The first project, Enterpret, aggregates and analyzes customer feedback from a variety of sources like social media, sales calls and support tickets. It uses adaptive AI models to extract insights and consolidate feedback into a single taxonomy. It's geared for product development teams and customer experience staff who want to get feedback into their workflow and get a better idea of what's going on.
Another good option is CustomerIQ, which collects and analyzes customer feedback from many sources through integrations with tools like Slack, Hubspot and Zendesk. It's got AI-powered highlight extraction, filtering and search that lets teams find feature requests, pain points and preferences. It's good for marketing and product teams that want to make money by following data.
If you want to focus more on turning customer reviews into useful information, check Appinion. It's designed for easy feedback analysis, detailed reports and an integrated monitoring system. It uses AI for sentiment analysis and topic modeling that can help you optimize marketing campaigns and improve customer satisfaction. Appinion is good for individual developers, small teams and companies that want to improve their mobile app users' satisfaction.
Last, Anecdote offers real-time insights with its monitoring of feedback from many sources, including App Store reviews and social media. It uses its own Natural Language Processing Engine to spot bugs and sentiment trends, and it integrates with more than 65 feedback sources. It's good for reducing churn and improving customer satisfaction by quickly spotting bugs and gauging sentiment.