Methodologies:

• To conduct research: Interview, Questionnaire

• To analyze data: Affinity Diagram, Empathy Map, Persona

• To design: Scenario, Sketching, Prototyping

• To evaluate design: Lean Validation, Usability Testing

Overview

Liam’s Story

From Liam’s experience of buying a used table, we initially came up with the idea of designing a neighborhood-based online platform for residents living within a small geographical range.

User Research & Analysis

Participant Description

In this project, we recruited such participants for user interviews, lean validation, and usability testing. We believe such users:

• are more likely to search for used items because of their tight budgets as students

• are more likely to seek or provide assistance within neighborhood due to their limited social relationships

• are more familiar with mobile applications as the younger generation

Secondary Research Findings

In order to gather information about the industry of online classified advertising services, we studied some of our competitors, including Kijiji, Bunz, Facebook Marketplace, and WeChat Groups.

It is interesting that the needs of users like Liam are not satisfied by any of them. Some apps do not have a distance filter within 1 km, while those that do are not accurate enough. Although some platforms have ways to prevent scams, such as ratings and reviews as well as email verification, there is space for improvement and it is possible to develop better ways to prevent scams. They also do not have a system to secure refunds for users.

Primary Research Findings

We hope to understand whether other people also share Liam’s experience in seeking and providing assistance within their neighborhood and in online communities. Through their journey, we aim to understand what they think, feel, say, and do. We also want to know their needs, desires, and obstacles. Furthermore, we are interested in the users’ characteristics and what kinds of assistance they have sought and provided. For our primary research, we interviewed 8 people and collected 23 effective answers to our questionnaire.

By analyzing the primary research results, we found three insights:

• First, users are likely to buy stuff and receive services from people nearby because it’s convenient.

• Second, there are a lot of scams on online classified advertising platforms. Scams make people like Liam worried about being swindled out of their money and about their personal safety when meeting sellers.

• Third, users like Liam also mentioned that they can only request a refund through private communication means, but the platforms don’t care about the result, and it’s frustrating sometimes because some sellers are just not trustworthy.

Persona

Based on the user research, we created our persona, Liam, as mentioned in the video.

Requirements Analysis

Hills Statements & Tasks

We then figured out 3 hills statements, which come from Liam’s problems. After that, we selected 3 tasks to be prototyped as part of our MVP.

PROTOTYPEs & Evaluations

Low-Fidelity Paper Sketches

When Liam opens the Nearby app for the first time, he will see on-boarding screens of our features that make the Nearby app unique from other existing classified advertising apps.

In this task, Liam needs to search for a seller that is located as close as possible to him.

In the next task, Liam wants to schedule a meeting with a reliable seller.

Since Liam and the seller fails to reach an agreement through private communication means. As for the last task, he is able to request and obtain a refund as long as his reason is reasonable.

Lean Validation

After we finished our low-fidelity prototypes, we conducted lean validation so as to receive feedback and comments from representative users like Liam.

We illustrated the main findings and updates with the comparison of before and after design as shown below.

Clickable Medium-Fidelity Prototype Demo

Based on our low-fidelity paper sketches as well as what we learned from our lean validation, we put together a clickable medium-fidelity prototype for our MVP. Here is the demo of Liam’s three tasks, which integrated design features of：

• Small geographical range

• Identity verification

• Escrow third-party transaction

Usability Testing

In order to further validate whether our design features meet Liam’s needs (Do not waste time and money getting to seller / Make a deal with a reliable seller / Obtain a refund through the app) and improve the usability of our medium-fidelity prototype, we conducted usability testing of our MVP with four representative users.

We chose observation and interview as our usability testing methods, since:

• It is very difficult for people to describe accurately how they achieve a task, observation is used to watch users directly to determine how well the developing prototype supports the tasks.

• The goal of the evaluation is to get feedback about our design features, we conducted interviews to let the users tell us about their experiences and provide information that could not be observed.

Using the DECIDE framework, We drafted out the protocol our team will follow to conduct the usability testing.

After we collected data relevant to usability of the prototypes from the participants, we interpreted their feedbacks and comments as the main findings as shown below.

We also analyzed participants’ point of views related to our three design features from the summative evaluation and presented our main conclusions as shown below.

NEXT STEPS

The findings and conclusions we gathered from our usability testing gave us directions for our next steps.

• In order to improve the usability of our prototypes, we will revise the app for the minor and moderate issues that were found from the usability testing.

• As for design features: