AdspirerInstall

Summary

Optimize the monthly budget allocation across TikTok advertising campaigns based on historical performance data and specified constraints.

Inputs

• advertiser_id (required) — TikTok advertiser ID identifying the advertiser account to optimize.
• total_budget (required) — Total monthly budget amount to allocate among campaigns.
• start_date — Start date (YYYY-MM-DD) for the historical performance data analysis.
• end_date — End date (YYYY-MM-DD) for the historical performance data analysis.
• lookback_days — Number of past days to analyze for historical performance; if omitted, no lookback period is used.
• max_change_percentage — Maximum allowed change in budget per campaign expressed as a decimal (e.g., 0.3 for 30% conservative, 0.7 for 70% aggressive).
• min_daily_budget — Minimum daily budget per campaign to enforce during budget allocation.
• target_roas — Override target Return On Ad Spend (ROAS) for budget optimization; numeric value influencing allocation strategy.
• raw_data — If true, returns only raw metrics in a JSON code block without any additional labels, recommendations, or benchmarking.

Output shape

a JSON object containing optimized budget allocations per campaign along with performance metrics or raw data depending on the 'raw_data' parameter.

The output includes severity labels, suggested bids and budgets, industry benchmarks, and optimization recommendations unless 'raw_data' is set to true, which restricts output to raw metrics only. Date parameters and numeric values should be provided as strings where applicable. The operation requires a TikTok advertiser ID and a total monthly budget to function.

Links

• n8n community nodes installation guide