We started as a team of four students who were tasked with researching a deal finder app called SKOUTDEAL that has a perfect rating online. When the strike happened our team went down to two people as the other two had dropped out at the time. The other remaining student also booked a ticket home prior and had to leave Canada in the following week. It was the worst situation to be in. However, we managed to pick ourselves back up by doubling on our weekly meetings to conduct interviews and have extended study group sessions to catch up with the rest.
We conducted user interviews within the week but the compiling phase took a bit longer, as it involved summarizing raw data into charts and graphs. I had some trouble trying to rationalize the different approaches that users took. Despite how we laid out two different possible paths in our task checklist, we couldn't incorporate them all: some users liked efficient route to an item, some users liked to take the long route, or both. Some users encountered unusual errors and thus we were not able to record the subsequent data. How should we class the missing data as? What about the steps skipped due to convenience?
We were having a lot of trouble figuring how to sort all these raw data, because when choices converge or break up like this we could have ended up with 8 graphs for the same metric, on just one scenario. I had tried to incorporate them all in messy column graphs that would cram 3 different variables but none of them worked. After sensing some pattern I tried to scribble it down and this is what we got from the task list:
This represents how different users went through when they hit a multiple choice task. We concluded that A answers always lead to long-winded route to reach the goal, while B answers let users skip a good number of tasks, as well as quick conclusion when a scenario ends. This leaves us with 2 designs: the comprehensive route and the efficient route. This has made organizing data much easier. Below are the charts we produced from this rationalization:
After testing the app with 3 candidates, we developed findings based on the duration users spent on each task and their success rate, as well as any shortcut they took. This told us the following issues:
Aesthetic issues or easy to circumvent and fleeting.
For the birthday picker, what User A wanted is a format that provides less exertion with more focus orientation. The use of yellow font on white background was a bad choice as it makes it hard to read. We recommended the following design which is a standard birthday picker for mobile.
Based on the 100% error rate on a sorting task, and user C spending double the benchmark time, we concluded they had trouble going through all the items. One user wished to remedy this by asking to turn the categories into grid that let them chunk a lot of data. It is true that by turning a long list into grid it can help reduce the length, effectively reducing scrolling time. However that still won’t solve the issue with data density. Therefore we recommended this design for their item list
Takes moderate effort to solve issue, but being able to solve it in most cases
User B spent a long time on task “Hit Select all” might be due to the fact that she wasn’t shown the category selection page through facebook sign up. User C spent a similarly long time on task “Hit Select all” because there wasn’t a “select all” button there before, thus he tried to manually deselect each categories to get to the one he wants without paying attention to the select all button.
This means there were inconsistencies, once when user signed up through Facebook and it wasn’t there, and once where it did show up, but “select all” button wasn’t there. Therefore we recommended that both sign up methods must present the same Category edit page, and when users access category edit including the shortcuts, they must enter the same page that was presented to them upon sign up.
User takes great effort to solve issue, attempts are made to use the product
Issue requires reboot if it’s an app, broken feature preventing further progress
These two were the most notorious, as such we recommended them to prioritize on tracing down the source of problem and fix the error if they wanted a functional product.
After the analysis is all done, we went to suggest their next possible ventures based on what they are missing on their site, but still relevant and within scope. We suggested that SKOUTDEAL should introduce an online market of digital goods that trade between users, and that they can top it off with a small protection fee if the products were not satisfactory. Sellers from different regions can get goods cheaper and can mark up the prices a bit more.