Insurance Agent Intelligent Trainer
AI-powered insurance agent training coach — auto-parses product docs, generates question banks, assesses agent skill levels (beginner/intermediate/advanced), schedules personalized…
lingfeng-19
@gechengling
What This Skill Does
AI-powered insurance agent training coach that auto-parses product documents, generates personalized question banks, assesses agent skill levels (beginner/intermediate/advanced), schedules daily training based on client visit schedules, and runs interactive role-play drills. Updated for 2025-2026 regulatory changes including the 3.0% predining rate cut impact on sales scripts and new health insurance regulations.
Replaces manual training content creation and generic coaching by auto-generating personalized question banks and role-play scenarios tailored to each agent's skill level and daily client visit schedule.
When to Use It
- Generate a question bank from a new insurance product document for agent training
- Assess an agent's current skill level (beginner/intermediate/advanced) before assigning training modules
- Schedule personalized daily training exercises based on an agent's upcoming client visit appointments
- Run interactive role-play drills for handling common customer objections during insurance sales
- Update sales scripts to reflect the latest regulatory changes like the 3.0% predining rate cut
- Create a compliance-focused training session on PIPL-compliant customer communication for agents
Install
$ openclaw skills install @gechengling/insurance-agent-trainerInsurance Agent Intelligent Trainer / 保险代理人智能陪练系统
⚠️ SECURITY NOTICE / 安全声明
- Type: Educational reference / analytical framework ONLY
- No executable code, scripts, or binaries are included in this skill
- No persistent storage, network calls, background execution, or credential collection
- All outputs are for reference only and require human review before real-world application
- This skill does NOT provide financial, legal, or insurance advice
- Users must exercise their own judgment and consult qualified professionals
⚠️ 数据安全警告
- 本技能仅提供保险代理人的培训辅导参考框架,不执行任何代码或脚本
- 所有文档解析、日程分析、画像评估的描述均为教学参考框架,不包含实际的OCR或PDF解析引擎
- 不会自动访问、存储或处理用户的任何培训数据或个人信息
- 培训计划和话术建议需结合用户实际业务场景调整,不能替代专业培训师
- 销售话术和异议处理仅为培训参考,实际使用须遵守《保险法》及相关监管规定,不得以AI输出替代合规审核
English: AI-powered insurance agent coaching system — parses product documents, generates personalized question banks, assesses agent competency levels, schedules daily training based on client visits, and runs interactive role-play drills. Benchmarked against AIA, Ping An, and Alibaba Cloud insurance training systems.
中文: 保险代理人智能陪练系统——解析产品文档、自动生成问题库、评估代理人能力等级、 结合当日客户拜访行程安排个性化训练、进行情景对练。对标友邦保险、平安保险、阿里云智能陪练水平。
Trigger Keywords / 触发关键词
⚠️ 精确触发规则:仅当用户明确提到保险代理人培训/陪练相关需求时激活。日常对话中提及"培训"、"训练"、"coaching"、"agent training"等通用词汇时不会自动触发。
用户确认规则:当用户输入匹配以下关键词时,必须先确认用户意图:
- "您需要保险代理人陪练/培训服务吗?"
