Sales Engineer Skill
5-Phase Workflow
Phase 1: Discovery & Research
Objective: Understand customer requirements, technical environment, and business drivers.
Checklist:
- - [ ] Conduct technical discovery calls with stakeholders
- [ ] Map customer's current architecture and pain points
- [ ] Identify integration requirements and constraints
- [ ] Document security and compliance requirements
- [ ] Assess competitive landscape for this opportunity
Tools: Run rfp_response_analyzer.py to score initial requirement alignment.
CODEBLOCK0
Output: Technical discovery document, requirement map, initial coverage assessment.
Validation checkpoint: Coverage score must be >50% and must-have gaps ≤3 before proceeding to Phase 2. Check with:
python scripts/rfp_response_analyzer.py assets/sample_rfp_data.json --format json | python -c "import sys,json; r=json.load(sys.stdin); print('PROCEED' if r['coverage_score']>50 and r['must_have_gaps']<=3 else 'REVIEW')"
Phase 2: Solution Design
Objective: Design a solution architecture that addresses customer requirements.
Checklist:
- - [ ] Map product capabilities to customer requirements
- [ ] Design integration architecture
- [ ] Identify customization needs and development effort
- [ ] Build competitive differentiation strategy
- [ ] Create solution architecture diagrams
Tools: Run competitive_matrix_builder.py using Phase 1 data to identify differentiators and vulnerabilities.
CODEBLOCK2
Output: Solution architecture, competitive positioning, technical differentiation strategy.
Validation checkpoint: Confirm at least one strong differentiator exists per customer priority before proceeding to Phase 3. If no differentiators found, escalate to Product Team (see Integration Points).
Phase 3: Demo Preparation & Delivery
Objective: Deliver compelling technical demonstrations tailored to stakeholder priorities.
Checklist:
- - [ ] Build demo environment matching customer's use case
- [ ] Create demo script with talking points per stakeholder role
- [ ] Prepare objection handling responses
- [ ] Rehearse failure scenarios and recovery paths
- [ ] Collect feedback and adjust approach
Templates: Use assets/demo_script_template.md for structured demo preparation.
Output: Customized demo, stakeholder-specific talking points, feedback capture.
Validation checkpoint: Demo script must cover every must-have requirement flagged in phase1_rfp_results.json before delivery. Cross-reference with:
python -c "import json; rfp=json.load(open('phase1_rfp_results.json')); [print('UNCOVERED:', r) for r in rfp['must_have_requirements'] if r['coverage']=='Gap']"
Phase 4: POC & Evaluation
Objective: Execute a structured proof-of-concept that validates the solution.
Checklist:
- - [ ] Define POC scope, success criteria, and timeline
- [ ] Allocate resources and set up environment
- [ ] Execute phased testing (core, advanced, edge cases)
- [ ] Track progress against success criteria
- [ ] Generate evaluation scorecard
Tools: Run poc_planner.py to generate the complete POC plan.
CODEBLOCK4
Templates: Use assets/poc_scorecard_template.md for evaluation tracking.
Output: POC plan, evaluation scorecard, go/no-go recommendation.
Validation checkpoint: POC conversion requires scorecard score >60% across all evaluation dimensions (functionality, performance, integration, usability, support). If score <60%, document gaps and loop back to Phase 2 for solution redesign.
Phase 5: Proposal & Closing
Objective: Deliver a technical proposal that supports the commercial close.
Checklist:
- - [ ] Compile POC results and success metrics
- [ ] Create technical proposal with implementation plan
- [ ] Address outstanding objections with evidence
- [ ] Support pricing and packaging discussions
- [ ] Conduct win/loss analysis post-decision
Templates: Use assets/technical_proposal_template.md for the proposal document.
Output: Technical proposal, implementation timeline, risk mitigation plan.
Python Automation Tools
1. RFP Response Analyzer
Script: INLINECODE7
Purpose: Parse RFP/RFI requirements, score coverage, identify gaps, and generate bid/no-bid recommendations.
Coverage Categories: Full (100%), Partial (50%), Planned (25%), Gap (0%).
Priority Weighting: Must-Have 3×, Should-Have 2×, Nice-to-Have 1×.
Bid/No-Bid Logic:
- - Bid: Coverage >70% AND must-have gaps ≤3
- Conditional Bid: Coverage 50–70% OR must-have gaps 2–3
- No-Bid: Coverage <50% OR must-have gaps >3
Usage:
CODEBLOCK5
Input Format: See assets/sample_rfp_data.json for the complete schema.
2. Competitive Matrix Builder
Script: INLINECODE9
Purpose: Generate feature comparison matrices, calculate competitive scores, identify differentiators and vulnerabilities.
Feature Scoring: Full (3), Partial (2), Limited (1), None (0).
Usage:
CODEBLOCK6
Output Includes: Feature comparison matrix, weighted competitive scores, differentiators, vulnerabilities, and win themes.
