Customer Feedback Agent

The Customer Feedback Agent finds common customer requests, bugs, complaints, and praise from your AI Feedback sources. It reviews feedback from surveys, support tickets, and sales calls to spot key themes and changes in sentiment. By combining this feedback with user behavior data, it helps you understand user motivations and sends prioritized recommendations by email or Slack.

Capabilities

• Automated feedback analysis: Analyzes incoming qualitative feedback from connected AI Feedback sources and identifies key themes, sentiment shifts, and emerging issues without manual review.
• Qualitative-quantitative connection: Connects qualitative insights to behavioral data so you understand not just what users do, but why.
• Theme grouping: Groups feedback into categories---feature requests, bugs, complaints, loved features, and pain points---instead of requiring you to read through hundreds of responses.
• Prioritized recommendations: Generates actionable, customer-informed recommendations on improvements to ship, ranked by impact and frequency.
• Async reporting: Delivers scheduled reports through email or Slack so you stay informed without manually checking dashboards.

Prerequisites

The Customer Feedback Agent requires at least one connected AI Feedback source. Set up your feedback sources before you create the agent.

Create and configure the agent

1. Select Create New Agent on the AI Agents tab.

2. Select Customer Feedback Agent.

3. Agent Name: Enter a descriptive name for the agent.

4. Keywords: Optionally add one or more keywords to guide the agent toward specific types of feedback insights and comments. For example, add keywords like "onboarding", "pricing", or "mobile app" to focus the agent's analysis and report on those topics.

5. Define the customer insights you want the agent to identify. Describe the types of feedback, sources, and time ranges you want the agent to monitor. For example, "top bugs from Zendesk this month" or "feature requests from support tickets in the last week."

   Use a starter prompt to get started quickly:

   • Top Weekly Feedback Themes: Surfaces the most common feedback themes each week.
   • Feature-Specific Deep Dive: Focuses analysis on feedback about a specific feature.
   • Customer Love Stories: Highlights positive feedback and loved features.
   • Urgent Product Bugs: Prioritizes bug reports and critical issues.
   • Sentiment Score & Trend Analysis: Tracks sentiment shifts and trends over time.

6. Configure how the agent sends you notifications.

   • Email: Add subscribers by entering names or email addresses.
   • Slack: Select a Slack channel to receive reports.
   • Set the recurring report frequency, day, time, and time zone.

7. Select Create Agent and Run Agent.

How the agent runs

The Customer Feedback Agent connects to your AI Feedback sources and operates in two modes:

Interactive mode

Chat directly with the agent to explore specific questions about your customer feedback. Ask questions like "What are the top complaints this week?" or "Show me feature requests related to onboarding" and the agent responds in real time with evidence-backed findings.

Scheduled runs

On its configured schedule, the agent analyzes recent feedback across your connected sources and delivers a report that includes:

1. Theme summary: The most common feedback themes grouped into categories like feature requests, bugs, complaints, loved features, pain points, and key takeaways.
2. Sentiment shifts: Changes in customer sentiment compared to the previous reporting period.
3. Emerging issues: New or growing patterns that need attention.
4. Actionable recommendations: Prioritized suggestions on what to build, fix, or investigate next, based on feedback volume and customer impact.

Limitations

The Customer Feedback Agent analyzes feedback from connected AI Feedback sources only. The quality and completeness of insights depend on the volume and variety of feedback available in your sources. The agent identifies patterns and themes from qualitative data but doesn't modify your feedback sources or AI Feedback configuration. Large volumes of feedback may take longer to process, and the agent may recommend smaller time ranges for more focused analysis.