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Overview

Time controls let you define what time period to analyze and at what granularity to view the data. Every report in Trodo supports flexible time configuration.

Time Range Selection

Preset Ranges

Quick selection for common time periods:
PresetDescription
TodayCurrent day (midnight to now)
YesterdayPrevious full day
Last 7 daysPast week including today
Last 14 daysPast two weeks
Last 30 daysPast month
Last 90 daysPast quarter
Last 365 daysPast year
This weekCurrent week (Monday to now)
This monthCurrent month (1st to now)
This quarterCurrent quarter
This yearCurrent year (Jan 1 to now)

Custom Date Range

Select specific start and end dates:
Custom Range:
├── Start: January 1, 2024
└── End: January 31, 2024

Include: All events from Jan 1 00:00 to Jan 31 23:59

Rolling Windows

Automatically update to show the most recent data:
Rolling 30 days:
├── Always shows the last 30 days
├── Updates automatically each day
└── Great for dashboards

Granularity

Granularity controls how data is grouped in time-series views:
GranularityBest For
HourlyIntraday patterns, short-term analysis
DailyDay-over-day trends, standard analysis
WeeklyWeek-over-week patterns, smoothing noise
MonthlyLong-term trends, executive reporting
QuarterlyBusiness planning, strategic analysis

Matching Granularity to Range

✅ Good combinations:
├── Last 24 hours → Hourly granularity
├── Last 7 days → Daily granularity
├── Last 30 days → Daily or weekly
├── Last 90 days → Weekly granularity
├── Last 365 days → Monthly granularity

❌ Poor combinations:
├── Last 365 days → Hourly (too many data points)
├── Last 24 hours → Monthly (not enough data)

Time Comparisons

Compare current period to previous periods:

Previous Period

Compare to the immediately preceding period:
Last 7 days vs Previous 7 days:
├── Current: 1,234 swaps
├── Previous: 1,100 swaps
└── Change: +12.2%

Same Period Last Year

Compare to the same period one year ago:
January 2024 vs January 2023:
├── Current: 45,000 users
├── Last year: 28,000 users
└── Change: +60.7% YoY

Custom Comparison

Compare any two time periods:
Compare:
├── Period A: Dec 1-31, 2023 (holiday season)
├── Period B: Nov 1-30, 2023 (pre-holiday)
└── See: Holiday impact on metrics

Session Timing

Trodo uses a 30-minute session timeout (not configurable):
Session Definition:
├── Session starts: First event from user
├── Session continues: Events within 30 min of last event
├── Session ends: 30 min of inactivity
└── New session: Activity after 30 min gap

Session Examples

User Activity Timeline:
├── 10:00 - page_view (Session 1 starts)
├── 10:05 - button_click (Session 1 continues)
├── 10:15 - swap_completed (Session 1 continues)
├── 10:45 - (30 min idle)
├── 11:00 - page_view (Session 2 starts)
└── 11:30 - session ends

Result: 2 sessions

Time-Based Filtering

Filter events by time properties:

Event Timestamp

Filter: timestamp last 30 days
Filter: timestamp between "2024-01-01" and "2024-01-31"
Filter: timestamp since "2024-01-01"

User First Seen

Filter: first_seen last 7 days
→ Only new users from this week

User Last Seen

Filter: last_seen before_the_last 30 days
→ Users who haven't been active in a month
See Filters & Operators for complete datetime operators.

Timezone Handling

Trodo automatically captures user timezone:
Default Property: timezone
Example values: "America/New_York", "Europe/London", "Asia/Tokyo"

Dashboard Timezone

Reports display in your selected timezone:
  1. Go to Settings
  2. Select your timezone
  3. All reports adjust accordingly

UTC Storage

All timestamps are stored in UTC internally:
  • Consistent data across timezones
  • No daylight saving issues
  • Accurate global comparisons

Time Patterns

Day of Week Analysis

Breakdown by day to see weekly patterns:
Swaps by day of week:
├── Monday: 15%
├── Tuesday: 16%
├── Wednesday: 17%
├── Thursday: 16%
├── Friday: 18%
├── Saturday: 10%
└── Sunday: 8%

Insight: Weekday trading dominates

Hour of Day Analysis

Breakdown by hour for daily patterns:
Swaps by hour (UTC):
├── 00-04: Low activity
├── 04-08: Rising (Asia)
├── 08-12: Peak (Europe)
├── 12-16: High (US East opens)
├── 16-20: Peak (US full)
└── 20-00: Declining

Insight: Schedule campaigns for peak hours
See seasonality:
Monthly active users:
├── Jan: 45K
├── Feb: 48K
├── Mar: 52K
├── Apr: 58K
├── May: 55K
├── Jun: 50K
├── Jul: 48K
├── Aug: 51K
├── Sep: 60K
├── Oct: 65K
├── Nov: 70K
└── Dec: 62K

Insight: Q4 is your peak season

Client time vs server-side events

For most browser SDK events, timestamps reflect when the client sent the event. If you also send server-side or backend events (for example when a long-running job finishes), those timestamps reflect server clock time. When comparing steps across sources, align on a single notion of “completed” (for example one agent_run_completed from the system of record).

Dashboard time controls

Global Time Selector

Dashboards can have a global time selector:
Dashboard: Weekly Overview
Global Time: Last 7 days

All charts on dashboard use "Last 7 days"
Override individual charts if needed

Per-Chart Time

Override global time for specific charts:
Dashboard Time: Last 7 days

Chart 1: Uses dashboard time (7 days)
Chart 2: Uses dashboard time (7 days)
Chart 3: Custom time (Last 30 days) ← Override

Best Practices

Match Time to Question

Question: What happened today?
Time: Today, hourly granularity

Question: How are we trending this month?
Time: Last 30 days, daily granularity

Question: Year-over-year growth?
Time: Last 365 days, monthly granularity

Use Comparisons Wisely

✅ Good comparisons:
├── Week-over-week (similar periods)
├── Month-over-month (business rhythm)
├── Year-over-year (seasonal adjustment)

❌ Poor comparisons:
├── Monday vs Sunday (different behavior)
├── Holiday vs normal week (outliers)
├── Launch week vs normal (unusual activity)

Account for Data Lag

Recent data may be incomplete:
If analyzing "Today":
├── Events appear in real-time
├── Transactions may have confirmation lag
├── Some aggregations update hourly

Recommendation: Use "Yesterday" for complete daily data

Smooth Volatility

Use longer time ranges or weekly granularity to smooth noise:
Daily view: Volatile, hard to see trend
Weekly view: Smoother, clear trend visible

Next Steps

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