How call scoring works in Empower

Empower evaluates customer calls using a combination of AI-generated insights and statistical analysis. The goal is to provide an accurate, actionable score for every call to support coaching, quality assurance, and performance tracking.

🧩 Core Components

Each call is evaluated across six components, each scored on a 0 to 5 scale and assigned a weight (1 to 5):

1. Objection Handling & Product Knowledge (AI-based)

This component is derived by averaging two independent AI-generated scores:

• Objection Handling:

  • The LLM identifies client objections and the agent’s response/resolution steps.

  • Based on how well objections are handled, a score from 0 to 5 is generated.

• Product Knowledge:

  • The LLM checks if the agent’s statements and answers align with a predefined product knowledge base.

  • It scores accuracy, completeness, and clarity.

🧠 While users only see the final score, a detailed internal analysis is performed to increase reliability using a "reasoning before answering" methodology.

2. Call Mood (Statistical)

• Raw mood is a number between -1 (negative) and +1 (positive).
   

It is normalized to a 0 to 5 scale using:

Mood Score = ((Mood + 1) / 2) * 5

3. Topics / "Moments" (Statistical)

• Based on a list of "must-have" moments provided in the scorecard.

Score is calculated as:

• Moments Score = (Number of Detected Moments / Total Expected Moments) * 5

4. Script Adherence (AI-based)

The LLM:

1. Groups semantically similar speech turns.

2. Matches them to the steps in the predefined call script.

3. Scores based on how many steps were covered and how well.

✅ This AI-driven semantic mapping ensures flexibility beyond keyword matching.

5 & 6. Call Duration & Speech Rate (Statistical)

Both are scored based on whether they fall within admin-defined acceptable ranges.

• If in range → Score = 5

If outside → Penalized proportionally:

• Score = 5 - (deviation from range midpoint / total range)

Example:

• Expected speech rate: 100–200 WPM

• Actual speech rate: 50 → Score = 2.5 (halfway below)

• Actual speech rate: 250 → Score = 2.5 (halfway above)

🧮 Final Score Computation

Each component contributes to the final call score based on its assigned weight:

Final Score = 

• (Score₁ × Weight₁ + Score₂ × Weight₂ + ... + Score₆ × Weight₆) / 

• (Weight₁ + Weight₂ + ... + Weight₆)

📌 Each component has a max score of 5, but the influence on the final score depends on its weight (1–5).

✅ Summary

This scoring system ensures a fair and balanced assessment combining explainable data-driven insights with deeper AI analysis.