Retention Analysis
Cohort return-rate curves over time — D1, D7, D30, and beyond.
Overview
Retention Analysis measures what fraction of users who first performed an action (e.g., signed up) came back and performed a retention event at specified intervals (Day 1, Day 7, Day 30, etc.). It groups users into cohorts by the period they first acted and plots return rates for each cohort.
When to use retention: "Are users coming back?", "How sticky is the product?", "Show me D7 and D30 retention after signup" — any question about cohort-based return rates over time.
When NOT to use retention: If you want to identify who is currently inactive or at risk
today, use churn. If you want to measure the first-value-moment rate for new users,
use activation.
Configuration Reference
Prop
Type
Available Template Variables
| Variable | Description |
|---|---|
{{cohortCount}} | Number of cohorts included in the analysis |
{{retentionSummary}} | Cohort × interval retention matrix (cohort label, size, and return rates at each interval) |
{{windowPeriod}} | Human-readable analysis window, e.g. "last 90 days" |
{{dataAsJson}} | Full structured result as JSON |
{{executedAt}} | ISO 8601 execution timestamp |
Example
apiVersion: journium.app/v0Beta
kind: InsightTracker
metadata:
name: signup-retention
displayName: Signup Retention (D1 / D7 / D30)
description: Weekly cohort retention after signup
spec:
type: LLM
trigger:
mode: automatic
schedule: weekly
window:
period: last_90d
analysis:
type: retention
entity: person_id
cohortEvent: user_signed_up
retentionEvent: session_started
cohortPeriod: week
intervals: [1, 7, 14, 30]
minCohortSize: 20
maxCohorts: 12
llm:
promptTemplate: |
Analyze signup retention for {{windowPeriod}}.
{{cohortCount}} weekly cohorts included.
Retention matrix:
{{retentionSummary}}
Full data: {{dataAsJson}}
Identify the cohorts with the best and worst D7 retention, and suggest one actionable
improvement for early-session engagement.
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