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Carvoyant is the fast and easy way to diagnose user car troubles without a trip to the mechanic. Answer questions, capture audio and done!
Craig is a car enthusiast. His favorite activity is changing oil and passing his knowledge to his kids. But his efforts are no match for their utter lack of interest. And not just his kids, but many car owners don't have the interest to learn how to fix their own vehicle. They turn to the internet to figure it out, not knowing the correct terminology or car parts to look up. Some car owners take it to a mechanic only to find they over paid to identify an easy fix. Both of these can be a waste of time and money.
Not all car owners care for cars, but they do love technology! Users no longer have to ponder what information they need to look up. Carvoyant asks all the key questions to determine the problem. Starting with vehicle specifics like make and model. It then asks for sensory details such as car light, vibrations or smell of gas or smoke. Last, users allow the app to capture the car sound. Carvoyant is cheaper than a trip to the mechanic and faster than searching on the internet.
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This project was designed during a one week sprint and followed a truncated design process. Each day focused on a step within design thinking. I held a discovery workshop with my client prior to the sprint.
The audience is young car owners aged 25-39. Older generations, like Craig, tend to have more car knowledge and don't need an app to help them with their car problems. The target audience is the middle class and budget conscious. Mechanics are expensive and can cause monetary stress on a car owner. Those in a lower income bracket are also more likely to own older cars which will in turn require more maintenance. The target audience is self-reliant and like to fix their own problems, however in this case have little to no car knowledge.
Referring back to Sam, what questions does he have about fixing a car. Turning those questions into "How Might We" statements helps identify possible features. These features define the scope of the project.
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Tests were conducted with 18 participants, 5 over zoom and 13 on Usability Hub. Participants had to complete the following tasks:
1) Once on the homepage, how do you start a new diagnostic?
2) Pretend you drive a 2008 Hyundai Accent GLS 4 Cylinder Automatic, how do you input that into the app?
3) How do you tell the app you noticed the check engine light is on?
4) Pretend you have been experiencing a strange noise under the hood on the driver side. How do you indicate that to the app?
5) How do you start sound recording?
The design offers comprehensive steps, with clear prompted questions to get to a diagnosis.
The features follow mental models, and allow users to relate the app to their car, helping them decipher the problem without actually understanding the problem.
Users have the option to save information for later to reduce cognitive load the next time they have a car issue.
The app provides a solution to a problem many car owners suffer, and has the potential to educate and help users save money.
If I had more time:
When the app is released, I would look at adding features such as:
