D⬤BO
Your Clothing Assistant App
#User Research
#UX Design
// This was a course project that aimed for learning the basic methodologies of research & design and how to choose the right design methods. This course project focused on discovering user pain points and developing solutions for better user experience.
// Through contextual inquiries, we found that users often have a hard time making decisions when shopping for clothings alone because they have nobody beside them to give them any suggestions on how their outfits match. Therefore, we designed a conceptual app that recommends matching items from the shop and users' wardrobe to assist users when they are shopping alone.
Contextual InquiryTo start off, we observed people's behaviors when they shop for clothes on their own. However, we wanted to understand more about what people actually feel and think when they shop alone. We held interviews with people who have experience and found that a lot of their behaviors, feelings, and decisions while shopping were strongly affected by their own personality and motivations of shopping.
Creating Personas
Thus, we organized four personas based on different personalities and motivations to outline what they consider the most when shopping for clothes.
User Journey Map
With four significant personas, we tried to map out each of their journey while shopping and marked down the special events that affect their mood. As a result, we found that there were mainly three parts of the shopping process with the most problems.
Derived Key Problems & Insights
Design Goal
Assist users by giving them a push on deciding whether to buy clothings that are in the "grey area."Meanwhile, we reminded ourselves to avoid directly giving answers on what to buy because we didn't want to lose the purpose of shopping.
Brainstorming & Card-Sorting
We applied the card-sorting method to organize the ideas we brainstormed based on our goal and key problems. As a result, we came up with five conceptual solutions.
Evaluating Ideas with Weighted Matrix
We analyzed the pros and cons of each idea and further applied them to the weighted matrix under certain criteria for evaluation. Eventually, the core app feature was to provide personalized clothing recommendations for users.
Defining Functions & User Flow
We first developed an overall user flow with the possible derived functions from our idea. Our main functions were focused on:
# 1 Recommending in-store clothings
# 2 Providing matching items in shop and from users' wardrobe
After that, we structured a sitemap with more specific functions and content:
We made mid-fidelity wireframes to test the user flow of the two core functions. We tested 3 tasks including:
1. Find recommended items from shop
2. Search for a specific in-shop item and find its matching items
3. Make a purchase decision and add the item to wardrobe
Findings from User Testing
