PosterMate: Audience-driven Collaborative Persona Agents for Poster Design

TL;DR

PosterMate is a collaborative poster design tool that uses AI-generated audience personas to gather diverse feedback and facilitate consensus, improving design relevance and capturing overlooked viewpoints.

Contribution

It introduces a novel AI-driven system that creates audience personas from marketing documents to enhance collaborative poster design and feedback synthesis.

Findings

Effective in capturing overlooked viewpoints

Facilitates consensus through discussion among personas

Proven to be an efficient prototyping tool

Abstract

Poster designing can benefit from synchronous feedback from target audiences. However, gathering audiences with diverse perspectives and reconciling them on design edits can be challenging. Recent generative AI models present opportunities to simulate human-like interactions, but it is unclear how they may be used for feedback processes in design. We introduce PosterMate, a poster design assistant that facilitates collaboration by creating audience-driven persona agents constructed from marketing documents. PosterMate gathers feedback from each persona agent regarding poster components, and stimulates discussion with the help of a moderator to reach a conclusion. These agreed-upon edits can then be directly integrated into the poster design. Through our user study (N=12), we identified the potential of PosterMate to capture overlooked viewpoints, while serving as an effective prototyping tool. Additionally, our controlled online evaluation (N=100) revealed that the feedback from an individual persona agent is appropriate given its persona identity, and the discussion effectively synthesizes the different persona agents' perspectives.