RAYDAR helps young adults planning a night out decide on an activity quickly and efficiently by leveraging proximity-based, real-time, personalised activity suggestions.
As humans, social interaction is essential for regulating our emotional and physical health. People who are more socially connected to family, friends, or their community are happier, physically healthier, and live longer, with fewer mental health problems than people who are less well connected (South University, 2018). Currently, young adults looking to socialise on any given night can spend hours scouring through social media pages, lifestyle blogs and websites or, if they’re lucky, reaching out to friends in the area for suggestions and ideas. This information is oftentimes outdated, incomplete, digitally inconspicuous and not readily available or curated to fit individual preferences.
Navigating the process of finding information on activities while curating an outing experience with friends often proves to be time consuming, overwhelming and exhausting. Between finding an activity that doesn’t break the bank and agreeing on the time and location of the activity with friends, curating the perfect night out has become a major challenge for many young adults.
Young adults are spending too much time sifting through night-out options with no straightforward system. Young adults need an easy and quick way to decide what to do on any given night out.
In order to determine what our users’ main pain points were, we carried out a preliminary survey to understand what factors they’d consider most important during the decision making process. We found that the top three considerations for users when deciding on a night out activity were; Proximity, Value for Money and Quality of food/services.
We decided to narrow down the user sample size in order to address the problem effectively. We then conducted 8 user interviews. From these interviews we obtained similar results with proximity of the user being one of the main considerations among users when deciding on a night out activity.
What we concluded from our research was that for many young adults, it’s not the unavailability of fun things to do, but rather the time spent sifting through various sources for information on fun things happening around them that is most painful. And so we started our journey at RAYDAR by exploring the question;
‘How might we provide personalised activity suggestions to young adults planning a night out so that they make decisions on where to go faster and more efficiently?’
Our hypothesis is that if a young adult is provided with fewer personalised suggestions for places to visit or things to do for a night out, they will spend less time on their phone and suffer less decision fatigue and ultimately make faster and more efficient decisions while planning a night out.
RAYDAR helps young adults planning a night out decide on an activity quickly and efficiently by leveraging proximity-based, real-time, personalised activity suggestions.
RAYDAR will help young adults make the decision on where to go on a night out faster and more efficiently by providing real-time, proximity based, personalised night out suggestions. While the possibilities of developing RAYDAR into a collaborative night out curator are endless, our MVP is predominantly aimed at providing accurate suggestions based on inputs from our users or as we like to call them ‘Vibe Checks’.
RAYDAR as an MVP is launched with 4 key features
Since our target demographic for RAYDAR is young adults (predominantly Gen-Z users) we decided to opt for a colourful, lively and interactive design. Our hope was to create an intuitive and fun user experience for users. We used different user interface formats for each Vibe Check to avoid monotony and enhance the overall experience.
According to Norman’s design principles, one of which is user feedback — The user must receive feedback after every action they perform to let them know whether or not their action was successful. The loading animation lets the user know the current system status and reduces anxiety during waiting periods.
For the personalised recommendation results, we only present a few suggestions in order to reduce the efforts for users to make a final decision. Test users said the recommendation model was new and straightforward and they were willing to use it if the results were accurate.
After we showcased our prototype to the users again, we learned that users were impressed by the product but wanted the option to navigate the process as well as the ability to store their activity history.
Raydar is a map-centric mobile application (relies on the user location) that gives curated events locations based on some preset options ranging from concerts to food to visiting the mall amongst other things.
In order to increase the accessibility of the application to a wide range of users, we decided to create both an IOS and android version of the Application. Currently, the Application is not hosted on Google Play store or the Apple App store. However, we have provided an APK file for the iOS App and a link to the Android APK where users can download and install the App on their phones.
On the Front-End, the Android App was built using Kotlin and XML while the iOS App was built using Flutter. IDE Android studio was used for the Android App while VS Code was used for the iOS App.
The API's used were Google Places API for getting information about places using HTTP requests and Google Maps SDK for adding Google Map to the App, adding markers and providing informations such as map locations to the user
Creating both an Android and IOS version of the Raydar App meant that we had less time to develop certain features that would’ve made the app more interactive and fun for the user. Additionally, due to budgetary constraints, we had to build the app using Google Cloud’s free credits system. This meant limited access to API functionality and limited feature development for Raydar.
What are some key takeaways?
In eight weeks, we were able to create an MVP that has a lot of potential for growth. From speaking with our test users, we learned that future iterations of RAYDAR might should provide the users with options to save their activity history, collaborate with their friends in the vibecheck process or even suggest the most accurate suggestions based on multiple user locations to further ease the decision making process for users and make the overall experience fun and collaborative.
While we don’t plan to keep working on RAYDAR after the Co.Lab program, our team is very proud of what we’ve accomplished in such a short amount of time. We are grateful to have had the experience to establish new connections and work in a multi-disciplinary team.
Ultimately, flexibility is at the basis of a truly agile development methodology. Identifying where our flexibility as a team lay and building that into the product development process allowed us to adapt to changes and still have the ability to deliver a successful product.
