---
title: "Feedback Management AI agents"
section: "Agent store — Customer Service — processes"
canonical_url: "https://leverge.ai/agents/customer-service/feedback-management"
category: "Customer Service"
process: "Feedback Management"
publisher: "Ailoitte Technologies Private Limited"
---

# Feedback Management AI agents

6 production agents automating feedback management within customer service. Each one runs today and publishes its inputs, steps and outputs.

## Agents in this process

### Customer Feedback Analysis

URL: https://leverge.ai/agents/customer-service/feedback-management/csat-analysis

Read a batch of survey responses and surface the themes, the drivers of low scores, and what is worth acting on.

Steps: Reading the export → Finding the themes → Writing the brief.

Returns: Satisfaction; What the responses say; Themes; Words that recur; Worth acting on.

### Customer Testimonial Request

URL: https://leverge.ai/agents/customer-service/feedback-management/testimonial-request

Find the customers whose own words are worth asking to quote publicly, and draft each ask so it names what you want to quote and how consent works. Every draft is approved individually — nothing is sent.

Steps: Reading the candidates → Shortlisting who to ask → Drafting ask {{loop.index}} of {{loop.total}} → Summarizing the batch.

Returns: This batch; Batch summary; Drafted asks — approve each individually; Not asked.

### Feedback Intake Routing

URL: https://leverge.ai/agents/customer-service/feedback-management/feedback-intake-router

Take feedback arriving from every channel and route each item to the team that can actually act on it, separating a product request from a support failure from something that needs answering today.

Steps: Routing each item → Writing the handover.

Returns: This batch; Handover; Needs answering today; Routing; Could not be routed.

### NPS Detractor Follow-Up

URL: https://leverge.ai/agents/customer-service/feedback-management/nps-detractor-followup

Work out which detractors are worth a personal reply and which are better left alone, then draft each one from what they actually wrote. Every draft is approved individually — nothing is sent.

Steps: Reading the survey export → Deciding who is worth contacting → Drafting reply {{loop.index}} of {{loop.total}} → Summarizing the batch.

Returns: This batch; Batch summary; Drafted replies — approve each individually; Deliberately not contacted.

### Product Review Request Check

URL: https://leverge.ai/agents/customer-service/feedback-management/product-review-request

Check a planned review-request campaign before it goes out: whether the list was filtered by expected sentiment, whether anything is being offered in exchange, and whether the wording steers the score.

Steps: Reading the recipient list → Checking the campaign → Writing the verdict.

Returns: Campaign standing; Verdict; Problems; Against each test; Wording — as drafted and as it should read.

### Service Survey Designer

URL: https://leverge.ai/agents/customer-service/feedback-management/service-survey-builder

Build a survey that will actually tell you something — questions derived from what you need to decide, with the leading ones, the double-barrelled ones and the unanswerable ones stripped out.

Steps: Designing the survey → Writing the questionnaire.

Returns: Will this answer the question?; The survey; Each question and what it buys you; Questions left out on purpose; What this survey will not tell you.

---

Source: https://leverge.ai/agents/customer-service/feedback-management — Leverge