Build a survey app from scratch in order to collect both qualitative and quantitative data using an AI powered system to produce reliable results.
My Role
Develop Design Plan, Write Functional Requirements, Design High-Fidelity Wireframes, Usability Testing
Tools
Marvel, Sketch App, Craft prototyping by InVision
Duration
1 month
Mission
Design a high-fidelity survey mobile app that will serve as a companion to a web application, with the ability to collect qualitative and quantitative data using and AI powered system to produce reliable results for complex research projects for the Department of Defense. View the official case study here.
Discovery + Research
PERSONA
Starting off with a specific client and project in place, I created a provisional persona, Harpreet, a research student, to work around the ambiguity of this project. It is in MVP status, where our team must build a fully functioning prototype to test our scientific algorithms.
The initial users of the MVP survey app will be graduate students, working under a professor who's performing scientific analysis for a research study. They’ll use their personal handheld devices to go out, perform surveys, and collect data.
Harpreet, Research Student, Provisional Persona
“Some research projects will involve interviewing 100+ people, it’s exhausting, so anything that makes that process easier will be welcome.”
COMPETITIVE ANALYSIS
Working with the Subject Matter Expert, I started crafting the functional requirements and with that, I needed to include 4 specific question types: multiple choice, text, numeric, and a form field to collect referrals. I compared competitors offerings below:
I noticed that both a scale and matrix grid were prominent in the field. In a final round of design discussions with our Subject Matter Expert, I added more question types to strengthen the potential of data collected.
User Experience
With my persona in place, there were 3 types of survey collection methodologies that needed to be considered: snowball sampling, cluster sampling and random sampling. With that, I created user flows for each method.
USER FLOW
Linear User Flow for Survey App Use in the Field
Design Process
After crafting the user flow, I created a paper prototype and performed guerrilla usability tests. The overall flow was validated, but there were many facets that needed additional critical thinking and information from the SME as I started to scale the designs.
With a clear vision of the Snowball Sampling user flow and specific question types, I designed the initial screens for the user flow. My primary focus here was to simplify what happens when a user accepts a survey and proceed to a map to view the assigned respondent.
Usability Testing
Paper prototyping with Marvel was crucial to helping me identify the initial issues in the happy path and I was able to establish an efficient user flow.
During the second round of usability tests, I worked with mid-fidelity wireframes and performed usability testing in InVision.
First 2 iterations of a single screen at the beginning of a survey.
Third iteration. The single screen was broken out into 2 screens.
Per the examples above, I iterated on each round of usability testing, for both the user flow and other minor usability benefits such as ease of signing consent.
Results
Once the app was completed, I created a User Acceptance Testing (UAT) spreadsheet with real scenarios that aligned with the functionality of the application. I used 4 participants to validate the user flow and interactions.
Additionally, I designed an in-house field test to use the mobile app in the field with 3 participants from my office before this product would be used in the true field study in September 2018 with our SME and Research Professor at the University of California, Irvine.
In conjunction with this project, I designed the virtual operations center web app component where researchers author the surveys used in this mobile app.
View the official “JIST” case study here.