- 仅在用户明确确认后,才进入陪练模式
激活关键词(需用户确认后生效):
- 保险陪练 / 产品陪练 / 智能陪练 / 代理人训练
- 代理人培训 / 新人培训 / 保险话术训练
- 产品演练 / 客户异议处理 / 保险销售训练
- insurance agent training / insurance coaching / insurance product drill
Core System Architecture / 核心系统架构
0. 2025-2026 代理人销售环境最新变化(截至2026-08)
| 变化 | 内容 | 话术调整建议 |
|---|---|---|
| 预定利率降至3.0% | 2024年9月后所有新产品执行 | 强调"锁定3.0%长期确定收益",对比银行理财波动性 |
| 分红险主导市场 | 分红险、万能险替代传统高利率产品 | 学会讲"浮动收益+保底保障"的双重价值 |
| 健康险新规上线 | 2025年商业健康险管理办法修订 | 健康告知流程需更规范,禁止误导性说明 |
| 代理人资格考试升级 | 2025年加入AI伦理、数字化服务模块 | 新人需补充数字化能力培训 |
| 企微客户触达合规 | AI外呼需标注身份,营销需客户授权 | 培训合规营销话术,避免违规外呼 |
| 预定利率进一步下调至2.0% | 2026年监管引导普通型人身险预定利率上限降至2.0%,分红/万能演示利率同步压降 | 话术从"锁定3.0%"转为"锁定2.0%长期确定+浮动分红对冲通胀" |
| 营销宣传合规强化 | 2026年整治"炒停售""夸大收益",自媒体/直播带货纳入监管 | 培训合规表达,禁用绝对化收益承诺与演示红线 |
| 养老金融与税优扩容 | 个人养老金、商业养老金试点扩围,税优额度可期上调 | 强化养老规划与税优测算话术,绑定家庭现金流诊断 |
┌─────────────────────────────────────────────────────────────────┐
│ Insurance Agent Intelligent Trainer │
├─────────────────────────────────────────────────────────────────┤
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────────────┐ │
│ │ Product Doc │ │ Agent Profile│ │ Daily Schedule/Routes│ │
│ │ Parser │ │ Engine │ │ Integration │ │
│ │ (PDF/Word/ │ │ (Skill Level │ │ (Today's Visits & │ │
│ │ Images) │ │ Assessment) │ │ Client Profiles) │ │
│ └──────┬───────┘ └──────┬───────┘ └──────────┬───────────┘ │
│ │ │ │ │
│ ▼ ▼ ▼ │
│ ┌──────────────────────────────────────────────────────────┐ │
│ │ Question Bank Generation Engine │ │
│ │ Product Knowledge │ Objection Handling │ Case Analysis │ │
│ │ [5 difficulty tiers × 3 categories = 15 question types] │ │
│ └──────────────────────────┬───────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌──────────────────────────────────────────────────────────┐ │
│ │ Personalized Training Scheduler │ │
│ │ [Skill Level + Schedule + Product Priority = Daily Plan]│ │
│ └──────────────────────────┬───────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌──────────────────────────────────────────────────────────┐ │
│ │ Interactive Training Engine │ │
│ │ Role-play │ Real-time Feedback │ Progress Tracking │ │
│ └──────────────────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────────┘
Core Capabilities / 核心能力
1. Product Document Parser / 产品文档解析引擎(教学演示)
⚠️ 教学演示:以下展示产品文档解析的概念性教学方法论,仅说明AI可如何辅助理解产品结构。本技能不执行任何实际的PDF解析、OCR识别或文档提取操作。 所有"解析流程"均为逻辑示意,实际应用需由具体的工程实现完成。
Supported formats (conceptual): PDF, Word (.docx), scanned images (with OCR), plain text
Conceptual parsing pipeline (for reference):
Document Upload
│
▼
[Format Detection] → PDF / Word / Image / Text
│
▼
[Text Extraction] → Raw text content
│
▼
[Structure Analysis]
├─ Product name, type, target customers
├─ Coverage scope (death, medical, annuity, critical illness, etc.)
├─ Premium levels & payment periods
├─ Policy terms & exclusions
├─ Sales pitch key points
├─ Competitive advantages vs. similar products
└─ Compliance notes & regulatory requirements
│
▼
[Structured Product Profile] → Ready for question generation
Output: Structured Product Profile JSON
{
"product_name": "XX福享人生终身寿险(万能型)",
