PersonaMail: Learning and Adapting Personal Communication Preferences for Context-Aware Email Writing

TL;DR

PersonaMail is a system that enhances email writing by capturing nuanced communication preferences, enabling more effective and context-aware messages through structured controls and adaptive reuse of tone strategies.

Contribution

It introduces a novel system that learns and adapts personal communication styles for email, addressing limitations of existing LLM-assisted writing tools.

Findings

Improved efficiency over standard LLM interfaces.

Higher user satisfaction with PersonaMail.

Effective reuse of tone strategies across messages.

Abstract

LLM-assisted writing has seen rapid adoption in interpersonal communication, yet current systems often fail to capture the subtle tones essential for effectiveness. Email writing exemplifies this challenge: effective messages require careful alignment with intent, relationship, and context beyond mere fluency. Through formative studies, we identified three key challenges: articulating nuanced communicative intent, making modifications at multiple levels of granularity, and reusing effective tone strategies across messages. We developed PersonaMail, a system that addresses these gaps through structured communication factor exploration, granular editing controls, and adaptive reuse of successful strategies. Our evaluation compared PersonaMail against standard LLM interfaces, and showed improved efficiency in both immediate and repeated use, alongside higher user satisfaction. We contribute design implications for AI-assisted communication systems that prioritize interpersonal nuance over generic text generation.