Canny: Organize feature requests and prioritize your roadmap.
Pricing Model
Free + from $79/mo
Visit Canny's website for the most up-to-date pricing tiers and features.
Canny is an AI-powered customer feedback management tool aimed at helping organizations collect, organize, and analyze feature requests. It centralizes feedback collection for deeper understanding of customer needs and effective product roadmap prioritization. Key features include feedback analysis and collection, request prioritization, roadmap creation, and progress update sharing.
Canny collects customer feedback through various sources. Users can set up a feedback portal for direct user interactions. It's also capable of auto capturing feedback from customer conversations with a feature called Autopilot. Furthermore, Canny can integrate customer support tools to enable capturing of feedback on behalf of users.
Yes, Canny allows direct user interaction on its feedback portal. Users can share their requests directly from the site, fostering more discussion and engagement around product features and requests.
Canny uses an automatic detection method to manage duplicate feedback. The system identifies and merges duplicates, consolidating similar ideas into single threads. This way, it quantifies the ideas and prevents the scattering of similar feedback across multiple entries.
Yes, Canny can connect customer data to specific product features. This capability provides significant insights into feature preferences and usage patterns, helping establish a strong connection between customer behavior and feature implementation.
In Canny, request prioritization is done using a customized formula that considers impact and effort weights. This allows requests to be scored and ranked accordingly, enabling product teams to focus on the features with the highest value and potential for impact.
Yes, Canny can integrate with popular project management tools. This integration aids in the creation of a concise product roadmap, leading to better planning and execution of feature developments.
Canny users can share progress updates through a public changelog. This changelog links to feature requests and automatically notifies users who interacted with those requests, keeping them informed about the progress and completion of requested features.
Yes, Canny supports automated feedback discovery through its AI-driven features. These intelligent features capture and deduplicate customer feedback from customer conversations, thereby reducing manual feedback tasks.
Yes, Canny aids in creating a roadmap for products. It integrates with popular project management tools to formulate a precise roadmap. Users can add top feature requests to the roadmap with a single click, ensuring a clear and updated representation of product development progress.
Canny helps make informed product decisions by transforming collected feedback into actionable insights. Busy feedback threads can be summarized for easy understanding and users can respond to feedback with clarifying questions for deeper insights. The system's AI features also assist in identifying top priority features guided by custom formulas considering factors like impact and effort.
Canny's AI-driven features include feedback discovery, smart replies, and summarization of long feedback threads. Feedback discovery is where it captures and deduplicates customer feedback from customer conversations. Smart replies let you respond to feedback with clarifying questions to uncover deeper insights. Summaries condense lengthy feedback threads to understand core use cases optimally.
In Canny, user segments are created to offer a closer look at feedback from specific groups. By creating user segments, product teams can focus on feedback from groups they deem most important. This could be based on user characteristics or behavior, and helps in refining product features and understanding customer needs better.
Canny summarizes lengthy feedback threads with AI-driven summarization. This tool presents a concise recap of extensive feedback threads, enabling users to quickly understand the core uses and needs expressed in the feedback.
In Canny, users who interacted with certain feature requests are notified automatically when progress updates are shared. This notification happens through a public changelog that links to feature requests and informs the contributors about the evolution of their requested features.
In Canny, you can set up a public changelog to share updates about your product's progress. You can publish detailed release notes linked to your feature requests, and those who interacted with or voted on these features are automatically notified. This feature helps keep your audience engaged and up-to-date with the product's progress.
Yes, Canny offers smart replies to customer feedback. These AI-driven responses can seek clarifying questions from users to uncover deeper insights into the feedback, promoting a deeper understanding of customer needs and expectations.
Canny helps users gain context from feedback by allowing them to connect customer data to specific features. Moreover, the system can clarify use cases up front and get more context from users. It promotes more in-depth insight into feedback, contributing significantly to product development decisions.
Yes, Canny does offer a way to transform feedback into actionable insights. The feedback collected is collated, organized, analyzed, and segmented if necessary. All this data is utilized to make key decisions about product development, roadmap creation, and essentially transform the constructive feedback from the user community into actionable tasks.
Canny helps prioritize your product roadmap based on customer feedback by collecting and organizing feedback in a centralized location. This information is then used to prioritize feature requests using a custom formula considering impact and effort. Consequently, decisions about the product roadmap are better informed and focused on what resonates most with the users.
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Check out Canny official site
Pricing
Free + from $79/mo
Category
Customer feedback analysis
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