138 lines
4.1 KiB
Python
138 lines
4.1 KiB
Python
import pandas as pd
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from typing import List
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from openpyxl import Workbook
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from AgentProxy import AgentProxy
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api_key = 'c6bbe7f48063a2c1'
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api_secret = '5f8e7d3a97465cc099bf19bd1b70c266'
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assistant_id = "66bb09a84673b57506fe7bbd"
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agent = AgentProxy(assistant_id, api_key, api_secret)
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# Stage: Evaluation
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# 客户接触与需求识别: 188.89%
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# 项目支持与优化: 91.11%
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# 产品演示与方案提供: 80.00%
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# 市场分析与策略调整: 80.00%
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# Stage: Qualification
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# 客户接触与需求识别: 154.24%
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# 项目支持与优化: 144.07%
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# 商务谈判与合同准备: 113.56%
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# 内部协调与支持: 83.05%
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# Stage: Bidding+Negotiation
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# 商务谈判与合同准备: 162.86%
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# 客户接触与需求识别: 130.00%
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# 项目支持与优化: 125.71%
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# 内部协调与支持: 111.43%
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# Stage: Closed Won
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# 商务谈判与合同准备: 130.77%
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# 内部协调与支持: 123.08%
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# 项目支持与优化: 123.08%
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# 合同审查与订单处理: 115.38%
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most_frequent_actions = {
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"Evaluation": [
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"客户接触与需求识别",
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"项目支持与优化",
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"产品演示与方案提供",
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"市场分析与策略调整"
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],
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"Qualification": [
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"客户接触与需求识别",
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"项目支持与优化",
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"商务谈判与合同准备",
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"内部协调与支持"
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],
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"Bidding+Negotiation": [
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"商务谈判与合同准备",
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"客户接触与需求识别",
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"项目支持与优化",
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"内部协调与支持"
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],
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"Closed Won": [
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"商务谈判与合同准备",
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"内部协调与支持",
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"项目支持与优化",
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"合同审查与订单处理"
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]
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}
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# Stage: Evaluation
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# 完成技术评估与测试: 4.44%
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# 完成市场调研与竞争分析: 4.44%
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# 完成需求确认与收集: 2.22%
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# 完成项目立项与采购流程: 2.22%
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# Stage: Qualification
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# 完成需求确认与收集: 1.69%
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# 完成技术评估与测试: 1.69%
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# 完成商务谈判与合同准备: 1.69%
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# 完成内部审批与预算确认: 1.69%
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# Stage: Bidding+Negotiation
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# 完成技术评估与测试: 2.86%
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# 完成市场调研与竞争分析: 2.86%
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# 完成需求确认与收集: 1.43%
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# 完成项目立项与采购流程: 1.43%
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# Stage: Closed Won
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# 完成商务谈判与合同准备: 3.85%
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# 完成关系建立与维护: 3.85%
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# 完成续约与增购谈判: 3.85%
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# 完成需求确认与收集: 0.00%
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top_action_results = {
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"Evaluation": [
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"完成技术评估与测试",
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"完成市场调研与竞争分析",
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"完成需求确认与收集",
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"完成项目立项与采购流程"
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],
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"Qualification": [
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"完成需求确认与收集",
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"完成技术评估与测试",
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"完成商务谈判与合同准备",
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"完成内部审批与预算确认"
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],
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"Bidding+Negotiation": [
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"完成需求确认与收集",
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"完成技术评估与测试",
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"完成项目立项与采购流程",
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"完成市场调研与竞争分析"
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],
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"Closed Won": [
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"完成商务谈判与合同准备",
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"完成关系建立与维护",
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"完成续约与增购谈判",
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"完成需求确认与收集"
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],
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}
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stages = ["Evaluation", "Qualification", "Bidding+Negotiation", "Closed Won"]
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for stage in stages:
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print(f"Stage: {stage}")
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prompt = f"""
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任务：
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你作为一个资深的销售领域专家，下面的输入数据给出了销售阶段，该销售阶段最频繁的销售行动，该销售阶段最top的行动结果，
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分析：
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1. 销售的行动和结果是否匹配和相关
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2. 销售的行动和结果是否正相关，是否存在gap
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3. 销售的行动和结果是否和当前的销售阶段相匹配
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输入：
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销售阶段：{stage}
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最频繁的销售行动：{most_frequent_actions[stage]}
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最top的行动结果：{top_action_results[stage]}
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输出：
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按照上述分析要点给出的分析结果和分析报告
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"""
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print(agent.send_message(prompt))
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