Personagram: Bridging Personas and Product Design for Creative Ideation with Multimodal LLMs

TL;DR

Personagram is an interactive multimodal LLM-powered system that enhances product designers' ability to create, explore, and utilize detailed personas for more actionable and engaging design ideation processes.

Contribution

This work introduces Personagram, a novel multimodal LLM-based tool that bridges personas and product features, improving designer engagement and transparency in the design process.

Findings

Increased designer engagement with personas.

Higher perceived transparency and satisfaction.

Facilitated structured, multimodal ideation workflows.

Abstract

Product designers often begin their design process with handcrafted personas. While personas are intended to ground design decisions in consumer preferences, they often fall short in practice by remaining abstract, expensive to produce, and difficult to translate into actionable design features. As a result, personas risk serving as static reference points rather than tools that actively shape design outcomes. To address these challenges, we built Personagram, an interactive system powered by multimodal large language models (MLLMs) that helps designers explore detailed census-based personas, extract product features inferred from persona attributes, and recombine them for specific customer segments. In a study with 12 professional designers, we show that Personagram facilitates more actionable ideation workflows by structuring multimodal thinking from persona attributes to product design features, achieving higher engagement with personas, perceived transparency, and satisfaction compared to a chat-based baseline. We discuss implications of integrating AI-generated personas into product design workflows.