VietnamAtoZ is a local search tool that help people find a place to go (e.g. coffee shop) in a certain area (e.g. Charlotte) with a simple method: entered Keyword, (hyphen) area (e.g. Coffee, Charlotte)

CASE STUDY

We wanted to create a new web that help people find a place to go (e.g. coffee shop) in a certain area (e.g. Charlotte) with a simple method: entered Keyword, (hyphen) area (e.g. Coffee, Charlotte) All the coffee shop list in Charlotte will right into the screen in less than 1 second with filter functions such as Free wifi, outdoor seats, free parking on the left bar. Once they click to see detail, they can see shop hours, users review, shop signature, services – it’s a 3 ways communication between user-user, user-staff, staff-manager to improve their business.

My role was user experience design, user interface design and evaluation of the project.

We analyzed questions from 20 users age from 17 to 37 (urban and social, outgoing and shopping savvy) and discovered that around 60% of users are forgotten the exact name of the place they went before or somebody told them.

From this analysis, we made 4 user personas and defined their experience searching with the customer journey map.

We carried out focus groups with 10 users to co-design an early prototypes base on this idea and then show 2-3 alternatives low fidelity user interface sketches that emerged as an output of that process. We came up with 2-3 wireframes and selected alternative 2 but improved with alternative 3 features that worked better in the lab.

In two weeks field trial with 100 users, we found the error of keywords/location search misspelled. We did not have the time to address this challenge. But in the next phrase, we focused on misspelled and build data lists to solve the issue. We moved the filter functions to the right side since the user is using the right hand (touch or mouse) We also had load-balancing at concurrent users in peak time. Our final version was successful, during a 2-week user test, misspelled keywords/locations are replaced by auto-correction, by our data list defined. It reduced error from 25% to 3% of all errors. Our Alexa range also improved and got invested $50,000 by our clients after we honor to achieve the top startup project organized by Forbes in 2015.