Automatic Updates

How automated tracking and updates work across AI engines

How Automatic Updates Work

Rankscale automatically refreshes your brand tracking data at scheduled intervals. When you configure a search term with an automatic update frequency, the system runs queries against all selected AI engines — including Google AI Overviews, ChatGPT, Gemini, Perplexity, Claude, and others — without any manual intervention.

Each automatic update collects fresh visibility scores, rankings, sentiment data, and competitor mentions, keeping your dashboard up to date with the latest AI search landscape.

When Do Automatic Updates Happen

You can set each search term to update at one of the following frequencies:

Hourly: Updates every hour — ideal for time-sensitive terms during campaigns or product launches

Daily: Updates once per day — recommended for core brand terms you want to monitor closely

Weekly: Updates once per week — suitable for secondary terms or broader industry tracking

Monthly: Updates once per month — best for low-priority terms or long-term trend analysis

Processing Time

Automatic updates may take a few minutes to complete depending on the number of search terms and AI engines being queried. During peak times, processing may be slightly delayed but all runs will be completed.

Aggregation Accuracy

For the most accurate dashboard aggregations and trend charts, keep update intervals consistent within each topic. Mixing hourly and weekly intervals in the same topic can produce uneven data points that make trends harder to interpret.

Manual Updates

In addition to automatic scheduling, you can trigger manual updates at any time. This is useful when you need fresh data immediately — for example, after publishing new content, launching a campaign, or responding to a PR event.

Manual Run Details

• Trigger from the Search Terms section

• Choose to run individual terms or all terms at once

• Results appear in your dashboard once processing completes

• Manual runs consume the same credits as automatic ones

Processing Times

• Single term: typically completes within 1–2 minutes

• Batch runs: may take 5–15 minutes depending on volume

• GUI-based engines (Beta): may take slightly longer than API-based ones

• Results are available as soon as each individual term finishes

Best Practice

Use manual runs strategically — for example, after publishing a major blog post or press release, trigger a manual update to see how quickly the new content affects your AI visibility.

Manual Update Interface in Rankscale

Credit Management

Every update — whether automatic or manual — consumes credits. Here’s how credit usage works:

• 💳One credit per engine per term: Each search term queried against each AI engine counts as one run and consumes credits based on the engine type

• 📅Monthly reset: Credits reset each billing cycle — unused credits do not roll over to the next month

• 📊Runway indicator: Check your credit runway to see how many days of automatic updates you have left at your current usage rate

Learn More About Credits

For a full breakdown of credit costs per AI engine and tips on optimizing your credit usage, see 📄 Understanding Credits and Usage

Update Management Tips

Frequency Optimization

• Set core brand terms to daily updates for consistent monitoring

• Use weekly or monthly for secondary or exploratory terms

• Reserve hourly updates for time-sensitive campaigns only

• Review and adjust frequencies quarterly based on credit usage

Performance Tips

• Keep update intervals consistent within each topic for clean data

• Monitor your runway indicator to avoid running out of credits

• Pause updates on terms that are no longer strategically relevant

• Use manual runs for ad-hoc checks instead of increasing frequency

Troubleshooting Updates