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Adding and Configuring Search Terms in AI Visibility

Learn how to add and configure AI search terms manually, in bulk, or via CSV upload, select engines and frequency, manage location and advanced settings, and understand how configurations are tracked.

Updated this week

What it is

Adding and configuring search terms defines how prompts are executed, tracked, and measured in AI Visibility.

Each configuration determines:

  • Which AI engine runs the prompt

  • How often it runs

  • Which region it runs from (if supported)

  • How responses are generated

  • How the term is tracked in reporting

Every configuration creates a unique tracked entry.

Why it matters

AI visibility tracking is execution-based.

Each combination of:

  • Prompt

  • AI engine

  • Location

  • Frequency

  • Advanced settings

creates its own tracked configuration.

If configured incorrectly:

  • Visibility data may fragment

  • Reporting may become inconsistent

  • Credit usage may increase unnecessarily

  • Competitive benchmarking may lose clarity

Configuration precision ensures reliable trend data.

Ways to add search terms

You can add search terms in three ways:

  1. Manual entry

  2. Bulk add (paste multiple terms)

  3. Bulk upload via CSV

All three methods lead into the same configuration process.

1. Manual adding

Manual entry gives you full control over each term.

How to add manually:

  1. Go to Search Terms

  2. Click + Add Term

  3. Select a Topic

  4. Add Tags (optional)

  5. Enter your prompt

  6. Select AI engine(s)

  7. Set frequency

  8. Configure location (if supported)

  9. Review credit estimate

  10. Save

💡 Notes:
​

Prompt field:

No character limit

Exact text is sent to the selected AI engine

Prompts should reflect realistic user language

Description (optional)

  • You can add an internal description. Use this to:

    • Document intent

    • Clarify campaign context

    • Explain enterprise tracking logic

    • Descriptions do not affect AI execution.

2. Bulk add (paste multiple terms)

Bulk Add allows you to paste multiple prompts at once.

How it works:

  1. Go to Search Terms

  2. Click Bulk Add

  3. Paste multiple prompts (one per line)

  4. Assign topic(s)

  5. Apply tags (optional)

  6. Select AI engine(s)

  7. Set frequency

  8. Save

This is ideal when:

  • Expanding topic coverage

  • Adding multiple comparison prompts

  • Scaling structured prompt libraries

3. Bulk upload via CSV

For larger structured imports, use CSV upload.

How to upload via CSV:

  1. Click Bulk Add

  2. Select Upload CSV

  3. Download the provided template

  4. Add:

    • Search Terms

    • Topics

    • Tags

  5. Upload the file

  6. Continue to engine and frequency configuration

  7. Save

CSV upload is recommended for:

  • Agencies onboarding clients

  • Enterprise prompt libraries

  • Large-scale structured imports

AI engine selection logic

When selecting multiple AI engines:

If you select 3 AI engines → 3 separate tracked terms are created.

Each configuration is treated as a unique tracked entry.

This follows the same principle as SERP tracking:
​

Each configuration = separate tracked entity.

This means:

  • Visibility is engine-specific

  • Execution history is engine-specific

  • Reporting is engine-filterable

Location settings (engine-specific)

Location selection is available for supported engines (e.g., ChatGPT and Google AI Overviews).

Location influences:

  • Regional brand ordering

  • Competitive positioning

  • Contextual output

Changing location creates a separate tracked configuration.

Frequency settings

Available frequencies:

  • Hourly

  • Daily

  • Weekly

  • Monthly

  • Manual

Frequency determines:

  • Data granularity

  • Trend speed

  • Resource consumption

Higher frequency builds faster trend stability but increases usage.

Credit preview before saving

Credit consumption depends on:

  • Selected AI engine(s)

  • Frequency

  • Configuration settings

Inside the Add/Bulk screen, you will see an estimated credit impact per run before saving.

For detailed mechanics, see How AI visibility credits work.

Cloud run limits

Cloud run limits control how many executions can process concurrently.

This primarily affects:

  • Large batch runs

  • Enterprise-scale tracking

  • High-frequency configurations

If limits are reached:

  • Runs are automatically queued

  • Execution continues sequentially

Most users do not need to modify this setting.

Advanced options (Expert Mode)

You can enable Expert Mode for advanced configuration.

Temperature

Temperature controls response variability:

Lower (e.g., 0.2)
→ More deterministic responses
→ More stable brand detection

Mid-range (0.5–0.7)
→ Balanced variability

Higher (0.8–1.0)
→ More creative or varied outputs

For brand monitoring and benchmarking:
Use lower or mid-range temperature for consistency.

For exploratory research:
Higher settings may surface broader mentions.

Consistency is important for trend reliability.

What happens after saving

Once saved:

  • A unique tracked configuration is created per engine

  • Execution begins based on selected frequency

  • Execution history starts building

  • Visibility metrics begin populating

Tracking starts from the first run forward.

No retroactive data is added.

Best practices

  • Assign every term to a Topic

  • Use Tags for reporting segmentation

  • Avoid duplicate configurations unless intentional

  • Review credit estimates before saving

  • Keep temperature consistent across comparable terms

  • Start with high-priority commercial prompts

Related Articles
Creating An AI Visibility Brand
Search Terms & Topics In AI Visibility Tracking
Managing Search Terms in AI Visibility
Using Find Terms in AI visibility
Search Terms Table Explained
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