Presty

Overview

  • The idea is to use generative AI to recommend styling options to the users and create a personal stylist application.
  • This was a group project and it used the design thinking framework throughout.
  • The idea was brainstormed and features were listed and prioritised.
  • Research methods such as interviews and competitive analysis were implemented.
  • The insights from the user research were sorted through affinity mapping, after which two personas for two user groups were created.
  • The PACT framework was used, and personas, scenarios and empathy maps were created to empathise with the user.
  • User journey maps, service blueprints and ScreenFlow diagrams were created to visualise and define the flow of events and tasks the user needs to undergo to get personalised styling advice.
  • Lo-Fi paper prototypes were created and tested.
  • Moodboards were made, and a high-fidelity prototype was created in Axure RP based on the selected moodboard.
My Role
UI/UX Designer
Type
Assessment Project
Time
1 Month
Technology
Axure RP
Skills Used

Table of Contents

Presty is a personal stylist application that makes use of modern generative AI technology to suggest all kinds of styling options for the user, including hair, facial hair, clothes, accessories, and more. The application also suggests new market products that suit the users needs. This project was done in a group (Peace Mfam~Onah, Devadhathan M D, Viral RajeshKumar Darji ) for User Experience Design and Service Design module for my MSc in User Experience Design. My role involved leading the team with ideation, research and prototyping.

The project followed the design thinking framework which involved the processes of empathising, planning, implementation, creation and evaluation of the project.

Ideation

The idea for the application was brainstormed by the team. Hiring a personal stylist could be an expensive deal, one of the key advantages of technology is that it helps make exclusive products and services available to a wider audience, a trend seen from the industrial revolution, making clothes available to masses at a cheaper price by mechanising the process. The team decided to use the same idea to make personal styling available to the masses by using generative AI.

The features of the envisioned application were listed out through brainstorming and were prioritised to set realistic goals.

Research

The research phase of this project included research methods such as interviews and competitive analysis.

The user research method used for this project was interviewing potential users in person. The goals of the research were listed out and questions were framed to extract answers that match the research goals. Five participants were interviewed thoroughly. The transcripts were taken and analysed to form an affinity diagram that helped identify the themes within the conversations.

Personas

Two kinds of users were identified in this small research, two personas were created to represent each group of users. Scenarios were created to add context to the situation of the users. The PACT (People, Activities, Context, and Technologies) method was used in the process.

Empathy maps were created for the personas to empathise with the potential users and better understand their frustrations and needs.

A user journey map was created to visualize the user’s touchpoints and emotions when moving from one point to another.

Screenflow diagrams for different tasks were created.

A service blueprint was created to illustrate the different stages of the business, the actions the user might take in each step, their emotions in each step, and the backstage actions the stakeholders will take to help the user progress through the blueprint.

Design

The insights from the research were considered, and the ideas for each screen were sketched with pen and paper. Several versions of the same screen were sketched and the best sketch was chosen and modified with elements from other screen sketches that stood out.

A paper prototype was created and tested. After the success of the paper prototype, moodboards were created, illustrations were sorted and a high-fidelity prototype was created in Axure RP. The high fidelity prototype is highly interactive and uses the dynamic panel feature of Axure RP to create something very close to a minimum viable product as Axure can deal with inputs, data and more.