Marzo AI personalizes your experience by continuously learning what matters to you—based on your role, your work patterns, your organizational relationships, and your own feedback.
How Personalization Works
1. Role & Org Data
Org chart and reporting lines: Marzo uses your title, manager, direct reports, and project teams to understand who and what is likely important for your work.
Team memberships and collaborators: Context from meetings, projects, and people you work with most frequently is prioritized for your briefs and alerts.
2. Conversation Analysis
Communication signals: Marzo analyzes the conversations you participate in (Slack, meetings, PRs, tickets, etc.), paying attention to your mentions, direct messages, and your engagement on specific topics or threads.
Recent activity: If you’re active in a discussion about a project, Jira ticket, or customer, Marzo knows to surface related updates, blockers, or risks in your brief or meeting prep.
3. Behavioral Feedback
Your actions teach Marzo: Every time you interact with a brief or alert—marking an item as “Done,” “Mute,” or “Follow”—Marzo AI learns what’s valuable to you and what’s noise.
Example: If you mute updates about a specific project or topic, Marzo deprioritizes similar items in the future.
Example: If you follow a project, Marzo keeps those updates front and center.
Thumbs up/down: Quick feedback on briefs or context items directly informs what Marzo should show more or less often.
4. Continuous Improvement
Natural language queries: When you use the Assistant to ask questions (“What’s blocking our next release?”), Marzo observes which answers you engage with, improving future relevance.
Personalization is always evolving: The more you use Marzo—and the more feedback you provide—the more precisely it adapts to your needs and working style.