3. POC Planner
Script: INLINECODE10
Purpose: Generate structured POC plans with timeline, resource allocation, success criteria, and evaluation scorecards.
Default Phase Breakdown:
- - Week 1: Setup — environment provisioning, data migration, configuration
- Weeks 2–3: Core Testing — primary use cases, integration testing
- Week 4: Advanced Testing — edge cases, performance, security
- Week 5: Evaluation — scorecard completion, stakeholder review, go/no-go
Usage:
CODEBLOCK7
Output Includes: Phased POC plan, resource allocation, success criteria, evaluation scorecard, risk register, and go/no-go recommendation framework.
Reference Knowledge Bases
| Reference | Description |
|---|
| INLINECODE11 | RFP/RFI response best practices, compliance matrix, bid/no-bid framework |
| INLINECODE12 |
Competitive analysis methodology, battlecard creation, objection handling |
|
references/poc-best-practices.md | POC planning methodology, success criteria, evaluation frameworks |
Asset Templates
| Template | Purpose |
|---|
| INLINECODE14 | Technical proposal with executive summary, solution architecture, implementation plan |
| INLINECODE15 |
Demo script with agenda, talking points, objection handling |
|
assets/poc_scorecard_template.md | POC evaluation scorecard with weighted scoring |
|
assets/sample_rfp_data.json | Sample RFP data for testing the analyzer |
|
assets/expected_output.json | Expected output from rfp
responseanalyzer.py |
Integration Points
- - Marketing Skills - Leverage competitive intelligence and messaging frameworks from INLINECODE19
- Product Team - Coordinate on roadmap items flagged as "Planned" in RFP analysis from INLINECODE20
- C-Level Advisory - Escalate strategic deals requiring executive engagement from INLINECODE21
- Customer Success - Hand off POC results and success criteria to CSM from INLINECODE22
Last Updated: February 2026
Status: Production-ready
Tools: 3 Python automation scripts
References: 3 knowledge base documents
Templates: 5 asset files
销售工程师技能
5阶段工作流程
阶段1:发现与研究
目标: 理解客户需求、技术环境和业务驱动因素。
检查清单:
- - [ ] 与利益相关者进行技术发现电话沟通
- [ ] 绘制客户当前架构和痛点地图
- [ ] 识别集成需求和约束条件
- [ ] 记录安全和合规要求
- [ ] 评估此机会的竞争格局
工具: 运行 rfpresponseanalyzer.py 以评分初始需求对齐度。
bash
python scripts/rfpresponseanalyzer.py assets/samplerfpdata.json --format json > phase1rfpresults.json
输出: 技术发现文档、需求地图、初始覆盖范围评估。
验证检查点: 在进入阶段2之前,覆盖率得分必须 >50% 且必备项差距 ≤3。使用以下命令检查:
bash
python scripts/rfpresponseanalyzer.py assets/samplerfpdata.json --format json | python -c import sys,json; r=json.load(sys.stdin); print(PROCEED if r[coveragescore]>50 and r[musthave_gaps]<=3 else REVIEW)
阶段2:解决方案设计
目标: 设计满足客户需求的解决方案架构。
检查清单:
- - [ ] 将产品能力映射到客户需求
- [ ] 设计集成架构
- [ ] 识别定制需求和开发工作量
- [ ] 构建竞争差异化策略
- [ ] 创建解决方案架构图
工具: 使用阶段1数据运行 competitivematrixbuilder.py,以识别差异化优势和薄弱环节。
bash
python scripts/competitivematrixbuilder.py competitivedata.json --format json > phase2competitive.json
python -c import json; d=json.load(open(phase2_competitive.json)); print(Differentiators:, d[differentiators]); print(Vulnerabilities:, d[vulnerabilities])
输出: 解决方案架构、竞争定位、技术差异化策略。
