GameNext is a mobile app prototype made for all types of gamer to, Organize their game collection, Find new games to play, Share their gaming info with friends.
In order to do make a working prototype we followed the Goal-Directed Design methodology created by Alan Cooper. This process started with Researching, followed by Modeling, then creating Requirements, and finally Frameworking.
• To expand knowledge of advance prototyping.
• To demonstrate proficiency with Figma
• Apply Figma knowledge and skills to a self-directed project.
Research is an imperative part of the GDD to understand the users’ goals and competitor’s technology. In order to do this, we split into 2 teams that we call the interviewing team and the research team.
Our team members Connor and Harrison we a part of or interviewing team which means they were at every interview and took detailed notes for us to use when making our personas later on in the modeling phase. Because of covid, we were only able to interview other classmates, but we reached out to the gamers of the class which was not hard to find. We conducted our interviews over discord with Harrison leading the interviews as the moderator and Connor as the primary faciliatory who took detailed notes. The rest of the team joined as secondary facilitatory when able to include me.
• Organize their collection
• Find new games recommendations according to taste
• Track achievements and time played
• Find good deals on games
• How do you organize your gaming collection?
• What are other things you collect and how do you keep track of them?
• How do you find new games to play?
• How do you find games on sale?
Our research team consisted of Ethan and Vlad who looked into competitors' apps and literature that talks about related topics to our apps. This helps us understand what works and what does not in the websites and apps that are related to our app.
During the lit review, they analyzed the importance of organization, having incentives and motivation, as well as some words of advice and warnings for GameNext.
Key takeaway:
1. Not all collectors are interested in keeping track of an application along with their collection.
2. Collectors have various expectations on how the user experience should be some will be ok with manually adding their games while others expect to use programs like steam.
3.We are up against the stiff competition.
During the completive audit, they looked through various apps and websites these included mobile and desktop video game sorting applications, proprietary achievement trackers for console games, and collection management tools that helped categorize other forms of media. This was so we could distinguish what works and what does not.
Key takeaway:
1. Most apps many apps were primarily a collector’s aid.
2. Not many apps went for a game-recommendation element.
3. The steam online store came up repeatedly with other apps importing the users steam library or by collecting links to the steam store.
The modeling phase is the part of our project where we take all of the information and goals, we gathered in the research phase and create. The first thing we create with this information is a persona. The persona is a character we make based on the goals and similar ideas our interviewees had and we then use this persona to look to when we are questioning if what we add is what our users would want.Based on our information we had two personas that we want to focus our app towards. While both personas have similar goals, they both have different ideas of how that looks like.
Our primary persona Kyle is a 23-year-old hardcore gamer and owns over 150 games. He wants to keep track of his achievements and play the coolest and newest games.
Kyle wants to organize his collection to see how much time he is playing specific games and get statistics on what game he has
Primary Users Goals:
•Organizing their collection
•Get recommendations of new games
•Tracking achievements
•Tracking Time played on Games
Our secondary person Jacob a 20-year-old casual gamer who has an older collection with 73 games and needs help organizing his collection he also wants to be able to find games recommended for him.
Jacob wants to organize is collection because he does not know what games he has where he also wants an easy way to decided what games he would play and would like a filter function to find games he has not played in a while, what console, and if he can play with his friends.
Secondary User Goals:
•Shown cheaper game prices
•Wants a personalized game recommendation
•Organizing collection of games across multiple consoles
This part is where we break down all of our data and put it into a list of requirements. As a team these were the requirements, we thought necessary for our app. We got this information by looking at our personas and from the data, we got during our research phase.
•Large database for users to find a majority of games
•The ability to store a user's game preferences through tags
•Recommendation system based on user ratings and preferences
•Storing user data so they can easily transfer from one phone to another
•Track game statistics such as time played in each game
• Multiple pages for owned games, currently playing and wanted games.
• Import digital libraries from Steam and other sources (PlayStation Network, Xbox Live, etc.)
• New users greeted with a welcome message, which takes them through the onboarding process
• Import physical games by scanning barcodes or manually entering data
• Show user status, online or offline
• A search function with the ability to filter by tags
• The user hears about an interesting new game then immediately looks up the game and adds it to their wishlist
• The user receives notification that his friend added a new game that he already owns on the same system. He texts his friend to ask if he wants to play a few rounds
• The user goes shopping and finds a game that looks interesting. He opens GameNext and searches through his library, discovering that he already owns the game. He puts the game back on the shelf and continues shopping.
• The user sees that his friends are playing a multiplayer game on Steam, logs into his computer, jumps into the game and plays a few rounds.
The wireframing and the prototyping was what I worked on the most. Using the information form the research phase, modeling phase, and the requirements phase I put together a low-fidelity wireframe. The wireframing part is very important to making the prototype because you can quickly make it and get an idea of the flow of the app and make decisions of what stays and what leaves.
From the data, we gather we knew the user primary goal for the app would be to organize their game collection, so we set that as their homepage.
During the research phase, we learned that users wanted to recommended games, shown what games are popular, and be told the cheapest price of a game, so we made the discover page which will recommend a game based on popularity, related games to games they currently play, games their friends play, the upcoming game, games on sale, and even games their favorite celebrity plays. Each game has its own profile page to give even more descriptions of the game. During the wireframing part, we wanted the user to be able to edit the page and decided for themselves what recommendation category should be shown first but this was proven unachievable when prototyping.
During the research phase, we learned that users would want to share their gaming information and easily view their game stats which is where the profile page was created. This page allows the user to show off their achievements, game stats, and game collection. During the wireframing part, we wanted the user to have the ability to decide what is shown on their profile page like what stats are showcased, what achievements are showed, and what games they want to showcase. This was proven unachievable when prototyping.
This project provided valuable skills in leadership, research report writing, and Figma prototyping.
While excited for the next project, there's a desire to be better prepared with interview questions, data documentation, and Figma proficiency.
Intensify interview preparation, improve data documentation skills, and delve deeper into Figma to create more interactive prototypes.
