Enabling Data-Driven Sales Targeting with Propensity Scoring

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Challenge

A leading cable operator sought to improve the effectiveness of its sales and marketing efforts for specialized network services. The organization faced challenges in identifying high-propensity prospects due to fragmented data sources and limited analytics capabilities. Existing tools and methods failed to provide actionable insights, resulting in suboptimal targeting and inefficiencies.

Solution

G2M Insights partnered with the client to develop a comprehensive propensity model, leveraging advanced machine learning techniques to predict the likelihood of prospects purchasing specialized network services. Key components of the solution included:

    1. Data Infrastructure and Preparation:
      • Designed and implemented a data architecture to consolidate and cleanse disparate data sources, including CRM opportunities, third-party data, and internal data.
      • Staged a robust data environment with automated pipelines for ongoing analytics.
    2. Predictive Model Development:
      • Built a state-of-the-art  propensity scoring model to analyze 70+ attributes and drivers, such as telco spend, multi-site attributes, firmographics, and geographic factors.
      • Scored full prospect universe, identifying the top locations with the highest propensity to buy.
      • Achieved high model accuracy outperforming the benchmark model.
    3. Integration and Scalability:
      • Developed a roadmap for integrating model outputs into enterprise systems, such as CRM and marketing lead identification platforms, to support ongoing targeting efforts.
      • Proposed enhancements, including a telecom spend model and up-sell/cross-sell propensity models, to maximize revenue opportunities.

Key Outcomes

This propensity modeling project delivered measurable business impact, including:

    • Improved Sales Targeting: Empowered sales teams to prioritize high-propensity prospects, increasing efficiency and effectiveness.
    • Actionable Market Insights: Enabled data-driven decision-making by identifying key drivers of purchase propensity.
    • Revenue Growth Opportunities: The top high-propensity prospects represented an estimated $200M+ in potential revenue capture.
    • Scalable Analytics Framework: Established a foundation for ongoing predictive analytics, supporting future use cases such as upselling and cross-selling.

Conclusion

This project highlighted the transformative power of predictive analytics in enhancing sales and marketing performance. By leveraging advanced data modeling techniques, the client gained a competitive edge in targeting prospects and unlocking revenue growth opportunities.

G2M Insights continues to partner with organizations to build and implement data-driven strategies that drive measurable business outcomes.