Identifying the Usability Sticking Points
This client came to me with an app already in the app store, with poor retention. My first step was to understand the goal of the application by asking the appropriate questions, such as: What problem is your app solving?
The next steps were to identify the key use cases, and features that a user needs to go through before becoming a sticky user. In this step I also used MixPanel, their go to analytics tool, to assist in identifying some of these sticky users and their behaviors.
This was followed by doing a heuristic evaluation to create hypotheses as to what sticking points might be, and cross correlate this with any existing data points they have through an application like MixPanel.
Usability Test Methodology
The final step before running the actual user tests was to create the user test methodology and script based on the information found in the previous steps. This involved creating tasks for users to perform (ie "What would you do if you wanted to replay your song"), without giving any hints or clues as to how to do it. Some of these tasks were just there to throw the user off, before giving them the next task. Some tasks asked for one thing, while I was observing for something else. Here is a subsection of the script, tasks and questions:
[Briefing: The purpose of this user test is to find out how to make Whispa more user friendly. I’ll be giving you several tasks, and questions. Please think out loud, the more you talk and express your thought process the better. There is no right or wrong.]
[Question: In your own words, how would you describe what Whispa does, to a friend?]
[Task: Create a song with drums and piano]
[Task: Add a guitar to the stage and make it’s volume 40%]
[Task: Listen to a song someone else created on Whispa]
...
The goal of the methodology was to cover the major use cases, as well as the major UX sticking points that were discovered or hypothesized in the previously described steps.
It is also important to gather relevant demographic information. For this particular app, one hypothesis was that users who do DJ understand the app better than those who do not. Other demographic information gathered was about what app the users currently use, to determine if there is a correlation between tech savvy-ness, or social-media-savvyness and the Net Promoter Score.
Post-test screening questions
“Are you able to play instruments or DJ?”
“Have you ever used any DJ or music production software in the past? If yes, when and for how long?”
“Which social media tool do you use?”
“How old are you?”
“What smartphone do you own?”
“What are your favorite apps?”
The following is an example of the key discoveries from one user test.
