Understanding the Problem

Discovery Insights

As a college alumna, I understood the struggle of finding the most optimal study spot off-campus and away from the comfort of home while juggling the actual studying aspect and working part-time jobs. I wanted to validate these problems with current students and fellow college alumni, so I took the initiative to sit down with several of them who also struggled with this problem.

After listening to these students and alumni, I discovered these top frustrations:

1. Wasting valuable time. Students would rather study outside of campus or their house to be more productive, but feel demotivated when gas and time is wasted to search for this ideal study space.

2. Lack of relevant information. Search engines are oversaturated with irrelevant reviews and information that is not relevant to students’ needs. Often the questions they ask go unanswered (i.e. does this place have enough outlets; how crowded does it get; is there a lot of seating?). This makes the search tedious and inconvenient.

3. Not enough trustworthy recommendations. The majority of students relied on word-of-mouth recommendations over search engine results because reviews on the business listing felt shallow and lacked depth.

Solution

Create an MVP that provides users with access to in-depth information on public space accessibility, a filterable search engine customizable to their needs, and a detailed peer review section to help users determine workspace suitability.

The Process

Define & Understand

My first step was to define the user/goals, the problem space, and the value proposition of this MVP.

The User/Goals

My user is a college student who wants to quickly find the most suitable place to study.

Students are often busy between schoolwork and studying; for some, the added internships or work, so they often don’t have the time to invest in playing rush and roulette for suitable workspaces in lieu of their campus and their home. Further examination of users and their goals was done through user interviews.

The Problem Space

Most search engines lack detailed descriptions of specific amenities that students prioritize when studying (e.g. outlets and WiFi strength). This lack of information often hinders students from finding a workspace that suits their needs.

This problem space was initially defined by personal experience and conversations in passing amongst current and former students. However, it was solidified after further research was gathered.

Value Proposition

In order to address the problem space and meet user goals, I created three key features:

1. Thoroughly detailed listings

2. Customizable search engine filter

3. Detailed peer reviews

I came to this conclusion by using Peter Thomson’s value proposition canvas. Since this particular project is an MVP created from the ground up, this VP canvas helped me to examine the human experience of my users and to think through the end-customer experience.

Overall, I kept two questions in the back of my mind to help frame the parameters of this MVP that best addresses the user’s goal.

1. How do you make the search for the most optimal study space easier for students?

2. What are the greatest needs for students when searching for a study space?

User Interviews

In order to better understand my user and their goals, I conducted user interviews. These interviews helped me to understand their challenges and priorities when meeting their goals. I interviewed a total of five people ranging from undergrad students to grad students.

You can click here to view the specific questions I asked in my interview.

Competitive Analysis

After my user interviews, I gathered information on competitors they frequently used. I used the SWOT analysis method to find opportunities my MVP could provide that they did not. I found that while the competitors provided information of each business listing (e.g. hours, directions, reviews), they lacked in providing specific information that my users were looking for (e.g. crowd control, outlet provision, etc.). In addition, I found that reviews were often too broad. This vague amount of information and reviews make it difficult for users to determine whether that business is suitable for their needs.

Persona

After conducting my user interviews and gaining better insight into their needs, I created a persona to give me context when designing with the user and their goals in mind.

In addition to a persona, I created the user’s task flow to identify the high-level steps they would take to get to their specific goal. This framed the overall experience I would provide in the MVP.

Wireframing

Low-Fidelity Wireframe

After gaining knowledge and insight on the user goals, I drafted low-fidelity wireframes. Creating low-fidelity wireframes allowed for quick sketches to get the main idea of the MVP across without wasting valuable time creating high-fidelity wireframes that would be subject to change after evaluation.

Mid-Fidelity Wireframe

After reviewing the low-fidelity wireframe with my tertiary stakeholder, I created a mid-fidelity wireframe on Figma and created a prototype for usability testing. I conducted a usability test with five college students.

High-Fidelity Wireframe

After conducting a usability test on the mid-fidelity wireframe, I gathered more information on what were successful and problematic areas for users. In doing so, I revisited and redesigned the overall experience to better suit the user.

Test & Evaluate

I conducted usability testing after creating the mid-fidelity and high-fidelity wireframes. Each stage of wireframing changed as I gained more insight on what were success points and pain points for users. Insights gathered from usability testing helped me to design improved designs relevant to the users’ needs and goals.

You can click here to view usability testing data.

Prototype

After various tests and iterations, I created a prototype showcasing the search filter feature. Below is a limited prototype.

Click here to view the prototype or expand the frame below.