[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6HBKAJWQC8TKFRJ8Y0A94MH":3,"skill-same:01M6HBKAJWQC8TKFRJ8Y0A94MH":88},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":33,"publishedAt":54,"linkOnly":55,"markdownContent":56,"markdownBody":57,"frontMatter":58,"refName":68,"commitSha":69,"skillDirectory":70,"forksCount":13,"repositoryHtmlUrl":71,"repositoryHomepageUrl":6,"ownerHtmlUrl":72,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":73,"install":74,"resources":87},"01M6HBKAJWQC8TKFRJ8Y0A94MH","campaign-analytics",null,"Analyzes campaign performance with multi-touch attribution, funnel conversion analysis, and ROI calculation for marketing optimization. Use when analyzing marketing campaigns, ad performance, attribution models, conversion rates, or calculating marketing ROI, ROAS, CPA, and campaign metrics across channels.","omarcelomoro\u002Fopenclaw-backup","omarcelomoro","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F270167219?v=4","01M6HBFFKGV65HGZNC9CHJ6QVB","01M6HBFFR9QS7RMTXWRRV4QWRB",0,"MIT","https:\u002F\u002Fgithub.com\u002Fomarcelomoro\u002Fopenclaw-backup\u002Fblob\u002Fmain\u002Fskills\u002Fcampaign-analytics\u002FSKILL.md",[17,22,25,30],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000013","分析与可视化","SCENARIO","使用场景",{"categoryNo":23,"categoryName":24,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000019","营销推广",{"categoryNo":26,"categoryName":27,"taxonomyType":28,"taxonomyTypeDesc":29},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",{"categoryNo":31,"categoryName":32,"taxonomyType":28,"taxonomyTypeDesc":29},"01JBSEEDCAT000000000000035","市场营销",[34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53],"analytics","campaign analytics","campaign","for","review","calculation","with","channels","touch","campaigns","across","imported","conversion","use","calculator","analysis","Optimization","attribution","roi","performance","2026-11-10 10:12:30",false,"---\nname: \"campaign-analytics\"\ndescription: Analyzes campaign performance with multi-touch attribution, funnel conversion analysis, and ROI calculation for marketing optimization. Use when analyzing marketing campaigns, ad performance, attribution models, conversion rates, or calculating marketing ROI, ROAS, CPA, and campaign metrics across channels.\nlicense: MIT\nsource: LeoYeAI\u002Fopenclaw-master-skills\nstatus: imported-for-leevre-review\nmetadata:\n version: 1.0.0\n author: Alireza Rezvani\n category: marketing\n domain: campaign-analytics\n updated: 2026-02-06\n python-tools: attribution_analyzer.py, funnel_analyzer.py, campaign_roi_calculator.py\n tech-stack: marketing-analytics, attribution-modeling\n---\n\n# Campaign Analytics\n\nProduction-grade campaign performance analysis with multi-touch attribution modeling, funnel conversion analysis, and ROI calculation.\n\n## Leevre adaptation notes\n- Use to measure content and paid campaign performance across Instagram, TikTok, landing pages, WhatsApp entrypoints, and email.\n- Prioritize simple business outputs first: lead volume, qualified leads, appointments, proposals, closed sales, CPA, and channel ROI.\n- Pair with `analytics-tracking` to define naming conventions before analyzing performance.\n","# Campaign Analytics\n\nProduction-grade campaign performance analysis with multi-touch attribution modeling, funnel conversion analysis, and ROI calculation.\n\n## Leevre adaptation notes\n- Use to measure content and paid campaign performance across Instagram, TikTok, landing pages, WhatsApp entrypoints, and email.\n- Prioritize simple business outputs first: lead volume, qualified leads, appointments, proposals, closed sales, CPA, and channel ROI.\n- Pair with `analytics-tracking` to define naming conventions before analyzing performance.\n",{"name":5,"source":59,"status":60,"license":14,"metadata":61,"description":7},"LeoYeAI\u002Fopenclaw-master-skills","imported-for-leevre-review",{"author":62,"domain":5,"updated":63,"version":64,"category":65,"tech-stack":66,"python-tools":67},"Alireza Rezvani",1770336000000,"1.0.0","marketing","marketing-analytics, attribution-modeling","attribution_analyzer.py, funnel_analyzer.py, campaign_roi_calculator.py","main","45fe8450c544a79912edbd7cec3777d22cab087d","skills\u002Fcampaign-analytics","https:\u002F\u002Fgithub.com\u002Fomarcelomoro\u002Fopenclaw-backup","https:\u002F\u002Fgithub.com\u002Fomarcelomoro","2026-06-26 01:49:15",{"source":8,"skillName":5,"commands":75,"prompt":85,"zipAvailable":86},[76,79,82],{"tool":77,"command":78},"npx","npx skills add omarcelomoro\u002Fopenclaw-backup --skill campaign-analytics",{"tool":80,"command":81},"bunx","bunx skills add omarcelomoro\u002Fopenclaw-backup --skill campaign-analytics",{"tool":83,"command":84},"pnpm","pnpm dlx skills add omarcelomoro\u002Fopenclaw-backup --skill campaign-analytics","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fomarcelomoro\u002Fopenclaw-backup\u002Fblob\u002Fmain\u002Fskills\u002Fcampaign-analytics\u002FSKILL.md",true,[],[]]