Skill

Design and Optimize Customer Feedback Systems

Name: Design and Optimize Customer Feedback Systems
Availability: OnlineOnly
Author: VibeBaza

Expert agent for designing multi-channel customer feedback systems with NPS/CSAT/CES surveys, sentiment analysis, automated routing, and actionable insights

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Works with githubsalesforce

VibeBaza

Maintainer?

Spark score

out of 100

Updated 6 months ago

Version 1.0.0

Models

claude

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Why it matters

Automate the collection, analysis, and utilization of customer feedback to drive product improvements and enhance customer satisfaction.

Outcomes

What it gets done

Design multi-channel feedback collection strategies (in-app, email, social media, etc.).

Implement sentiment analysis and theme extraction for qualitative feedback.

Generate actionable insights and reports for product and support teams.

Automate feedback routing and response mechanisms.

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/vb-customer-feedback-system | bash

Capabilities

What this skill does

Extract

Pulls structured data fields from unstructured text.

Classify

Labels or categorizes text, files, or data points.

Summarize

Condenses long documents or threads into key takeaways.

Write copy

Drafts marketing, email, or product copy on demand.

Notify

Sends alerts or messages via email, Slack, or other channels.

Overview

Customer Feedback System Designer Agent

What it does

This agent provides expertise in designing and implementing customer feedback systems across multiple channels (in-app, email, support tickets, social media, review platforms). It covers survey design with NPS, CSAT, and CES metrics, timing optimization for maximum response rates, sentiment analysis with theme extraction, and automated routing logic. Includes data schemas, KPI dashboard structures, and integration patterns with CRM and product management tools.

How it connects

Use this when building or optimizing a customer feedback program, designing surveys that balance completion rates with data quality, implementing automated sentiment analysis and response routing, or integrating feedback data with CRM systems. Ideal for product managers, customer success teams, and engineers architecting feedback infrastructure that turns customer input into actionable product decisions.

Discussion