Lead Scoring Calculator Connector for AI agents.

It automatically ranks your leads so your reps know exactly who to call first, saving them from chasing cold contacts.

Yes, you can update the scoring weights and thresholds to fit any industry or region you target.

It identifies them automatically based on the scoring rules you set up in your configuration.

It looks at firmographics like company size and job titles, along with other behavioral data points.

Yes, the Connector provides an estimated percentage chance of a lead converting based on your specific scoring logic.

By focusing your budget and effort on Hot leads with high conversion probabilities, you spend less on low-quality leads.

The scoring model is comprehensive. It combines static Firmographic Signals (like company size and industry sector) retrieved via query_lead_profile_data with dynamic Behavioral Signals (such as page visits or emails opened). The final score weights these signals to give a true picture of intent.

The model is highly flexible. It fetches all necessary weights and thresholds using query_scoring_configuration. This allows administrators to adjust the importance of any attribute (e.g., boosting the value of a 'Director' title) without changing core code.

To calculate the final result, three pieces of information are required. First, you need raw lead data using query_lead_profile_data. Second, you must provide the scoring weights from query_scoring_configuration. These inputs feed into the core function, calculate_converted_score, which provides the total score and status.