retail-clerk-comparison-analysis

导购对比分析工具。基于clerk-performance-analysis的扩展,提供导购业绩的多维度对比分析。 核心能力: 1. 时间维度对比(培训前后、活动前后、月度环比) 2. 横向对比(多人排名、标杆学习、差距分析) 3. 高频场景(晨会对比、周会报告、绩效对标) 4. 导购能力雷达图对比 5. 业绩贡献度对比 触发条件: - 用户对比导购(如"李翠和杨丽谁业绩好") - 用户需要排名(如"导购业绩排名") - 用户分析差距(如"标杆导购和其他人的差距")

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Install skill "retail-clerk-comparison-analysis" with this command: npx skills add gwyang7/retail-clerk-comparison-analysis

导购对比分析 Skill

技能名称

clerk-comparison-analysis

功能描述

基于 clerk-performance-analysis 的扩展,提供导购业绩的对比分析功能:

  • 时间维度对比:培训前后、活动前后、月度环比等
  • 横向对比:多人排名、标杆学习、差距分析
  • 高频场景:晨会对比、周会报告、绩效对标

依赖关系

本Skill依赖 clerk-performance-analysis

import sys
sys.path.insert(0, '~/.openclaw/skills/clerk-performance-analysis')
from analyze import analyze

核心功能

1. 导购自身时间维度对比

函数: compare_guide_over_time()

使用场景:

场景period_aperiod_bcomparison_label
培训效果评估培训前7天培训后7天"新品销售培训前后"
活动效果复盘活动前7天活动期间"315大促活动期间"
月度环比上月同期本月"3月vs2月环比"
波动归因低谷期高峰期"低谷vs高峰对比"

示例:

from compare import compare_guide_over_time

result = compare_guide_over_time(
    store_id="416759_1714379448487",
    guide_name="李翠",
    period_a_from="2026-03-01",
    period_a_to="2026-03-07",
    period_b_from="2026-03-16",
    period_b_to="2026-03-22",
    comparison_label="新品销售培训前后"
)

输出:

{
  "status": "ok",
  "comparison_label": "新品销售培训前后",
  "period_a": {"from": "...", "to": "...", "metrics": {...}},
  "period_b": {"from": "...", "to": "...", "metrics": {...}},
  "changes": {
    "sales": {"before": 28456, "after": 36103, "change": 7647, "change_pct": 26.9, "trend": "up"},
    "orders": {...},
    "atv": {...},
    "new_customers": {...}
  },
  "key_findings": [...],
  "recommendations": [...]
}

2. 多人导购横向对比

函数: compare_guides()

使用场景:

  • 晨会快速对比昨日表现
  • 周会排名和差距分析
  • 月度绩效对标
  • 标杆学习和经验分享

示例:

from compare import compare_guides

result = compare_guides(
    store_id="416759_1714379448487",
    guide_names=["李翠", "杨丽", "赵泽瑞", "陈二妹"],
    from_date="2026-03-25",
    to_date="2026-03-25"
)

输出:

{
  "status": "ok",
  "total_guides": 4,
  "rankings": {
    "by_sales": [...],
    "by_new_customers": [...],
    "by_atv": [...]
  },
  "top_performer": {...},
  "bottom_performer": {...},
  "gap_analysis": [...],
  "needs_attention": [...],
  "quick_insights": [...]
}

3. 标杆对比(找差距)

函数: compare_with_benchmark()

使用场景:

  • 待提升导购与标杆对比
  • 生成个性化改进计划
  • 一对一辅导准备

示例:

from compare import compare_with_benchmark

result = compare_with_benchmark(
    store_id="416759_1714379448487",
    guide_name="陈二妹",           # 待提升导购
    benchmark_guide_name="李翠",   # 标杆导购
    from_date="2026-03-01",
    to_date="2026-03-25"
)

输出:

{
  "status": "ok",
  "guide": {"name": "陈二妹", "metrics": {...}},
  "benchmark": {"name": "李翠", "metrics": {...}},
  "gaps": {
    "sales": {"guide_value": 31922, "benchmark_value": 64559, "gap": 32637, "gap_pct": 50.6},
    "new_customers": {...}
  },
  "learning_points": [...],
  "action_plan": [...]
}

高频使用场景

场景1:晨会快速对比(每日)

# 店长每日晨会前自动生成
report = compare_guides(
    store_id="...",
    guide_names=["李翠", "杨丽", "赵泽瑞", "陈二妹"],
    from_date=yesterday,
    to_date=yesterday
)

# 推送到店长企业微信
send_morning_meeting_report(report)

输出示例:

═══════════════════════════════════════════════════════
导购横向对比 - 正义路60号店
2026-03-25(昨日)
═══════════════════════════════════════════════════════

【销售额排名】
#1  活动导购  ¥3,529  (25%)  7单  ¥504  ✅
#2  李翠      ¥3,111  (22%)  4单  ¥778  
#3  杨丽      ¥2,115  (15%)  3单  ¥705  
#4  陈二妹    ¥0      (0%)   0单  ¥0    ⚠️ 无销售

【需要关注】
⚠️ 陈二妹: 昨日无销售,近14天有4天无销售

【今日建议】
1. 店长重点关注陈二妹
2. 李翠分享高客单价经验

场景2:培训效果评估(培训后7天)

result = compare_guide_over_time(
    store_id="...",
    guide_name="李翠",
    period_a_from="2026-03-01",  # 培训前
    period_a_to="2026-03-07",
    period_b_from="2026-03-16",  # 培训后
    period_b_to="2026-03-22",
    comparison_label="新品销售培训前后"
)

if result['changes']['sales']['change_pct'] > 20:
    print("✅ 培训效果显著,销售额提升20%+")
else:
    print("⚠️ 培训效果不明显,需要复盘")

场景3:月度绩效对标(每月底)

# 生成本月完整对比报告
report = compare_guides(
    store_id="...",
    guide_names=all_guides_in_store,
    from_date="2026-03-01",
    to_date="2026-03-31"
)

# 生成绩效考核表
generate_performance_table(report)

场景4:标杆学习(按需)

# 找出差距最大的导购与标杆对比
result = compare_with_benchmark(
    store_id="...",
    guide_name="陈二妹",
    benchmark_guide_name="李翠",
    from_date="...",
    to_date="..."
)

# 生成一对一辅导计划
coaching_plan = result['action_plan']

输出指标说明

时间对比指标

指标说明用途
change绝对变化值量化改进幅度
change_pct变化百分比评估改进比例
trend变化趋势up/down/stable

横向对比指标

指标说明用途
gap_to_top与标杆的销售额差距量化提升空间
gap_pct差距百分比评估追赶难度
potential达到标杆的潜在收益激励改进

诊断规则

时间对比诊断

发现类型判断条件建议
显著提升销售额提升>30%固化成功经验
显著下滑销售额下滑>30%分析原因并干预
问题改善发现数量减少肯定改进效果

横向对比诊断

发现类型判断条件建议
业绩集中TOP3贡献>70%关注尾部导购
新客差异最大/最小>3倍推广标杆经验
高风险有high severity finding立即干预

版本

v1.0.0 - 导购对比分析Skill(支持时间对比和横向对比)

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