Freddy Copilot Reports

Freddy Copilot Reports are designed for organizations to maximize AI in customer support, offering insights into agent adoption and utilization of its features. With the introduction of Freddy Copilot capabilities, it's crucial to have a simple way to track usage and derive insights for each Freddy Copilot feature. These insights help measure and enhance agent productivity, evaluate AI effectiveness, and guide the expansion of AI applications.
Key benefits include:

Enhanced Visibility: Understand how agents use Freddy Copilot features and their frequency of use.
Productivity Measurement: Analyze AI tool adoption and usage to gauge agent performance.
Informed Decision-Making: Data-driven insights aid in expanding AI investments and directing agent training.
Optimization of Resources: Identify effective features for resource reallocation to boost impact.

This article has the following sections:

Understanding the Freddy Copilot Reports
Freddy Copilot Usage Report
1. Adoption Tab:
2. Drill-down Tab
Freddy Copilot Feature Drill Down Report

Understanding the Freddy Copilot Reports

The Freddy Copilot reports include two curated reports:

Freddy Copilot Usage Report - provides an understanding of the broad application of Copilot functionalities among agents
Freddy Copilot Feature Drill Down Report - provides data points to gauge the adoption and usefulness of Freddy Copilot features

Notes:Default data view covers the last 30 days; you can customize the date range and group by filters. 
You can export the report data to your email or download it as a PDF. 
Curated reports are not editable, but you can clone or create a custom report with preferred widgets/metrics.

Steps to access the reports:

Go to Support Analytics > Curated Reports.
Choose Freddy Copilot Usage Report or Freddy Copilot Feature Drill Down Report from the list of curated reports.

Freddy Copilot Usage Report

The Freddy Copilot Usage Report provides a comprehensive overview of agents' use of Copilot features, segmented into two tabs: Adoption and Drill-down.

Each tab has customizable filters for date range, group, and agent. These filters enhance the report's utility by allowing users to tailor the data presentation according to specific time periods, agent groups, or even individual agents.

If you have registered for a Freshdesk Omni (CSS) account or integrated your Freshchat account with Freshdesk, you will find the following 4 tabs related to conversations and tickets.

Adoption-conversation
Drill-down - conversation
Adoption - tickets
Drill-down - tickets

Adoption Tab:

The Adoption tab showcases how Copilot licenses and features are being used at the feature level, offering a clear view of adoption trends through the following widgets.

Freddy copilot usage
Agent adoption trend
Feature level analysis

This widget provides a summary of engagement with Copilot features, highlighting the frequency of use and the number of agents utilizing at least one feature.

This widget tracks the number of agents incorporating Freddy Copilot's features over time, indicating how feature adoption evolves.

This widget breaks down engagement by specific features, offering insights into which functionalities are most used and by how many agents. The widget displays the following columns:

Feature name - This includes Freddy Copilot features such as Summarize, Rephrase, Enhance tone, Expand text, Email Draft Generator, Conversational Knowledge Base, etc.
Number of times used - This shows the total usage count of all enabled Freddy Copilot features.
Number of agents using the feature - This indicates the total count of agents utilizing the Freddy Copilot features.

Drill-down Tab

The Drill-down tab offers an agent-level perspective on feature usage, essential for understanding individual engagement and identifying opportunities for further training or support.

Widgets in the Drill-down tab:

Feature usage trend
Agent level analysis

This widget visualizes the adoption and use patterns of Freddy Copilot features over selected timeframes, enabling leaders to spot shifts and make data-driven decisions on feature optimization.

This widget delves into how each agent interacts with different features, aiding in tailoring support and training initiatives to boost feature utilization effectively.

Freddy Copilot Feature Drill Down Report

The Freddy Copilot Feature Drill Down Report is a more granular examination of feature adoption and utility, segmented into 3 tabs.

Sentiment Analysis
Proactive Quality Coach Analysis
Post-resolution Quality Coach Analysis

Note: Freddy Copilot Feature Drill Down Report is specific to conversations and is not available as part of Freshdesk.

Sentiment Analysis Tab

The Sentiment Analysis tab offers insights into the trajectory of customer sentiment throughout interactions, underlining how effectively agents use Copilot to navigate and influence customer emotions.

Widgets in the Sentiment Analysis tab:

Conversation Volume
Sentiment change analysis
Initial user sentiment - trend
User sentiment on resolution - trend
User sentiment on resolution - agent analysis
User sentiment on resolution - group analysis

This widget shares information on the volume of resolved conversations within a selected period.

This widget examines how customer sentiment evolves during the conversation lifecycle.

This trend chart tracks the starting and ending sentiment of conversations, providing insight into emotional shifts facilitated by agent engagement.

User Sentiment On Resolution - Trend Widget

This trend illustrates user sentiment upon resolution of conversations.

User Sentiment on Resolution - Agent Analysis Widget

The analysis involves examining customer sentiments expressed at the end of interactions with agents. It evaluates how agents have addressed these sentiments and provides insights into individual agent performance and areas for improvement in service delivery.

It involves examining the sentiments expressed by customers at the end of their interactions at the group level and assessing how the group has impacted or dealt with these sentiments throughout the resolution process.

Proactive Quality Coach Tab

The Proactive Quality Coach Analysis tab provides an overview of user responses to prompted suggestions—accepted, rejected, or ignored—and analyzes the types of suggestions.

Widgets in the Proactive Quality Coach tab:

Volume Analysis
Suggestion type analysis
Agent level analysis

This widget displays the count of suggestions provided, accepted, rejected, and no action taken.

This widget analyzes suggestion categories such as grammar, abuse, and spell check. It shows the status of suggestions, including those that have been provided, accepted, rejected, and not taken action on.

This widget provides insights based on each agent’s use of the offered suggestions.

Post-resolution quality coach tab

The report allows users to see scores at both the group level (overall performance) and the agent level (individual performance). Administrators can also track the quality score trend to understand overall performance over time. They can also examine the quality score breakdown by agent, providing a comprehensive assessment of individual agent performance.

Widgets in the Post-resolution Quality Coach tab:

Average scores
Quality score trend
Agent level analysis
Feedback analysis

This widget displays the average quality scores for resolution based on 6 parameters, providing an overall quality score and individual scores for each parameter on a scale of 10.

The Quality Score Trends Widget monitors different customer service metrics over time so that organizations can assess performance trends, pinpoint areas for improvement, and maintain consistent quality standards in customer interactions. The service metrics include Overall Quality, Grammar of Response, Sentiment on Resolution, Timeliness of Response, Use of Abusive or Filler Words, Relevancy of Response, Greeting, and Closure.

Agent level analysis

This widget offers information on each agent’s quality score for each of the metrics measured: Overall Quality, Grammar of Response, Sentiment on Resolution, Timeliness of Response, Use of Abusive or Filler Words, Relevance of Response, Greeting, and Closure.

Feedback analysis

This widget offers an overview of the feedback provided by agents to assess the effectiveness of the quality coach’s suggestions. The widget displays metrics such as the number of scored conversations, conversations with feedback, conversations with positive feedback, and conversations with negative feedback.

By offering a detailed overview of feature adoption and effectiveness, Freddy Copilot reports empower users to make data-driven decisions that elevate operational efficiency, agent productivity, and, ultimately, customer satisfaction.

Modified on: Wed, 16 Oct, 2024 at 4:46 PM