Get attribution breakdown showing which traffic sources and campaigns drive orders and revenue. Returns top 20 campaigns per source by default to reduce response size.

Key Features:

• Multi-source attribution with campaign/referrer breakdowns
• Smart filtering to reduce response size
• Discovery pattern for unknown source names
• Supports 4 attribution models

Parameters:

• store_id (integer, required): Store identifier
• last_x_days (integer, optional): Get data for last X days (e.g., 30 for last 30 days, 0 for today). Alternative to date_start/date_end.
• date_start (string, optional): Start date (YYYY-MM-DD, inclusive). Use with date_end or use last_x_days instead.
• date_end (string, optional): End date (YYYY-MM-DD, inclusive). Use with date_start or use last_x_days instead.
• attribution_model (string, optional): Attribution model - "last_click_per_channel" (default), "any_click", "first_click", "last_click"
• attribution_window_days (integer, optional): Attribution window in days (default: 180)
• sources (string, optional): Comma-separated source names to filter (e.g., "Meta Ads,Google Ads,Klaviyo"). Default: all sources
• min_orders (integer, optional): Minimum orders threshold to include campaigns (default: 0)
• limit_per_source (integer, optional): Max campaigns/referrers per source (default: 20)
• include_breakdowns (boolean, optional): Include campaign/referrer detail (default: true)
• sort_by (string, optional): Sort campaigns by - "orders", "sales", "roas" (default: "orders")

Common Traffic Sources:

Meta Ads, Google Ads, TikTok Ads, Klaviyo (email), Organic, Direct, Instagram, Snapchat Ads, Pinterest Ads, Microsoft Ads, Amazon Ads