customer-feedback

A free, open source, self-hosted customer feedback tool 🦊

🔥 🔥 🔥 Open Source Canny, ProductBoard, UserJot Alternative. Track your customers feedback to build better products with LogChimp. ⭐️ Star to support our work!

Multi Class Text (Feedback) Classification using CNN, GRU Network and pre trained Word2Vec embedding, word embeddings on TensorFlow.

Using Machine Learning to Analyze & Visualize Consumer Behavior

A short hand-picked collection of resources to help SaaS founders get started with customer interviews.

A customer feedback demo application for collecting reviews for a product after a successful purchase.

Sample google appscripts

B2B Customer Feedback collection and analysis SaaS using AI/ML to generate, cluster and rank actionable tasks, helping you to grow your business.

🏠 The source code of bimbala.com.

Modern hotel review sentiment analysis with interactive GUI, AI explanations, and educational features. Python/ML/NLP project.

Instantly catch, manage, and respond to business reviews—never miss a review again. reviewready.ca

This repository contains code and tools for sentiment analysis of Persian customer reviews and feedback. Using Natural Language Processing (NLP) techniques, this project helps you transform Persian customer reviews into interpretable data and gain valuable insights to enhance the shopping experience.

This project analyzes customer feedback for skincare products by predicting sentiment using an unsupervised model. It includes a web application for real-time sentiment analysis, an ETL pipeline built with Azure Data Factory, Azure Databricks, and Azure Synapse Analytics, and a Power BI dashboard for visualizing review trends.

AI-powered sentiment analysis tool for evaluating processes and tracking feedback. Extract positive insights from reviews, customer feedback, and text data with real-time analysis and visualization.

Customer Feedback and Sentiment Analysis

Customer-Review-Feedback

Automated Restaurant Feedback Agent – SteamNoodles🍜 (AgentX Mini Project)

Developed a full-stack web application for catering services using the MERN stack (MongoDB, Express.js, React, Node.js). Features include menu management, order tracking, customer feedback, payment gateway and many more..

💬 It uses NLP techniques to classify reviews as positive, neutral or negative, providing valuable insights into customer feedback.

The cab booking project is used to book online from where you need there are three user admin and user and cab driver, The admin can check the cab details who all booked who all login etc, I have provide user-friendly domain to customer's happy it will helpful to all users used my cab booking online..