"product_type": "whole-life insurance with universal account",
"insurer": "国联人寿",
"target_customers": ["30-50岁中高收入人群", "有财富传承需求"],
"coverage": {
"death_benefit": "100%-160%账户价值",
"annuity_option": "60岁起可转换为年金",
"waiver": "可选投保人保费豁免"
},
"premium": {
"min_annual": 12000,
"payment_periods": ["3年", "5年", "10年", "20年"],
"min_coverage_years": "终身"
},
"key_selling_points": [
"复利增值,万能账户历史结算利率4.5%-5.2%",
"灵活追加,额外资金可随时进入万能账户",
"身故保障与财富传承双重功能"
],
"competitive_edges": ["结算利率优于同类竞品", "追加无上限"],
"exclusions": ["投保人对被保险人的故意伤害", "2年内自杀(无民事行为能力人除外)"],
"compliance_notes": ["需双录(录音录像)", "犹豫期15天", "等待期90天"],
"difficulty_tags": ["新人友好", "需强化健康告知", "财务规划综合能力"]
}
**示例产品画像 2(重大疾病保险):**
```json
{
"product_name": "XX康健终身重疾险(2026版)",
"product_type": "critical illness insurance",
"insurer": "国联人寿",
"target_customers": ["28-50岁家庭经济支柱", "有重疾保障缺口人群"],
"coverage": {
"ci_types": "120种重疾+20种中症+40种轻症",
"multiple_payout": "重疾1次+中症2次+轻症3次,累计最高260%保额",
"death_benefit": "身故赔已交保费或现金价值较大者"
},
"premium": {
"sample": "30岁男,50万保额,30年缴,年缴约 6800 元",
"payment_periods": ["10年","20年","30年"]
},
"key_selling_points": [
"重疾+中症+轻症三重递进保障",
"轻中症豁免后续保费",
"可附加恶性肿瘤二次赔付"
],
"exclusions": ["投保前已患重疾", "遗传性疾病(条款约定)", "等待期内出险"],
"compliance_notes": ["重疾定义以监管规范为准", "需明确告知等待期90-180天", "如实健康告知义务"],
"difficulty_tags": ["健康告知敏感", "条款专业度高", "需结合医疗知识"]
}
---
### 2. Agent Profile & Skill Assessment / 代理人画像与能力评估
> **⚠️ 数据处理提醒**:以下代理人画像和日程数据为**演示示例**。实际使用时,用户应自行管理代理人数据的收集和存储,确保符合《个人信息保护法》及保险行业合规要求。请勿输入真实客户PII信息。
**Three skill tiers:**
| Tier | Level | Description | Training Focus | 建议训练时长/周 |
|------|-------|-------------|----------------|----------------|
| 🌱 **L1 - 入门级** | Beginner | < 1 year experience, struggles with product details and objection handling | Foundation: product knowledge, basic sales scripts, simple objection responses | 5-8 小时(晨会快练+情景对练) |
| ⚡ **L2 - 进阶级** | Intermediate | 1-3 years, solid product knowledge but inconsistent closing rate | Application: complex scenarios, multi-product combination, competitive replacement, high-net-worth clients | 3-5 小时(聚焦弱项情景对练) |
| 🎯 **L3 - 专家级** | Advanced | 3+ years, high performance, needs strategy for complex cases | Mastery: enterprise/group clients, tax planning, estate planning, competitive stealing, mentoring skills | 2-3 小时(策略复盘+带教新人) |
**Profile structure:**
```json
{
"agent_id": "AG20240001",
"name": "张明",
"level": "L2",
"level_label": "进阶级",
"tenure_years": 2.5,
"certifications": ["保险代理人资格证", "健康险销售资质"],
"performance": {
"monthly_premium_target": 50000,
"monthly_premium_actual": 42000,
"closing_rate": 0.32,
"avg_policy_size": 18500,
"new_customer_rate": 0.45
},
"product_mastery": {
"term_life": 0.85,
"whole_life": 0.72,
"critical_illness": 0.58,
"medical_insurance": 0.80,
"annuity": 0.45,
"investment_linked": 0.38
},
"weak_points": [
"健康险异议处理不够熟练",
"不了解高端客户的税务筹划需求",
"组合产品销售话术单一"
],
"strong_points": [
"老客户维护能力强",
"缘故市场开拓优秀"
],
"daily_schedule": [
{"time": "09:00-10:00", "activity": "晨会", "location": "营业部"},
{"time": "10:30-12:00", "activity": "拜访客户A(国企中层,有养老需求)", "location": "客户公司"},
{"time": "14:00-15:30", "activity": "拜访客户B(私企业主,健康险需求)", "location": "客户公司"},
{"time": "16:00-17:30", "activity": "缘故客户C(教育金规划)", "location": "咖啡厅"}
]
}
**示例画像 2(L3 专家级):**
```json
{
"agent_id": "AG20230088",
"name": "李华",
"level": "L3",
"level_label": "专家级",
"tenure_years": 6,
"certifications": ["保险代理人资格证", "CFP国际金融理财师", "私人银行家"],
"performance": {
"monthly_premium_target": 200000,
"monthly_premium_actual": 235000,
"closing_rate": 0.48,
"avg_policy_size": 86000,
"new_customer_rate": 0.62
},
"product_mastery": {
"term_life": 0.95, "whole_life": 0.92, "critical_illness": 0.90,
"medical_insurance": 0.93, "annuity": 0.88, "investment_linked": 0.82
},
"weak_points": ["家族信托等复杂传承架构经验不足", "跨境税务筹划需外部专家协同"],
"strong_points": ["高净值客户经营", "企业团险开拓", "复杂方案设计"],
"coaching_focus": ["传承架构进阶", "监管合规红线强化", "带教新人方法论"]
}
---
### 3. Question Bank Generation / 问题库自动生成(教学模板)
> **⚠️ 教学演示**:以下问题库和话术为**培训场景的教学参考模板**,展示如何结构化设计代理人训练内容。所有涉及销售话术、竞品对比、异议处理的内容均为**培训素材**,实际销售行为须遵循《保险法》及相关监管规定,并经持牌保险专业人士审核后方可执行。
**Generated from product profile + agent level + training objectives**
#### Question Types (15 categories across 3 dimensions)
**By Category:**
| Category | Description | Example | 考核重点 |
|----------|-------------|---------|---------|
| **产品知识** | Product features, terms, coverage | "XX福的等待期是多久?" | 条款准确性、关键利益点无误 |
| **客户画像** | Target customer identification | "什么样的客户适合购买这款产品?" | 需求诊断与匹配逻辑 |
| **异议处理** | Objection handling scripts | "客户说'我已经有社保了,不需要商业保险',如何回应?" | 共情+数据化反驳能力 |
| **案例分析** | Real case discussion | "40岁国企中层,年薪50万,如何用这款产品做养老规划?" | 方案完整性与定制化 |
| **合规话术** | Compliance-approved scripts | "如何向客户解释犹豫期和退保损失?" | 红线词零触发 |
| **竞品对比** | vs. competitors | "相比平安福,这款产品的核心优势是什么?" | 客观不贬损竞品 |
| **促成话术** | Closing techniques | "客户表现出购买意向,如何自然促成?" | 时机把握自然度 |
| **交叉销售** | Multi-product combination | "如何将主险与医疗险组合销售?" | 保障缺口覆盖度 |
| **养老规划** | 养老现金流与替代率测算 | "客户55岁期望退休月领8000,如何测算缺口?" | 测算逻辑与工具使用 |
| **税优保险** | 个人养老金/税优健康险政策应用 | "年缴1.2万养老金,节税多少?" | 政策准确、不夸大节税 |
**By Difficulty (5 tiers):**
| Level | Target Audience | Question Complexity | 建议题量/次 |
|--------|----------------|---------------------|------------|
| ⭐ 基础 | L1新人 | 单一产品,单一问题,直接答案 | 10-15 题 |
| ⭐⭐ 入门 | L1-L2 | 单一产品,1-2个知识点,需要解释 | 15-20 题 |
| ⭐⭐⭐ 进阶 | L2 | 单一产品,3-5个知识点,需组合分析 | 20-30 题 |
| ⭐⭐⭐⭐ 高阶 | L2-L3 | 多产品组合,竞争替换,高净值客户 | 25-35 题 |
| ⭐⭐⭐⭐⭐ 专家 | L3 | 综合方案,税务筹划,财富传承 | 30-40 题 |
#### Question Bank Generation Prompt:
Based on the product profile provided, generate a question bank with:
-
For each difficulty tier (基础/入门/进阶/高阶/专家):
- 5 multiple choice questions (产品知识)
- 3 case analysis questions
- 3 objection handling scenarios
- 2 competitive comparison questions
- 1 closing technique exercise
-
Total: 65+ questions per product
-
For each question, provide:
- Question text
- Difficulty level (1-5)
- Category (产品知识/异议处理/案例分析/竞品对比/促成话术)
- Ideal answer / model response
- Evaluation criteria (excellent/good/needs-improvement)
- Coaching tips for the trainer
**示例生成题目(养老规划类别 / ⭐⭐⭐ 进阶):**
- **题目**:客户 55 岁,当前社保养老金预计月领 3500 元,期望退休后月生活支出 8000 元,如何测算商业养老金缺口?
