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Cracking the Code: A Data-Driven Lead Scoring Framework

With Lead scoring you get to know if your leads are qualified. Also, which of those qualified leads should you actually pursue? But with so many models, how do you choose?

Let’s examine popular lead-scoring options in depth:

Best Practices for Implementation:

  • Establish clear definitions for what constitutes a marketing qualified lead. Align on criteria.

  • Audit existing data tracking - enhance ability to capture needed behavioral data for scoring.

  • Map common prospect actions to stages in your sales funnel. Develop associated point values.

  • Employ a blended model approach for optimal results. Consider demographic, behavioral, predictive and persona-based combinations.

  • Leverage predictive lead scoring powered by machine learning for fully customized models based on historical data and behaviors.

  • Continuously analyze lead score performance and correlations to refine model weights over time.

  • Make lead scoring part of your martech stack - integrate with CRM, marketing automation, and analytics tools.

Sophisticated lead scoring blends art and science to identify the prospects most likely to convert.

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