Overview of Supportbench's AI Insights Feature

Marcel Gravelle

28-Jan-2025

Overview of Supportbench's AI Insights Feature in Closed Cases

Supportbench has introduced a powerful AI Insights feature, designed to provide detailed analysis and actionable data from closed cases. This feature leverages artificial intelligence to assess various metrics and deliver a comprehensive breakdown of customer interactions. The insights tab is conveniently located next to the "Discuss" tab within closed cases, enabling users to quickly access and analyze data.

Below is an in-depth explanation of the metrics covered by the AI Insights feature.

1. Customer Experience

Customer Satisfaction (CSAT)

This metric measures overall customer satisfaction based on the interaction. The AI analyzes communication and outcomes to determine whether the customer's expectations were met.

Positive Experience

This field highlights whether the overall experience with the agent and solution provided was positive.

Customer Satisfaction Reason

Provides insights into why the customer was or wasn't satisfied. This could include factors such as response time, solution effectiveness, or communication tone.

2. Customer Effort (CES)

This metric measures how easy it was for the customer to resolve their issue. The AI evaluates factors such as:

• Simplicity of the solution provided.

• Overall customer journey to resolution.

3. Quality Assurance (QA)

QA Score

A summarized score that evaluates the overall quality of the interaction, based on multiple subcategories.

QA Summary

Provides a brief overview of the case's quality evaluation, summarizing the interaction's strengths and areas for improvement.

4. Quality Assurance Breakdown

The QA Breakdown provides a granular view of specific criteria that contribute to the overall QA Score:

Grammar

• Assesses the grammatical accuracy of the agent's communication.

Tone

• Evaluates whether the tone of communication was appropriate, professional, and aligned with the company's standards.

Politeness

• Measures how polite and courteous the agent's responses were.

Product Knowledge

• Assesses whether the agent demonstrated sufficient knowledge of the product or service.

Empathy

• Determines if the agent showed empathy and understanding toward the customer's situation.

Explanation

• Evaluates how well the agent explained the solution or next steps to the customer.

Language

• Analyzes the clarity and appropriateness of the language used in communication.

Validation

• Checks whether the agent validated the customer's concerns or feedback during the interaction.

Clear Follow-Up

• Assesses the clarity and thoroughness of follow-up steps provided by the agent.

Solution Quality

• Evaluates the effectiveness and appropriateness of the solution offered.

How to Access AI Insights

1. Open any closed case in Supportbench.

2. Navigate to the AI Insights tab, located next to the "Discuss" tab.

3. Review the detailed metrics and breakdown provided for that case.

Benefits of Using AI Insights

• Enhanced Customer Understanding: Gain a deeper understanding of customer satisfaction and effort.

• Quality Improvement: Identify areas where agents excel or require training.

• Actionable Feedback: Use detailed QA metrics to make informed decisions about agent performance and training programs.

• Time-Saving: Automated insights save time compared to manual review processes.

By utilizing the AI Insights feature, Supportbench users can dramatically improve their customer service quality, identify trends, and ensure consistent customer satisfaction.