
In this conversation, we explore how an AI-powered historical analysis agent can analyze past quote and contract data to improve sales decision-making.
🔹 What will you discover in this video?
✅ What is an AI-powered multi-agent system for sales managers?
🤖 How a team of specialized artificial intelligence can support sales management.
✅ Functions of the Historical Analysis Agent
🔍 Analysis of accepted, rejected, and pending quotes.
📊 Comparison and structuring of key data.
🏆 Identification of success patterns in sales proposals.
✅ Key Insights Extracted by AI
📌 Which proposals are most likely to be accepted?
🎯 Which customer profile responds best to certain services?
💰 What are the most effective prices by sector and region?
⚠️ What common elements do rejected proposals have?
✅ Complement to the Sales Team
🚀 AI analyzes thousands of proposals quickly.
📊 Provides insights based on data, not just intuition.
🔄 Adapts and improves over time.
✅ Real Use Cases
📈 Acceptance rate of specific proposals by sector and region.
🎯 Predicts the success of new offers before sending them.
🚨 Alerts on combinations of factors with a low probability of success.
🔍 Detects upselling and cross-selling opportunities.
✅ Commercial Contract Analysis
📄 Review of contracted services, terms, and economic margin.
🏦 Identify profitable clauses to improve negotiations.
📊 Creation of customer profiles to optimize growth opportunities.
✅ How It Works on a Technical Level
⚙️ Use of NLP to extract key information from PDFs and text.
🔗 Integration with CRM, ERP, and other business tools.
📊 Presentation of results in visual dashboards and automatic reports.
✅ Impact on Sales Management
🚀 Decisions based on data instead of intuition.
📊 Improvement in sales pipeline planning and management.
🤝 Greater alignment between sales, marketing, and management.
📌 Next video: How sales decisions impact profitability, with an AI-powered financial agent's analysis.
📩 Is your company ready to integrate AI into its sales strategy? Contact us to find out how.
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