Detect lifecycle email fatigue

Correlate email volume, opens, clicks, unsubscribes, activation, and churn to find where lifecycle messaging helps or hurts.

Published

difficulty intermediate · time to value 7 minutes

Start from this

Analyze lifecycle email fatigue: sends, opens, clicks, unsubscribes, activation, and churn by sequence and user cohort.

Why this matters

Lifecycle email can activate users or annoy them into leaving. The difference is visible when email events are joined with product behavior.

What you get

  • Sends, opens, clicks, and unsubscribes by sequence
  • Activation after email clicks
  • Churn or inactivity after high-volume sequences
  • Recommendations to pause, rewrite, or segment messages

Walk through it

You

Are our lifecycle emails helping or hurting?

Agent

I’ll compare email engagement with activation and churn signals.

POST /v1/projects/:project_id/analytics/query {
  project_id: "default",
  hogql: "SELECT properties.sequence AS sequence, countIf(event = 'email_sent') AS sent, countIf(event = 'email_clicked') AS clicked, countIf(event = 'email_unsubscribed') AS unsubscribed FROM events WHERE event IN ('email_sent','email_clicked','email_unsubscribed') AND timestamp > now() - INTERVAL 30 DAY GROUP BY sequence ORDER BY sent DESC"
}

The output

The agent returns sequences to keep, improve, or stop. It should segment by lifecycle stage before making broad recommendations.

Setting it up

Forward email provider webhooks into Agentry as analytics events. Keep distinct_id stable with product events.

Variations

  • “Show onboarding emails only.”
  • “Find messages with high clicks but low activation.”
  • “Draft improvements for the worst-performing sequence.”

Try this recipe in your own agent.

Ask your agent to adapt the starter prompt to your saved signal map and live events, then run it against your data.

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