Problem
Enterprise users hate logging time manually because it’s time-consuming, leading to low task efficiency and user drop-off.
Opportunity: To reimagine time tracking as a low-effort, high-accuracy experience by combining user-controlled automation with ML. By leveraging data from different systems, we could reduce manual input, improve data reliability, and rebuild trust —while meeting the needs of both individual users and enterprise administrators. This would help Tempo expand in the Enterprise space.
My Role: I led end-to-end design for Tempo’s automated time tracking feature. Interviews with enterprise users revealed that they were frustrated with spending 30+ mins a week manually logging time. This created an opportunity for a UX strategy that would reduce user pain through automated time tracking. I pushed to improve our ML algo to recognize common patterns, making time tracking faster and smarter at scale (among other things).
How might we use integrations for automated time tracking to reduce user friction, increase efficiency and increase trial-to-paid conversion?
🎯Objectives
🔮 Future vision
Nicole Merchant 