- **参考答案**:缺口 = (8000 - 3500) × 12 × 退休年限(按 25 年计)≈ 135 万;结合预期投资收益率反推年缴/趸交金额,并叠加通胀与医疗支出弹性。
- **评分**:优秀(准确测算+工具使用)/ 良好(逻辑正确但忽略通胀)/ 待改进(未考虑长寿风险)。
- **教练提示**:引导代理人用"替代率"概念切入,避免直接推销产品。
---
### 4. Personalized Training Scheduler / 个性化训练调度引擎(方法论演示)
> **⚠️ 教学演示**:以下调度算法、代理人画像及日程数据均为**教学方法论的概念性展示**。**本技能不实际采集、存储或处理任何代理人或客户数据**。所有姓名、日程、业绩数据均为虚构示例,仅用于说明逻辑框架。
**Input factors:**
Agent Profile (Level + Weak Points) + Today's Client Schedule (Who → What need → What product) + Product Priority Matrix = Personalized Daily Training Plan
**Scheduling Algorithm:**
```python
def generate_daily_training_plan(agent_profile, daily_schedule, products):
"""
Generate personalized training plan for the day.
"""
# Step 1: Identify today's client visit products
today_products = extract_products_from_schedule(daily_schedule)
# Step 2: Get agent's weakness areas for these products
weakness_map = get_weakness_for_products(
agent_profile.weak_points,
today_products
)
# Step 3: Calculate training time available
available_minutes = calculate_available_training_time(daily_schedule)
# Step 4: Prioritize by impact × weakness × product value
training_queue = prioritize_training(
weakness_map,
today_products,
agent_profile.level,
time_constraint=available_minutes
)
# Step 5: Generate session plan
sessions = split_into_sessions(training_queue, available_minutes)
return {
"date": today,
"agent": agent_profile.name,
"total_minutes": available_minutes,
"sessions": sessions,
"focus_products": today_products,
"key_objectives": get_key_objectives(training_queue)
}
Example Daily Training Plan:
{
"date": "2026-05-05",
"agent": "张明",
"level": "L2",
"total_minutes": 90,
"sessions": [
{
"time": "08:00-08:20",
"duration": 20,
"type": "晨间快练",
"mode": "快问快答",
"focus": "年金险产品知识(高频问题5题)",
"product": "福享人生终身寿险",
"objective": "巩固年金转换权的计算逻辑"
},
{
"time": "12:30-13:00",
"duration": 30,
"type": "午间强化",
"mode": "情景对练",
"focus": "健康险异议处理",
"scenario": "客户:"我有社保,不需要商业医疗险"",
"product": "康健医疗保险",
"level": "⭐⭐⭐ 进阶",
"coaching_tips": "引导客户认识到社保报销比例上限,用自费药比例对比引发需求"
},
{
"time": "17:30-18:30",
"duration": 40,
"type": "晚间复盘",
"mode": "案例分析 + 角色扮演",
"focus": "私企业主综合保障方案",
"scenario": "45岁私企老板,年收入200万,已有多份保单,如何做加保方案?",
"products": ["终身寿险+万能账户", "高端医疗", "企业财产险"],
"level": "⭐⭐⭐⭐ 高阶",
"model_response_guide": "从家庭资产与企业资产隔离角度切入,引出终身寿险的债务隔离和传承功能"
}
],
"key_metrics_to_track": [
"异议处理响应时间(目标<30秒)",
"产品知识点正确率(目标>85%)",
"方案组合完整性(3单以上产品覆盖)"
]
}
**示例计划 2(健康险异议攻坚日):**
```json
{
"date": "2026-08-12",
"agent": "李华",
"level": "L3",
"total_minutes": 60,
"sessions": [
{
"time": "13:00-13:20",
"duration": 20,
"type": "午间强化",
"mode": "异议攻关",
"focus": "健康险'已有社保'高频异议",
"scenario": "客户:'我有医保,重疾险没必要'",
"level": "⭐⭐⭐ 进阶",
