Trend / Growth

Count events or unique users per time period — daily, weekly, monthly.

Overview

Trend Analysis computes a time-series of an aggregated metric bucketed by hour, day, week, or month. It covers all growth and usage-frequency questions. "How many times does X happen per period?" is always a trend question.

When to use trend: "How many users are signing up every month?", "Show me daily active users over the last 90 days", "What is the weekly trend in purchases over the past quarter?"

When NOT to use trend: If you want automated spike/dip alerts, use anomaly. If you want cohort return curves, use retention. If you want to compare groups, use cohort.

Configuration Reference

Prop

Type

Available Template Variables

VariableDescription
{{metricName}}Human-readable name for the metric (derived from event + aggregation)
{{periodCount}}Number of time buckets in the result
{{currentPeriodValue}}Value in the most recent complete time bucket
{{peakPeriod}}Label of the time bucket with the highest value
{{peakValue}}The value at the peak period
{{trendDirection}}Overall trend direction: "up", "down", or "flat"
{{trendSummary}}Human-readable summary of the trend (e.g. "grew 12% week-over-week")
{{hasComparison}}true if compareWindow data is available
{{previousPeriodValue}}Value in the equivalent previous period (when hasComparison is true)
{{growthRatePct}}Percentage change vs. previous period (when hasComparison is true)
{{windowPeriod}}Human-readable analysis window, e.g. "last 90 days"
{{dataAsJson}}Full structured result as JSON
{{executedAt}}ISO 8601 execution timestamp

Example

.journium/trackers/daily-signups-trend.yml
apiVersion: journium.app/v0Beta
kind: InsightTracker
metadata:
  name: daily-signups-trend
  displayName: Daily Signups Trend (WoW)
  description: Daily signup count with week-over-week comparison
spec:
  type: LLM
  trigger:
    mode: automatic
    schedule: daily
  window:
    period: last_30d
    granularity: day
  analysis:
    type: trend
    entity: person_id
    event: user_signed_up
    aggregation: uniqueUsers
    groupBy: day
    compareWindow: previous_period
  llm:
    promptTemplate: |
      Daily signup trend for {{windowPeriod}}.
      Metric: {{metricName}} — {{periodCount}} days.
      Most recent day: {{currentPeriodValue}} signups.
      Peak day: {{peakPeriod}} ({{peakValue}} signups).
      Overall trend: {{trendDirection}}. {{trendSummary}}
      {{#if hasComparison}}
      Previous period: {{previousPeriodValue}} total. Growth: {{growthRatePct}}%.
      {{/if}}
      Full data: {{dataAsJson}}
      Summarize the signup trend and highlight any days with unusual volume.
    maxOutputTokens: 400

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