Score Cards & Confidence Levels Explained

Score Cards & Confidence Levels Explained

When the AI scores a property, it produces a score card with several components. Understanding each part helps you prioritize outreach effectively.

The Score (0-100)

The numeric score represents how well the property matches the selected deal profile. Higher is better. The AI considers all available data points and weighs them according to the profile's strategy.

Confidence Indicator

Each score includes a confidence level that tells you how reliable the score is:

• High confidence — The AI had all or nearly all data points for this property. The score accurately reflects the property's fit.
• Medium confidence — Some data points were missing (e.g., no square footage, unknown year built). The score is reasonable but may shift if more data becomes available.
• Low confidence — Significant data gaps. The score is directional at best. Use the written explanation to understand what data was missing.

The Written Explanation

Below the score, the AI provides a written explanation of its reasoning. This is often more valuable than the number alone. The explanation covers:

• Key positive factors — What made this property score well
• Key negative factors — What pulled the score down
• Missing data — What the AI could not evaluate due to data gaps
• Recommendation — A brief actionable suggestion

Key Factors List

The score card lists the specific factors that most influenced the score (both positive and negative). This lets you quickly see why a property ranked where it did without reading the full explanation.

Using Score Cards for Outreach

1. Sort by score to get your top leads.
2. Filter by high confidence to focus on reliable scores.
3. Read the written explanation for your top 10-20 leads.
4. Use the explanation to personalize your outreach — mention specific factors ("I noticed your property has been tax-delinquent for 2+ years...").