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Hi-Tech Customer Elevates Talent Platform with Advanced Analytics

  • The Customer

    The Customer

    A global enterprise focused on enhancing its data analytics capabilities to improve customer insights, streamline product performance metrics, and maintain a competitive edge in pricing and service strategies.

  • The Challenge

    The Challenge

    The customer faced limitations in their analytical capabilities, primarily due to data silos that obstructed product performance insights and an outdated Customer Health Score (CHS) model that failed to provide actionable insights for retention and satisfaction. Service analytics lacked comprehensive metrics, making it difficult to assess service efficiency and effectiveness. Additionally, the customer encountered challenges in maintaining competitive pricing across various segments due to fragmented data sources and inconsistent metrics.

  • The Solution

    The Solution

    • Implementation of a centralized data science platform for integrated analytics, modeling, and observability.
    • Development of predictive models, including a redesigned Customer Health Score, service analytics metrics, and pricing tools.
    • Optimization of the platform with data orchestration, built-in observability, and proactive incident management.
    • Integration of key product metrics into a data lake for real-time insights.
  • Solution Components

    Solution Components

    Data Science Platform, Predictive Modeling, Data Lake, Data Orchestration, Observability Tools

  • The Results

    The Results

    • Enhanced decision-making with real-time visibility through the CHS metric.
    • Improved insights into product usage, adoption, and marketing pipeline, boosting conversion rates.
    • Increased operational efficiency with faster data refresh cycles and reduced downtime.
    • Revenue growth through optimized pricing strategy, achieving a higher average selling price.

The Customer

A global enterprise focused on enhancing its data analytics capabilities to improve customer insights, streamline product performance metrics, and maintain a competitive edge in pricing and service strategies.

The Challenge

The customer faced limitations in their analytical capabilities, primarily due to data silos that obstructed product performance insights and an outdated Customer Health Score (CHS) model that failed to provide actionable insights for retention and satisfaction. Service analytics lacked comprehensive metrics, making it difficult to assess service efficiency and effectiveness. Additionally, the customer encountered challenges in maintaining competitive pricing across various segments due to fragmented data sources and inconsistent metrics.

The Solution

  • Implementation of a centralized data science platform for integrated analytics, modeling, and observability.
  • Development of predictive models, including a redesigned Customer Health Score, service analytics metrics, and pricing tools.
  • Optimization of the platform with data orchestration, built-in observability, and proactive incident management.
  • Integration of key product metrics into a data lake for real-time insights.

Solution Components

Data Science Platform, Predictive Modeling, Data Lake, Data Orchestration, Observability Tools

The Results

  • Enhanced decision-making with real-time visibility through the CHS metric.
  • Improved insights into product usage, adoption, and marketing pipeline, boosting conversion rates.
  • Increased operational efficiency with faster data refresh cycles and reduced downtime.
  • Revenue growth through optimized pricing strategy, achieving a higher average selling price.

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