Prompt

How do I ensure my keyword research with a search volume API is compliant with rate limits and attribution rules?

Latest observation

Jul 21, 2026 · OpenAI APIWeb search: off

To stay compliant, treat the API as a licensed data source with two main constraints: rate limits and attribution/usage rules.

1) Respect rate limits

  • Read the API docs carefully for:
    • requests per second/minute/hour
    • daily/monthly quotas
    • burst limits
    • concurrent request limits
  • Build throttling into your app
    • Add client-side or server-side rate limiting.
    • Queue requests instead of firing many at once.
    • Use exponential backoff on 429 Too Many Requests.
  • Cache results
    • Store keyword results and reuse them when allowed.
    • Avoid re-querying the same keyword unnecessarily.
  • Batch requests if supported
    • Use bulk endpoints rather than single-keyword calls.
  • Monitor usage
    • Track request counts, error rates, and quota consumption.
    • Alert before hitting limits.
  • Handle retries safely
    • Retry only on transient failures.
    • Don’t retry aggressively on quota errors.

2) Follow attribution rules

  • Check whether attribution is required
    • Some providers require a credit line in UI, reports, exports, or dashboards.
  • Use the exact wording required
    • If the provider specifies a phrase or logo, use it exactly as written.
  • Place attribution where required
    • Common places: footer, report appendix, settings page, export metadata.
  • Preserve source labels
    • If you transform data, still identify the original source.
  • Don’t imply ownership
    • Avoid wording that suggests the data is your proprietary dataset if it came from the API.
  • Watch redistribution restrictions
    • Some APIs allow internal use but not reselling, republishing, or exposing raw data to end users.

3) Add compliance checks to your workflow

  • Document the API terms
    • Keep a summary of allowed use, attribution text, and quotas.
  • Create technical guardrails
    • Rate limiting middleware
    • Request logging
    • Quota dashboards
    • Attribution templates for exports and reports
  • Review changes before launch
    • If you add new features like bulk exports or public dashboards, re-check the terms.

4) Practical implementation tips

  • Use a token bucket or leaky bucket limiter.
  • Store a per-keyword cache key with a TTL that matches the provider’s terms.
  • When the API returns 429, stop sending requests and wait the suggested Retry-After period if present.
  • Include attribution automatically in:
    • downloadable reports
    • UI footers
    • shared links
    • API-powered charts

5) Ask the provider if unclear

If the terms are ambiguous, contact the API vendor and ask:

  • Can I cache results?
  • How long can I store them?
  • Can I show them in my app?
  • Is attribution required in the UI, exports, or both?
  • Can I redistribute results to clients/customers?

If you want, I can help you draft a compliance checklist or a rate-limited keyword research architecture for your specific API.

Observation history

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How did Obsurfable measure this prompt?

Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.

Which AI systems does Obsurfable collect answers from?

OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, and Meta AI.