Chattermill

Chattermill

Chattermill is a customer experience analytics platform that helps companies understand sentiment from customer feedback to improve products, services and experiences. It uses natural language processing and machine learning to analyze various data like surveys, reviews and socia
Chattermill image
sentiment-analysis natural-language-processing machine-learning customer-feedback

Chattermill: Customer Experience Analytics Platform

Discover the power of customer feedback analysis with Chattermill, a cutting-edge platform that leverages NLP and machine learning to provide actionable insights from surveys, reviews, and social media data.

What is Chattermill?

Chattermill is a customer experience analytics software that allows businesses to centralize, analyze and take action on customer feedback data from various sources to improve products, services and customer experiences.

It uses natural language processing and machine learning algorithms to analyze unstructured data like customer surveys, online reviews, feedback forms and social media conversations at scale. Sentiment, topics, categories and other insights are automatically detected.

Key features include:
- Data centralization from 30+ sources including SurveyMonkey, Google Reviews, Facebook, Salesforce, Zendesk etc.
- Sentiment analysis, topic extraction and automatic categorization of feedback data.
- Comparison of feedback data across locations, products, time periods etc.
- Prioritization based on impact so you can focus on the most critical feedback.
- Collaboration tools to discuss insights and create tasks.
- Benchmarks against competitors.
- Executive reporting and presentation-ready reports.

It's easy to get started with simple data integrations and an intuitive interface. Chattermill is used by consumer brands like Airbnb, ClassPass, HelloFresh etc. to help them listen better to the voice of their customers.

Chattermill Features

Features

  1. Natural language processing to analyze unstructured text data
  2. Sentiment analysis and text classification
  3. Integrations with data sources like surveys, reviews, social media
  4. Dashboards and visualizations for insights
  5. Alerts based on sentiment changes or review volume shifts
  6. Customer journey mapping
  7. Root cause analysis to understand drivers of sentiment
  8. AI-powered product recommendations

Pricing

  • Subscription-Based

Pros

Powerful NLP and ML for accurate analysis

Unified view of all customer feedback data

Easy to use dashboards and visualizations

Helps prioritize actions based on insights

Continuously monitors customer sentiment changes

Integrates seamlessly with existing tools and workflows

Cons

Can require large data volumes for accurate insights

Setup and training may require time investment

May need consulting help to maximize value

Not as customizable as building in-house NLP platform


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