Question: Is there a tool that helps engineering teams prioritize tasks based on customer value and make data-driven decisions?

If you need a system to help engineering teams set priorities based on customer value and make data-driven decisions, Cardinal is a good choice. It combines customer feedback, CRM data and task management tickets to offer a data-driven approach to prioritization. Cardinal uses AI to identify feature requests and match them to actual projects, so teams can focus on the most important features based on business impact and customer needs. With integrations with Salesforce, HubSpot and Zendesk, it's got good support for tracking customer feedback and making decisions based on it.

Another good option is DevDynamics, an engineering management platform that offers a single interface to real-time metrics and AI insights to optimize engineering capacity and cut waste. It integrates with widely used tools like GitHub, Jira and GitLab, and offers features like DORA and SPACE benchmarking, alerts that trigger action, and cycle time measurements. DevDynamics can help teams improve engineering velocity, quality and team health, and is a good choice for data-driven decision making.

If you want a more lightweight way to track and manage projects, Snapshot Reviews offers a single interface for real-time data analysis and decision making. It includes features like daily standups, AI-driven data analysis and continuous feedback, and integrates with tools like Jira and GitHub. The platform can boost productivity by providing actionable feedback, so teams can make data-driven decisions more easily.

Last, Fibery is a product discovery and development platform that collects market signals and customer feedback to inform product development decisions. It integrates with tools like Jira, Trello and Airtable, offers AI-powered insights, customizable prioritization and roadmapping features. Fibery's fine-grained permissions and security features mean feedback is private and accessible, so teams can work more efficiently and make data-driven decisions.