-page mix, device mix, tagging issues) as hypotheses, not conclusions. 5. List the data you would need but did not receive. Rules: do not invent metrics or benchmarks. Treat engagement and conversion differences as correlations; do not claim a source "causes" revenue. Verify your arithmetic and recompute rates from counts where counts are provided. If a column is missing, say so.

Customize

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

Period covered.

What matters.

How quality is judged.

Below this, flag as unreliable.

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.

A ranked list of sources with computed engagement and demo-request rates, flags for low-volume rows, three hypotheses to check, and a missing-data list. (Illustrative.)

Expected format: Assumptions, ranked table with formulas, flags, follow-up hypotheses.

How to use it

  1. Pick a quality definition before you analyse.
  2. Use the threshold to avoid over-reading tiny samples.
  3. Verify rates against the export.

Limitations

  • Quality by source depends on attribution and tagging; poorly tagged traffic distorts the ranking.
  • Small samples produce unstable rates.

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-002. We will correct or remove it.

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