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AI-Driven Lead Scoring System for Enhanced Telemarketing Efficiency in Telecom Sales
  1. case
  2. AI-Driven Lead Scoring System for Enhanced Telemarketing Efficiency in Telecom Sales

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AI-Driven Lead Scoring System for Enhanced Telemarketing Efficiency in Telecom Sales

neoteric.eu
Telecommunications

Challenges in Telemarketing Efficiency and Lead Management

The client faced low telemarketing efficiency due to lack of lead scoring, multiple disconnected data funnels, underutilized historical data, high manual maintenance costs, and dependency on manual lead management processes. These issues resulted in wasted resources on low-conversion leads and limited scalability.

About the Client

Provider of business phone products, including the HiHi2 innovative desk phone with tablet and business phone system integration

Objectives for AI Integration in Sales Process

  • Validate AI's ability to predict high-quality leads with >90% accuracy
  • Develop a predictive lead scoring model for telemarketing prioritization
  • Consolidate data from multiple sales funnels into a unified system
  • Reduce manual data management overhead by 70%
  • Demonstrate remote development team effectiveness for future collaboration

Core System Functionalities and Features

  • Automated lead scoring algorithm using historical conversion data
  • Multi-source data aggregation from CRM, call logs, and web analytics
  • Real-time dashboard for sales performance tracking
  • Integration with existing telephony and CRM systems
  • Exportable reports for lead prioritization lists

Technologies for Implementation

Google Cloud Functions
Python
NumPy
Pandas
scikit-learn

System Integrations

  • CRM platform (Salesforce/HubSpot)
  • Telephony API (Twilio)
  • Web analytics tools (Google Analytics)
  • Cloud storage (Google Cloud Storage)

Non-Functional Requirements

  • Scalable architecture for 100k+ daily leads
  • 99.9% system availability
  • Data encryption and GDPR compliance
  • Response time under 500ms for scoring requests

Expected Business Impact of AI Implementation

The AI solution is projected to increase sales conversion rates by focusing efforts on high-probability leads, reduce operational costs through automated data processing, and enable scalable AI adoption across the organization. The validated 91.36% success probability provides confidence for company-wide implementation.

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