Measure landing-page source quality

Compare acquisition sources by activation, retention, and paid conversion instead of only measuring clicks or signups.

Updated · published

markdown for agents →

difficulty intermediate · time to value 5 minutes · execution on demand
#analytics #acquisition #marketing #activation #retention #saas

Start from this 

Compare acquisition sources by signup volume, activation rate, day-7 retention, and paid conversion. Show which sources are high-quality, not just high-volume.

Why this matters

Marketing dashboards overvalue volume. Product teams need to know which sources create activated, retained, paying users.

What you get

  • Signup volume by source
  • Activation and retention by source
  • Paid conversion by source if revenue events exist
  • Recommendations for where to spend or stop spending

Walk through it

You

Which landing sources produce good users?

Agent

I’ll compare acquisition source against activation and retention events.

Endpoint: POST /v1/projects/:project_id/analytics/query
Exact shape: /v1/openapi.json?path=%2Fv1%2Fprojects%2F%7Bproject_id%7D%2Fanalytics%2Fquery&method=post
Custom HogQL goes in the OpenAPI-defined `query` field.
Concept fields:
  query: "SELECT properties.utm_source AS source, countIf(event = 'signup_completed') AS signups, countIf(event = 'activated') AS activated, activated / nullIf(signups, 0) AS activation_rate FROM events WHERE event IN ('signup_completed','activated') AND timestamp > now() - INTERVAL 30 DAY GROUP BY source ORDER BY signups DESC"

The output

The agent returns a source-quality table and flags sources with many signups but weak activation.

Setting it up

Persist UTM/source attribution onto signup and activation events. Anonymous pageviews are useful, but source must survive account creation.

Variations

  • “Compare LinkedIn vs Google by paid conversion.”
  • “Only show sources with at least 50 signups.”
  • “Publish this as a marketing quality dashboard.”

Related workflows

growth 3 minutes

Track trial-to-paid conversion by acquisition source

Build the trial-to-paid funnel split by acquisition source. Surface the channel that converts 8x better than the rest.

growth 15 minutes

Identify early behaviors associated with retention

Compare predefined first-window product behaviors with later retained activity, quantify associations, and design a validation step without declaring a magic cause.

growth 10 minutes

Calculate campaign payback by cohort

Tie acquisition campaigns to paid conversion, revenue, and retention so marketing and finance can see which campaigns pay back.

Adapt this workflow in your own agent.

Ask your agent to map the starter prompt to your saved signal map, live events, and the current HTTP API before answering.

Agentry gives coding agents production context from errors, product analytics, and deploys through one HTTP API. Fetch and read https://agentry.sh/install.md completely, then install Agentry's full first-time telemetry baseline in this repository. I authorize device-code login, saving the owner key only to ~/.agentry/credentials.json, creating one Agentry project for this repository, and read-only inspection of shipped source plus hidden CI/provider configuration. Deeply analyze the product's business logic and complete value flow before choosing telemetry. Save the complete source-backed plan and show me its exact contents and hash. Until I explicitly approve that plan or request a replacement, do not edit app/CI source, place runtime/CI credentials, commit, exercise product traffic, start proof, push, or deploy. After approval, I authorize only the reviewed targets: place the required scoped browser/server/CI credentials through the established environment or secret mechanism, preserve existing telemetry, implement and test the baseline, commit it, push that reviewed commit when the shipped CI/provider path requires it, exercise safe proof paths with test/non-customer data, and perform one deployment through the reviewed shipped CI/provider path. Ask first if proof would charge money, contact a third party, change real customer data, or require new external access. After the plan is saved, immediately before every onboarding state-changing POST, GET current onboarding state, perform only its single returned next_action, then read state again; do not batch or infer later stages. Continue until status is verified, installation_complete is true, and next_action is null. Keep all secrets, source snapshots, proof markers, and scratch files outside the repository.

+ Full access
5.5 Extra High
  1. 1. Open your repo in Codex, Claude Code, Cursor etc.
  2. 2. Paste the install prompt.
  3. 3. Your agent reads the install doc and shows you an implementation plan for approval.
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