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AI-Driven Market Expansion Engine (Huawei)

PythonXGBoostGeospatial AnalysisCausal InferenceMarket Mix Modeling5G Networks

Business Impact

$40M revenue, +39% targeting efficiency

Scale

Multi-country 5G deployment

AI-Driven Market Expansion Engine (Huawei)

The Challenge

Huawei needed to identify optimal locations for 5G network deployment across Latin America. Traditional telecom planning methods were inefficient, leading to suboptimal site placement and pricing strategies that left $40M+ in potential revenue unrealized.

The Architecture

Built end-to-end Market Mix Model combining geospatial clustering, demographic analysis, and causal inference. Lifestyle Zones methodology: Geographic Data (OpenStreetMap) → Clustering Algorithm (K-Means + DBSCAN) → XGBoost Demand Prediction → Linear Programming for Site Optimization → Pricing Model (Elasticity-Based). Delivered insights via interactive PowerBI dashboards for C-level stakeholders.

System Architecture Diagram

graph TD
    A[Geographic Data<br/>OpenStreetMap] --> B[Clustering Algorithm<br/>K-Means + DBSCAN]
    B --> C[Lifestyle Zones<br/>Segmentation]
    C --> D[XGBoost<br/>Demand Prediction]
    D --> E[Linear Programming<br/>Site Optimization]
    E --> F[Pricing Model<br/>Elasticity-Based]
    F --> G[PowerBI<br/>C-Level Dashboard]

    H[Demographic<br/>Data] --> C
    I[Network<br/>Coverage Data] -.->|Constraints| E

    style A fill:#0066ff,stroke:#0052cc,stroke-width:2px,color:#fff
    style B fill:#4C9AFF,stroke:#0066ff,stroke-width:2px,color:#fff
    style C fill:#0066ff,stroke:#0052cc,stroke-width:2px,color:#fff
    style D fill:#4C9AFF,stroke:#0066ff,stroke-width:2px,color:#fff
    style E fill:#0066ff,stroke:#0052cc,stroke-width:2px,color:#fff
    style F fill:#4C9AFF,stroke:#0066ff,stroke-width:2px,color:#fff
    style G fill:#0066ff,stroke:#0052cc,stroke-width:2px,color:#fff
    style H fill:#666,stroke:#444,stroke-width:1px,color:#fff
    style I fill:#666,stroke:#444,stroke-width:1px,color:#fff

The Impact

Generated $40M in incremental revenue through optimized 5G deployment. Improved user targeting efficiency by 39% compared to legacy methods. Created reusable 'Lifestyle Zones' methodology adopted across multiple markets in Latin America.

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