验证检查点: 在进入阶段3之前,确认每个客户优先级至少存在一个强差异化优势。如果未找到差异化优势,则升级至产品团队(参见集成点)。
阶段3:演示准备与交付
目标: 提供针对利益相关者优先级量身定制的、有说服力的技术演示。
检查清单:
- - [ ] 构建与客户用例匹配的演示环境
- [ ] 为每个利益相关者角色创建包含要点的演示脚本
- [ ] 准备异议处理回应
- [ ] 演练故障场景和恢复路径
- [ ] 收集反馈并调整方法
模板: 使用 assets/demoscripttemplate.md 进行结构化的演示准备。
输出: 定制化演示、针对利益相关者的要点、反馈收集。
验证检查点: 在交付前,演示脚本必须覆盖 phase1rfpresults.json 中标记的所有必备需求。使用以下命令交叉引用:
bash
python -c import json; rfp=json.load(open(phase1rfpresults.json)); [print(UNCOVERED:, r) for r in rfp[musthaverequirements] if r[coverage]==Gap]
阶段4:概念验证与评估
目标: 执行结构化的概念验证,以验证解决方案。
检查清单:
- - [ ] 定义概念验证范围、成功标准和时间表
- [ ] 分配资源并搭建环境
- [ ] 执行分阶段测试(核心、高级、边缘情况)
- [ ] 根据成功标准跟踪进度
- [ ] 生成评估记分卡
工具: 运行 poc_planner.py 以生成完整的概念验证计划。
bash
python scripts/pocplanner.py pocdata.json --format json > phase4pocplan.json
python -c import json; p=json.load(open(phase4pocplan.json)); print(Go/No-Go:, p[recommendation])
模板: 使用 assets/pocscorecardtemplate.md 进行评估跟踪。
输出: 概念验证计划、评估记分卡、执行/不执行建议。
验证检查点: 概念验证转化要求记分卡在所有评估维度(功能、性能、集成、可用性、支持)上的得分 >60%。如果得分 <60%,记录差距并循环回阶段2进行解决方案重新设计。
阶段5:提案与成交
目标: 提供支持商业成交的技术提案。
检查清单:
- - [ ] 整理概念验证结果和成功指标
- [ ] 创建包含实施计划的技术提案
- [ ] 用证据解决未解决的异议
- [ ] 支持定价和打包讨论
- [ ] 决策后进行赢/输分析
模板: 使用 assets/technicalproposaltemplate.md 作为提案文档。
输出: 技术提案、实施时间表、风险缓解计划。
Python自动化工具
1. RFP响应分析器
脚本: scripts/rfpresponseanalyzer.py
目的: 解析RFP/RFI需求、评分覆盖率、识别差距,并生成投标/不投标建议。
覆盖率类别: 完全(100%)、部分(50%)、计划中(25%)、差距(0%)。
优先级权重: 必备项3倍、应有项2倍、可有可无项1倍。
投标/不投标逻辑:
- - 投标: 覆盖率 >70% 且必备项差距 ≤3
- 有条件投标: 覆盖率50–70% 或必备项差距2–3
- 不投标: 覆盖率 <50% 或必备项差距 >3
用法:
bash
python scripts/rfpresponseanalyzer.py assets/samplerfpdata.json # 人类可读
python scripts/rfpresponseanalyzer.py assets/samplerfpdata.json --format json # JSON输出
python scripts/rfpresponseanalyzer.py --help
输入格式: 参见 assets/samplerfpdata.json 获取完整模式。
2. 竞争矩阵构建器
脚本: scripts/competitivematrixbuilder.py
目的: 生成功能比较矩阵、计算竞争得分、识别差异化优势和薄弱环节。
功能评分: 完全(3)、部分(2)、有限(1)、无(0)。
用法:
bash
python scripts/competitivematrixbuilder.py competitive_data.json # 人类可读
python scripts/competitivematrixbuilder.py competitive_data.json --format json # JSON输出
输出包括: 功能比较矩阵、加权竞争得分、差异化优势、薄弱环节和制胜主题。
3. 概念验证规划器
脚本: scripts/poc_planner.py
目的: 生成包含时间表、资源分配、成功标准和评估记分卡的结构化概念验证计划。
默认阶段分解:
- - 第1周: 设置 — 环境配置、数据迁移、配置
- 第2-3周: 核心测试 — 主要用例、集成测试
- 第4周: 高级测试 — 边缘情况、性能、安全
- 第5周: 评估 — 记分卡完成、利益相关者评审、执行/不执行
用法:
bash
python scripts/pocplanner.py pocdata.json # 人类可读
python scripts/pocplanner.py pocdata.json --format json # JSON输出
输出包括: 分阶段概念验证计划、资源分配、成功标准、评估记分卡、风险登记册和执行/不执行建议框架。
参考知识库
| 参考 | 描述 |
|---|
| references/rfp-response-guide.md | RFP/RFI响应最佳实践、合规矩阵、投标/不投标框架 |
| references/competitive-positioning-framework.md |
竞争分析方法论、战卡创建、异议处理 |
| references/poc-best-practices.md | 概念验证规划方法论、成功标准、评估框架 |
资产模板
| 模板 | 用途 |
|---|
| assets/technicalproposaltemplate.md | 包含执行摘要、解决方案架构、实施计划的技术提案 |
| assets/demoscripttemplate.md |
包含议程、要点、异议处理的演示脚本 |
| assets/poc
scorecardtemplate.md | 包含加权评分的概念验证评估记分卡 |
| assets/sample
rfpdata.json | 用于测试分析器的示例RFP数据 |
| assets/expected
output.json | rfpresponse_analyzer.py 的预期输出 |
集成点
- - 营销技能 - 利用来自 ../../marketing-skill/ 的竞争情报和消息框架
- 产品团队 - 协调来自 ../../product-team/