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We take a systematic approach to organize user feedback effectively. We start by setting internal triggers using defined percentage thresholds and consider factors such as emoji usage, user account details, roles, response rates, and our feature request criteria, which is set at a minimum threshold of 80%. Utilizing our advanced sequence check and leveraging historical user filters (including product mentions, word analysis, and phrase breakdowns), we ensure that each piece of feedback aligns with your existing data. This meticulous process allows us to accurately tag feedback and save it in the appropriate collection, providing your team with valuable insights for well-informed decision-making.
Be where your users are and connect ChainFuse to your community channels, such as Discord, Discourse, Slack, and more.
Feedback is collected in real-time from all your connections. The more connections you have, the greater the intake of feedback.
Categorize incoming feedback as feature requests, bugs, general comments, and even off-topic remarks with the assistance of AI. Each type of feedback is filtered based on a percentage threshold and sorted automatically.
Prioritize and create a summary from the data you collect, making it easier for your team to collaborate and prioritize what comes next.
With all the data coming in, finding answers to your questions can be laborious and expensive. However, with ChainFuse and Clair, it doesn't have to be. Clair helps you converse with your data, enabling you to dive deeper into it.