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Creative Cross Analysis

zuckerbot_creative_cross_analysis

Cross two creative dimensions to find winning combinations. Example: hook_type × visual_style can reveal that curiosity + ugc outperforms pain_point + stock. Returns a performance matrix, best and worst combinations, and an actionable insight string.

Parameters

Name	Type		Description
`business_id`	string	optional	Optional business ID override
`group_by`	"hook_type" \| "visual_style" \| "product_focus" \| "setting" \| "cta_type" \| "copy_tone" \| "opening_element"	required	Primary dimension
`cross_by`	"hook_type" \| "visual_style" \| "product_focus" \| "setting" \| "cta_type" \| "copy_tone" \| "opening_element"	required	Secondary dimension to cross with
`metric`	"cpl" \| "ctr" \| "cpc" \| "frequency"	optional	Metric to rank by. Defaults to cpl.
`date_from`	string	optional	Optional start date in YYYY-MM-DD
`date_to`	string	optional	Optional end date in YYYY-MM-DD
`min_spend`	number	optional	Optional minimum spend threshold per ad
`cohort`	"objective"	optional	Set to 'objective' to compute one matrix per campaign objective family instead of pooling every campaign together.
`objective_family`	"leads" \| "sales" \| "traffic" \| "awareness" \| "engagement" \| "app" \| "unknown"	optional	With cohort='objective', restrict results to one objective family.

Example call

{
  "tool": "zuckerbot_creative_cross_analysis",
  "arguments": {
    "group_by": "hook_type",
    "cross_by": "hook_type"
  }
}

You never invoke this directly — describe what you want in plain English inside Claude, Cursor, ChatGPT or any MCP client with ZuckerBot connected, and the agent selects zuckerbot_creative_cross_analysis and fills the arguments for you.

Related tools — Creative analysis

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