Schedules
Set up automated snapshot captures to continuously monitor your brand's AI visibility without manual intervention.
Overview
Schedules let you automate snapshot captures so that AEO Optima continuously monitors how AI engines respond to your tracked prompts. Instead of manually triggering snapshots, you define a schedule and the platform handles the rest.
Automated scheduling is essential for tracking trends over time. Consistent, regular snapshots provide the data foundation for Analytics, Sentiment Analysis, and Insights.
Creating a Schedule
- Navigate to Schedules from the sidebar.
- Click Create Schedule.
- Enter a descriptive name for the schedule (e.g., "Weekly Brand Monitoring" or "Daily Competitor Check").
- Choose a frequency:
- Hourly — Captures run once every hour. Best for time-sensitive campaigns or rapidly changing topics.
- Daily — Captures run once every day.
- Weekly — Captures run once every 7 days.
- Biweekly — Captures run once every 14 days.
- Monthly — Captures run once every 30 days.
- The schedule activates immediately after creation.
What Happens When a Schedule Runs
When a scheduled capture executes, the following occurs:
- All active prompts are queried — Every prompt in your project that is marked as active will be sent to the configured AI engines.
- All active LLM configurations are used — Each prompt is sent to every AI engine you have configured (e.g., ChatGPT, Claude, Gemini, Perplexity).
- One snapshot per combination — The system creates one snapshot for each prompt-LLM combination. For example, if you have 10 active prompts and 3 active LLM configurations, a single scheduled run produces 30 snapshots.
- Usage is tracked — Token usage and costs are recorded for each capture, visible on the Usage page.
This ensures comprehensive coverage across all your monitored queries and AI engines with every capture.
Monitoring Schedule Runs
The Recent Runs table on the Schedules page shows the status and results of each capture.
| Column | Description |
|---|---|
| Run Time | When the capture started |
| Status | Whether the run completed, failed, or is still in progress (pending, running, completed, failed) |
| Snapshots | Number of snapshots captured in that run |
| Duration | How long the capture took to complete |
| Errors | Any error messages if the run failed or partially failed |
Job Status Indicators
- Pending — The job is queued and waiting to be processed
- Running — The job is currently capturing snapshots
- Completed — The job finished successfully
- Failed — The job encountered an error. Check the error message for details.
Note: Jobs that remain in "pending" or "running" status for more than 15 minutes are automatically marked as failed to prevent stuck jobs from blocking future captures.
Troubleshooting Failed Runs
If a scheduled run shows a failed status:
- Check the error message in the Recent Runs table for details.
- Verify that your LLM configurations are still valid and active.
- Confirm that you have active prompts in the project (a schedule with no active prompts will have nothing to capture).
- Review your API key status if using Bring Your Own Key (BYOK) configurations.
Managing Schedules
- Pause a schedule — Temporarily stop captures without deleting the schedule. You can resume it at any time.
- Edit a schedule — Change the name or frequency. Changes take effect on the next scheduled run.
- Delete a schedule — Permanently remove the schedule. Historical data from past runs is preserved.
- Manual trigger — Run a schedule immediately without waiting for the next scheduled time.
Choosing the Right Frequency
| Frequency | Best For |
|---|---|
| Hourly | Time-sensitive campaigns, product launches, or crisis monitoring where AI responses may change rapidly |
| Daily | Active campaigns, product launches, or rapidly evolving topics where AI responses may change quickly |
| Weekly | Standard brand monitoring for most organizations. Provides consistent trend data without excessive captures |
| Biweekly | Brands with stable presence in AI responses. Useful for long-term trend tracking with lower volume |
| Monthly | Baseline monitoring or low-priority projects. Sufficient for quarterly reporting |
Note: Higher-frequency schedules consume more snapshots and API usage. The platform's health monitoring dynamically adapts its thresholds based on your shortest active schedule frequency.
Best Practices
- Start with weekly — For most brands, weekly captures provide the best balance of data richness and resource efficiency.
- Use hourly sparingly — Reserve hourly schedules for short-term campaigns or crisis monitoring. Switch back to daily or weekly once the campaign ends.
- Use multiple schedules for different purposes — Create a daily schedule for high-priority prompts during a product launch and a weekly schedule for ongoing brand monitoring.
- Check Recent Runs regularly — Make it a habit to review the Recent Runs table to catch any failed captures early.
- Align with your reporting cadence — If you share reports with stakeholders monthly, make sure your schedule captures enough data points to show meaningful trends within that window.