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

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

Sample google appscripts

🏠 The source code of bimbala.com.

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

Free and unlimited feedback widget for your websites through Google Analytics

Customer Feedback and Sentiment Analysis

Customer-Review-Feedback

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..

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..

An Analysis of the tech review and customer feedback on twitter, provided an insight into what the customers seek from Apple’s iPhone Series.

For feedback collection and external issue tracking

Mechanism for a search engine backed by inverted indexes (from using Lucene and Hadoop). Word embeddings and Snippet generation were used.

A Rust crate for calculating Net Promoter Score (NPS) from survey responses.

Sentimaster is a powerful sentiment analysis tool that leverages machine learning to provide deep insights into textual data, ideal for businesses and individuals

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

Emaily is a full-stack web application to collect customer feedback. It is for startups and product managers. It is written in JavaScript using Node.js, Express, Mongo DB, React, Redux, and Material UI.