AI-Driven Lead Qualification and Sales Optimization System

The client faces low telemarketing efficiency due to absence of a lead scoring system, fragmented data funnels complicating lead tracking, underutilized lead information, high manual maintenance costs, and uncertainties in remote team collaboration, impacting sales success and scalability.

A mid-sized telecommunications company offering innovative business communication devices, seeking to enhance sales efficiency through AI-driven lead scoring and data analytics.

• Validate the hypothesis that AI can improve sales conversion rates by identifying high-quality leads more accurately.
• Develop a predictive model to assess lead quality and likelihood of conversion with over 91% confidence.
• Create an initial proof of concept to demonstrate AI feasibility in optimizing lead assignment and data utilization.
• Enable automation and better management of lead data to reduce manual effort and costs.
• Assess remote teamwork effectiveness during AI development and prepare for company-wide AI adoption.

• Exploratory data analysis module to assess data quality and prepare datasets for modeling.
• Data filtering mechanism to remove low-quality or irrelevant records.
• Predictive modeling component utilizing machine learning algorithms to evaluate lead quality.
• Interactive dashboard for telemarketers to view lead scores and prioritized lists.
• Integration layer for seamless data ingestion from multiple lead funnels.
• Automated model update and retraining capability for continuous improvement.

• Multiple lead management systems or data funnels for unified data access
• CRM or telemarketing platform to deliver lead prioritization insights

• System must process and analyze call and lead data with minimal latency to support real-time decision making.
• Secure handling and storage of sensitive client and lead information, complying with relevant data protection standards.
• Scalable architecture capable of handling increasing lead volumes and user loads.

The project aims to increase sales efficiency by enabling telemarketers to focus on high-probability leads, resulting in improved conversion rates. Based on prior validation, an expected success probability of over 91% can significantly reduce manual effort and costs, fostering scalable growth and more predictable sales processes.