"coaching_tips": "用'医保目录外用药+收入补偿'双轴拆解,量化缺口而非否定客户"
},
{
"time": "18:00-18:40",
"duration": 40,
"type": "晚间复盘",
"mode": "案例研讨 + 角色扮演",
"focus": "高净值客户重疾+医疗+寿险组合",
"scenario": "50岁企业主,家庭年收入300万,已有多张保单如何查漏补缺?",
"level": "⭐⭐⭐⭐ 高阶",
"model_response_guide": "从企业资产与家庭资产隔离、重疾收入补偿、医疗高端资源三维度切入"
}
],
"key_metrics_to_track": [
"异议处理响应时间(目标<25秒)",
"方案组合维度(目标≥4个)",
"合规红线触发(目标0次)"
]
}
---
### 5. Interactive Training Session / 智能陪练对话引擎
**Session modes:**
| Mode | Description | Duration | Best For | 适用场景 |
|------|-------------|----------|----------|---------|
| **快问快答** | Rapid-fire Q&A | 5-10 min | Pre-meeting warmup | 晨会热身、拜访前激活产品知识 |
| **情景对练** | Role-play (client vs. agent) | 15-30 min | Skill practice | 健康险/养老险高频异议实战 |
| **案例研讨** | Real case analysis | 20-40 min | Advanced agents | 高净值综合保障方案设计 |
| **异议攻关** | Objection busting focus | 10-15 min | Weak point training | 单一弱项(如"已有社保")专项突破 |
| **综合考核** | Full simulation exam | 30-60 min | Level assessment | 晋升/季度能力认证 |
| **直播带练** | 模拟自媒体/直播讲保险 | 15-25 min | 数字化展业 | 合规表达与镜头前讲产品 |
**Real-time coaching during training:**
Agent Response │ ▼ [Natural Language Understanding] → Extract key claims, tone, strategy │ ▼ [Evaluation Engine] ├─ Product knowledge accuracy ✓/✗ ├─ Objection handling effectiveness (1-5) ├─ Compliance adherence ✓/✗ ├─ Closing attempt timing (good/early/late/missing) ├─ Client empathy signals ✓/✗ └─ Product combination logic ✓/✗ │ ▼ [Real-time Coaching Feedback] ├─ Immediate tip (if struggling): "💡 提示:可以先问客户目前的保障缺口..." ├─ Completion praise (if excellent): "🌟 完美!您已经很好地识别了客户需求" └─ Post-question summary: "本轮得分 85/100。建议加强:竞品对比环节"
**Training session flow:**
- 导入 (5%) → 介绍训练目标和产品背景
- 暖场 (10%) → 快问快答热身,激活产品知识
- 主体 (60%) → 情景对练:客户角色扮演 + 实时点评
- 复盘 (20%) → AI给出详细反馈:优点/不足/改进建议
- 行动 (5%) → 下次拜访的具体行动计划
**示例对练对话片段(健康险异议攻关):**
AI(客户): "我单位福利好,重疾险真没必要买。" Agent: "您说的对,单位福利是重要保障。不过重疾理赔是'确诊即付'的一笔钱——您想过没有,万一需要长期康复,单位会不会照发全额工资?" AI(客户): "那倒不会,病假工资大概只发底薪……" Agent: "这就是缺口。重疾险补的正是'收入中断+自费药'这两块。我们按您月支出算一下具体差额?" [实时点评] ✅ 共情到位;✅ 用'收入补偿'替代'恐吓式'话术;⚠️ 下一步应主动给出测算而非直接推产品。
---
### 6. Effect Assessment & Progress Tracking / 效果评估与进度追踪
**Metrics tracked per session:**
| Metric | Definition | Target | 评估方式 |
|--------|------------|--------|---------|
| **产品知识得分** | 知识点正确率 | L1: ≥70%, L2: ≥80%, L3: ≥90% | 自动判分题库 + 人工抽检 |
| **异议处理时效** | 从异议提出到满意回答的时间 | < 30秒 | 对话时间戳测算 |
| **促成成功率** | 能否自然引入促成信号 | ≥ 1次有效尝试 | 教练引擎标记 + 主管复核 |
| **话术合规率** | 合规敏感词使用正确性 | 100% | 合规词库实时监测 |
| **方案完整性** | 保障覆盖广度 | ≥ 3个维度 | 结构化评分表 |
| **合规红线触发率** | 触碰禁语/误导表述次数 | 0 次 | 实时拦截 + 事后复盘 |
**Progress report structure:**
```markdown
## 📊 代理人张明 训练报告 - 2026-05-05
### 综合得分: ⭐⭐⭐⭐ (78/100)
| 维度 | 本次得分 | 较上次 | 目标 |
|------|---------|--------|------|
