The RICE Scoring Framework - Overview, Example, and Explanation

📈 The RICE scoring model, introduced by intercom, has been widely adopted and used by product managers and product owners around the world for prioritizing feature releases or projects. 💡 Implementing a new onboarding flow can potentially reach the same number of new users per month as the average number of new users, potentially improving user engagement and retention. 💡 The impact of a feature in a product is determined by the benefit it provides to users, highlighting the importance of considering user needs and satisfaction. 💰 The impact score in the RICE scoring framework measures how much a feature will increase conversion rates, retain users, and improve ease of use, potentially impacting a company's metrics significantly. 💯 Always question the extent to which your data can support your estimates. 🎯 The RICE scoring framework assigns confidence scores to features based on research, live tests, and effort estimates, allowing room for potential errors. ⏰ The effort metric in the RICE scoring framework measures the amount of work required from a team to build a feature or finish a project, and it is determined by asking how much time will be required from all team members. 💡 The RICE scoring framework can help prioritize initiatives and projects based on their impact, confidence, and effort, providing a data-driven approach to decision-making.