亚马逊选品深挖
jungle-scout-deep-dive-analyzer · 电商运营 · AI 工具超市官方 · v0.0.101
面向亚马逊选品，用Jungle Scout数据深挖类目机会与竞品，产出选品报告和货源清单。
这个技能能做什么
- 抓取关键词、竞品与趋势等多维数据
- 计算指标框架并拆出8个决策子问题
- 分三档推荐约50个候选产品并生成图表
- 联动查找B2B供货源并输出最终调研报告
什么时候用
- 要进一个新类目，想看数据判断机会到底大不大
- 上新品前想要一份带数据的竞品深挖报告
什么时候别用
只想查单个关键词的数据，用轻量查询工具就够了。
适用场景与行业
配合这些工具用
- ChatExcel
- Claude
怎么安装
在技能超市搜索 jungle-scout-deep-dive-analyzer 一键安装；也可在 AI 助手里直接说"安装 jungle-scout-deep-dive-analyzer 技能"
来源：https://skill.accio.com/skills/phoenix/official/0.0.101/jungle-scout-deep-dive-analyzer.zip
原始英文描述（未经改写）
Jungle Scout API-powered deep market analysis for Amazon product selection. Uses real keyword, competitor, trend and brand-share data to compute an Indicator Data Framework, produce an 8-dimension deep-dive, 3-tier product recommendations (~50 products CSV) and B2B supply sourcing. Bilingual (zh/en). Mandatory deliverable: `final_report.md`. Use when the user wants a data-driven Amazon market analysis backed by Jungle Scout — category opportunity evaluation, competitive deep-dive, or end-to-end product selection. Do NOT use for cross-platform trending/hotselling products or general market trends (use `market-insight-product-selection`); do NOT use for a single Jungle Scout data point (use `jungle_scout_search` in `info_search`). Deep-dive analysis pipeline: Step 1: Detect query language (zh/en) Step 2: Collect Jungle Scout data via ONE jungle_scout_collect call → CSVs Step 3: Compute Indicator Data Framework → JSON Step 4: Detect anomalies → generate 8 decision-oriented sub-questions Step 5: Read CSVs + indicators → write 8 SubQuestionAnswer objects with calculations Step 6: 3-tier product recommendations → ~50 products CSV + charts Step 7: B2B supplier search → Phase A read inputs → Phase B assemble report → Phase C verify → write final_report.md + alibaba_supply.csv