| 产品知识 | 82/100 | ↑5 | 80+ |
| 异议处理 | 71/100 | ↓3 | 75+ |
| 促成技巧 | 85/100 | ↑8 | 80+ |
| 合规话术 | 95/100 | →0 | 100 |
| 方案设计 | 72/100 | ↑12 | 75+ |
### 🔥 本次表现亮点
1. 养老规划方案逻辑清晰,能结合客户生命周期讲解
2. 合规话术使用规范,犹豫期/退保说明完整
### ⚠️ 需要加强
1. 健康险异议处理:回应"已有社保"时过于被动,应主动算账
2. 竞品对比:对中国平安主要产品线不够熟悉
### 📅 明日训练重点
- 产品:康健医疗保险(健康告知流程)
- 场景:竞品替换(平安福 vs. XX福)
- 时长:30分钟情景对练 + 10分钟快问快答
Workflow / 标准工作流程
⚠️ 重要提示:以下工作流展示的是培训场景的教学参考。所有销售话术和异议处理内容均为培训素材,实际销售行为须遵循《保险法》及相关监管规定,经持牌保险专业人士审核。
Mode 1: Quick Start (已知产品 + 快速训练)
User: "帮我准备明天拜访客户B的训练,他是私企老板,对健康险感兴趣"
│
▼
[Step 1] 获取代理人信息 → 张明,L2,弱项:健康险异议处理
[Step 2] 识别拜访产品 → 康健医疗保险(目标:替换平安福)
[Step 3] 生成训练计划 → 午间30分钟:健康险异议处理对练
[Step 4] 开始陪练 → 情景对练:私企业主健康险需求挖掘
[Step 5] 实时反馈 → 异议处理评分:71/100,给出改进建议
[Step 6] 报告输出 → 训练报告 + 明日拜访话术优化建议
Mode 2: Product Document Upload (上传产品文档)
User: [上传 XX保险公司福享人生终身寿险 产品手册 PDF]
│
▼
[Step 1] 解析文档 → 提取产品结构、条款、卖点
[Step 2] 生成产品画像 → Structured JSON Profile
[Step 3] 生成问题库 → 65+道题目(5难度×8类别)
[Step 4] 生成参考题库 → 作为AI对话上下文,**不持久存储**
[Step 5] 等待选择 → "请选择训练模式:快问快答 / 情景对练 / 案例研讨"
Mode 3: Full Agent Assessment (全面能力评估)
User: "帮我评估代理人李华的综合能力,她入职8个月,主要卖重疾险"
│
▼
[Step 1] 建立代理人档案 → L1入门级,8个月,重疾险方向
[Step 2] 产品文档上传 → 重疾险产品手册
[Step 3] 综合考核 → 30题产品知识 + 5个情景对练
[Step 4] 生成能力雷达图 → 6维度能力可视化
[Step 5] 制定成长路径 → 90天训练计划
Input / Output Specifications / 输入输出规范
Input
| Input Type | Description | Example |
|---|---|---|
| 代理人档案 | JSON/文本描述 | 姓名、级别、工龄、业绩、弱项 |
| 产品文档 | PDF/Word/TXT/图片 | 保险产品手册、条款、计划书 |
| 当日行程 | 文本/日历 | 09:00晨会 / 10:30拜访客户A |
| 训练指令 | 自然语言 | "帮我准备健康险的陪练" |
| 客户信息 | 文本描述 | "45岁私企老板,年收入200万" |
Output
| Output Type | Description |
|---|---|
| 产品画像JSON | 结构化产品信息 |
| 问题库 | 65+道分类分级题目 |
| 训练计划 | 分钟级个性化日程 |
| 陪练对话 | 实时AI角色扮演 |
| 评估报告 | 评分 + 改进建议 + 雷达图 |
| 成长路径 | 30/60/90天训练建议 |
Integration Notes / 集成说明
Data privacy:
- All agent and client data remains local / within the company's system
- No sensitive PII should be included in training documents
- Comply with China CBIRC insurance sales compliance regulations
Lianxi with other Skills:
insurance-bidding-pro: Use product analysis for bidding scenariosinsurance-private-domain-ops: Link training completion to customer follow-upinsurance-claims-intelligence: Train agents on claim processes for better client communication
Disclaimer / 免责声明
⚠️ Training is advisory only. This skill provides coaching materials, question banks, and simulation training for insurance agent development. All final sales advice, compliance decisions, and product recommendations must be reviewed by licensed insurance professionals and comply with CBIRC regulations. Model answers represent reference best practices, not guaranteed outcomes.
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