Task Plan: 电商用户流失影响因素分析【免费下载链接】planning-with-filesPersistent file-based planning for AI coding agents and long-running tasks. Crash-proof markdown plans, session recovery after /clear and compaction, per-turn re-injection against context rot, deterministic completion gate. Manus-style. Install from npm, the Claude Code plugin marketplace, or npx skills. Codex, Cursor, OpenCode, 60 agents.项目地址: https://gitcode.com/GitHub_Trending/pl/planning-with-filesGoal确定过去 12 个月中与用户流失最显著相关的行为特征并输出一份可行动的留存建议清单。Current PhasePhase 1PhasesPhase 1: Data DiscoveryIdentify and connect to data sourcesorders 表、users 表、support_tickets 表Document schemas and field descriptions in findings.mdAssess data quality (nulls, duplicates, outliers, date ranges)Estimate dataset size and query performanceStatus:completePhase 2: Exploratory AnalysisCompute summary statistics for key variablesVisualize distributions and relationshipsIdentify outliers and anomaliesDocument initial patterns in findings.mdStatus:in_progressPhase 3: Hypothesis TestingFormalize hypotheses from exploratory phaseSelect appropriate statistical testsRun tests and record results in findings.mdValidate findings against holdout data or alternative methodsStatus:pendingPhase 4: Synthesis ReportingSummarize key findings with supporting evidenceCreate final visualizationsDocument conclusions and recommendationsNote limitations and areas for further investigationStatus:pendingHypotheses首单后 30 天内登录次数 ≤ 2 的用户流失率显著更高。售后工单数 ≥ 3 与流失显著正相关。Decisions MadeDecisionRationale流失定义为 90 天无任何行为与业务留存周期一致避免把低频用户误判为流失使用 Cox 回归而非逻辑回归可处理流失时间点的右删失数据Errors EncounteredErrorAttemptResolutionorders 表日期字段为空字符串导致 JOIN 丢行1先清洗 date_parsed 列并记录清洗规则到 findings.mdNotes更新阶段状态pending → in_progress → complete重大决策前重读 Goal 与 Current Phase查询结果与可视化发现及时记录到 findings.md【免费下载链接】planning-with-filesPersistent file-based planning for AI coding agents and long-running tasks. Crash-proof markdown plans, session recovery after /clear and compaction, per-turn re-injection against context rot, deterministic completion gate. Manus-style. Install from npm, the Claude Code plugin marketplace, or npx skills. Codex, Cursor, OpenCode, 60 agents.项目地址: https://gitcode.com/GitHub_Trending/pl/planning-with-files创作声明：本文部分内容由AI辅助生成（AIGC），仅供参考 Task Plan: 电商用户流失影响因素分析
Task Plan: 电商用户流失影响因素分析【免费下载链接】planning-with-filesPersistent file-based planning for AI coding agents and long-running tasks. Crash-proof markdown plans, session recovery after /clear and compaction, per-turn re-injection against context rot, deterministic completion gate. Manus-style. Install from npm, the Claude Code plugin marketplace, or npx skills. Codex, Cursor, OpenCode, 60 agents.项目地址: https://gitcode.com/GitHub_Trending/pl/planning-with-filesGoal确定过去 12 个月中与用户流失最显著相关的行为特征并输出一份可行动的留存建议清单。Current PhasePhase 1PhasesPhase 1: Data DiscoveryIdentify and connect to data sourcesorders 表、users 表、support_tickets 表Document schemas and field descriptions in findings.mdAssess data quality (nulls, duplicates, outliers, date ranges)Estimate dataset size and query performanceStatus:completePhase 2: Exploratory AnalysisCompute summary statistics for key variablesVisualize distributions and relationshipsIdentify outliers and anomaliesDocument initial patterns in findings.mdStatus:in_progressPhase 3: Hypothesis TestingFormalize hypotheses from exploratory phaseSelect appropriate statistical testsRun tests and record results in findings.mdValidate findings against holdout data or alternative methodsStatus:pendingPhase 4: Synthesis ReportingSummarize key findings with supporting evidenceCreate final visualizationsDocument conclusions and recommendationsNote limitations and areas for further investigationStatus:pendingHypotheses首单后 30 天内登录次数 ≤ 2 的用户流失率显著更高。售后工单数 ≥ 3 与流失显著正相关。Decisions MadeDecisionRationale流失定义为 90 天无任何行为与业务留存周期一致避免把低频用户误判为流失使用 Cox 回归而非逻辑回归可处理流失时间点的右删失数据Errors EncounteredErrorAttemptResolutionorders 表日期字段为空字符串导致 JOIN 丢行1先清洗 date_parsed 列并记录清洗规则到 findings.mdNotes更新阶段状态pending → in_progress → complete重大决策前重读 Goal 与 Current Phase查询结果与可视化发现及时记录到 findings.md【免费下载链接】planning-with-filesPersistent file-based planning for AI coding agents and long-running tasks. Crash-proof markdown plans, session recovery after /clear and compaction, per-turn re-injection against context rot, deterministic completion gate. Manus-style. Install from npm, the Claude Code plugin marketplace, or npx skills. Codex, Cursor, OpenCode, 60 agents.项目地址: https://gitcode.com/GitHub_Trending/pl/planning-with-files创作声明：本文部分内容由AI辅助生成（AIGC），仅供参考