
OVERVIEW
IMPACT
<aside> 🎉 27% increase in workflow adoption Increased daily usage compared to the previous AI chat-based workflow
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<aside> 🎉 Over half of the emails sent with minimal or no edits AI-generated emails became more context-rich and production-ready within reps’ existing workflow
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<aside> 🎉
Increased AE workflow efficiency
Reduced time taken on writing emails from 15-20min → 2-5 min
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DISCOVERY
To learn about how reps write follow-up emails today, I conducted research across multiple channels:

From user research, I identified not only what was breaking in the current flow but also the broader email tasks AEs wanted AI to support. After syncing with the PM, we prioritized fixing the most immediate drop-off issues first—improving the UI/UX and refining AI output—before exploring additional email types and workflows once we had stronger validation.

Other themes & problems discovered from research
Key research findings:
<aside> 💡 Reps write different emails across the sales cycle Follow-ups, re-engagements, replies, scheduling, and deal updates.
</aside>
<aside> 💡 Sending emails is high-stakes Reps wanted control over editing, formatting, and delivery in Gmail/Outlook.
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<aside> 💡 Generic AI chat wasn’t the right interaction model
Users could generate emails through AI chat, but most didn’t think to use it that way.
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