📄 中文摘要
通过使用 AI 仪表板，销售人员可以在短短 8 分钟内完成对潜在客户的研究，而之前需要花费 45 分钟。该仪表板提供了公司概况（包括规模、收入、行业和最新新闻）、关键决策者的 LinkedIn 资料、技术栈分析、竞争对手情况、针对潜在痛点的三条谈话要点以及基于公司规模的建议定价。整个系统的技术栈包括 Python 进行协调，Claude API 进行分析和综合，Perplexity API 进行实时网络研究，以及 Flask 用于仪表板用户界面。
如何在 Python 中构建 AI 销售智能仪表板（附代码）
出处: How I Built an AI Sales Intelligence Dashboard in Python (With Code)
发布: 2026年3月25日
📄 English Summary
How I Built an AI Sales Intelligence Dashboard in Python (With Code)
An AI sales intelligence dashboard significantly reduces the time spent on prospect research from 45 minutes to just 8 minutes, while improving the quality of the information gathered. The dashboard provides a comprehensive overview of a company, including its size, revenue, industry, and recent news. It identifies key decision-makers with LinkedIn profiles, analyzes the technology stack, outlines the competitive landscape, and generates three tailored talking points addressing potential pain points. Additionally, it suggests pricing based on the company's size. The technology stack includes Python for orchestration, Claude API for analysis and synthesis, Perplexity API for real-time web research, and Flask for the dashboard UI.