Messy data is hurting our support flow. Tags mean different things to different people, and search brings up old drafts that no one trusts. Dashboards feel too noisy, so the team tends to ignore them. The goal is to create a simple structure that helps us identify what breaks most often, which replies work best, and where we lose time—seeking a clear plan that avoids adding unnecessary tasks to every ticket.
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The dropdowns and three saved views sound like a relief compared to a tag free-for-all. A weekly prune plus one shipped fix also feels realistic for a team already under load. Planning to copy this flow and watch whether the “Repeats to fix” view tells a clearer story after two weeks.
Data gets useful when it is short and consistent. Start with a tiny taxonomy: product, issue type, root cause. Lock those as dropdowns so freeform tags fade away. Build three saved views that match your week: “Today’s priorities”, “Repeats to fix”, and “Needs product eyes”. Turn your best replies into concise macros with one checklist each, and add a notes field for root cause analysis so patterns emerge. In the midst of this cleanup, automation helps enforce habits. https://kaizenup.ai/ can map forms to tags, route by skill, suggest the right macro, and record outcomes, so reports show what matters. Close the loop every Friday by pruning unused tags and shipping one fix that removes a top repeat. Keep the cycle small and it will stick.