Case Study
GG Guides
Taking a look at video game guides in 2022, and how they could be presented in a new way.
The video game industry shows no sign of stopping, but that doesn’t mean tools people use for video games are solved. In this capstone case study, I explore what an alternative to game guides may look like in the 2020s.
Part 1
Finding the Problem
The state of video game guides
Polygon.com’s front page on December 15, 2022
In 2021, the video game industry generated an estimated $60 billion (according to the NPD Group), and likewise, the amount of people playing games grows daily. These people—whether they’ve played for years or started yesterday—are spending more time than ever playing games on consoles, computers, and phones.
As someone who plays games, I’ve noticed a severe drop in quality guides and sites at the top of Google results. Searching for assistance in a game often leads to content aggregator sites with generic names and copy/pasted content—from where? By whom? It’s far different from the days of GameFAQs and print guides, where passionate people (and paid authors) provided tips and walkthroughs for the hottest new properties.
Vox Media, owner of publications such as The New Yorker, and SB Nation, noted in its recent celebration of Polygon’s tenth anniversary that: “‘Animal Crossing: New Horizons guide - Jolly Redd’s art, real or fake?’ and ‘Zelda: Breath of the Wild shrine maps and locations’ have become the #1 and #2-most-visited pages in Vox Media’s history.” (Vox Media)
With more people playing games, traffic to game guide sites has increased steadily. People playing games, people contributing to content for games, and journalists are spread across multiple outlets. The quality standards, editing, and sources for every site is unique, and few people seem satisfied with the state of video game guides.
All told, I could see the problem:
People playing games struggle to find high-quality guides, tips, and solutions across the dozens of active websites and communities that post them.
Part 2
Seeking Solutions
The competitive landscape
Parts 2 and 3 of interview affinity map on Miro
I began my search by looking at potential competitors. Game guides, tips, videos, and more get posted across dozens of sites, so I narrowed my focus to four brands that described the field I wanted to enter. What did I find?
Keeping It Recent: Sites like IGN and Fandom have contained guide ecosystems that mostly focus on games from the last five years.
Getting Older: GameFAQs, once the most loved source, has barely changed in 20+ years.
Community First, Curation Second: Guides and tips are largely written by users, for free, and distributed freely on sites like Reddit, IGN, Fandom, and GameFAQs.
Videos & Wikis Reign: Videos and wikis dominate non-message board game guides in the 2020s.
In essence, guides are mostly written by the general public, and existing sites are either dependent on newer games or saddled with technical debt. I needed to look toward the community to help curate the guides they see and write themselves.
Talking to the audience
The problem seemed to exist in the wild, but what did people who play games have to say about game guides when asked directly, right now? Who exactly was playing games and sharing guides, anyway? I set up a series of five interviews and captured my findings through an affinity diagram. I found three particularly prominent themes among the comments:
Hard To Find: People know good game guides exist, but finding them is challenging.
Moving Fast: No matter what type of gaming a person does, they find themselves searching for quick answers.
Sharing Favorites: People share favorite guides among friends but don’t have a way to collect or distribute them.
It turns out they had thought about what an alternative might look like, too. My interviewees noted that they wanted to see what people liked the most at a glance and what kind content guides were providing for certain types of games. One common request—a search algorithm that can parse natural questions—was beyond my short scope, but I recorded it in my findings.
I used the MoSCoW method to break down my features according to user needs, wants, and desirability, squared with the amount of time I could contribute to each. I identified the themes I wanted to address and the features that would support them:
Finding guides: find a guide; rate a guide
Learning from guides: save a guide
Getting help: submit a question
Helping others: submit a guide
Generating personas
I wanted to attach a theoretical person to my theoretical features. I found that people playing games had favorite genres but identified themselves less by what games they played than how they chose to play games. I wanted my personas to embody that philosophy.
GG Guides personas Margot, Tav, and Luis
Margot, the chill game player… plays games widely considered more about socializing, relaxation, or exploration. She tends to play for fun!
Tav, the intense game player… plays games widely considered difficult, deep, or competitive. They tend to play to complete games or win.
Luis, the contributor… plays games and contributes to game communities by writing guides, answering questions, or moderating groups. He plays to learn more!
Part 3
Design, Iterate, Repeat
Low-fidelity designs
Low-fidelity screens of GG Guides
I began my work on paper but moved into digital as quickly as I could, in hopes of capturing as much user data as possible before the deadline. While I had already prepared some basic branding, I opted to use a low-fidelity design system through Figma to build my screens and first prototype.
The four flows covered all of the features I’d identified in my research. I placed each flow into Maze.co and sent it to a few gaming-related communities and let it run.
Early usability test results
Maze.co usability test results
The raw data looked good, but it also highlighted some issues I needed to address in the next version. The second flow, which involved saving a guide and finding that guide on their account, had the lowest success rate and highest misclick rate, meaning I needed to revise several sections. Meanwhile, asking a question (flow 3) had the best overall results and required the fewest revisions. I identified the problem screens .
Throughout the user tests, I asked questions about how simple or difficult a flow was, what they liked, and what they’d like to see changed. One user simply said:
“It’s clean and simple.” — Tester #130633460
A few users others left thoughtful comments about how much they liked the idea and the way it worked so far, but also some revisions they’d like to see in future versions:
Likes: Simple browsing (3); one place for guides (2); design flow, as compared to competitors (2)
Dislikes: Hard-to-spot sorting (1); lack of like/dislike while viewing a guide (1); process of saving a guide (1)
Wants: Dark mode (3); ability to follow a creator or an author (1)
High-fidelity designs
Overview of hi-fi screens
Custom GG Guides logotype in color
“Your Role: You just purchased the new video game, Lost Beekeeper 3! These quests will involve you interacting with the website ‘GG Guides.’ Let’s get started!”
With the given feedback, I moved on to my final version for the 8-week cycle. I aimed for as high of a fidelity as I could by using a Figma community file based on the Ant Design React UI kit. I developed a simple logotype around the idea of GG Guides, then swapped the theme’s primary color for my own selection.
I revisited each flow from the low-fidelity design and updated the UI, then built a functional prototype for user testing and to demonstrate a few micro-interactions in the flow. Within a week of receiving feedback on the low-fidelity version, I had my next iteration ready to go.
Prototype breakdown
GG Guides prototype demonstration on Youtube
The updated prototype includes 4 total flows, with flow 2 appearing in two parts. Each section interconnects around either the home page or the game page.
I did several changes to hierarchy and scale, but the major updates based on feedback and testing included the guide submission page, improved visibility of guide filters and sorting, and the addition of the like and dislike button to the guide view.
I’ve broken down each flow below, highlighting key functions that are intended to lead the user from start to finish.
Watch the prototype in action in the YouTube video, or visit the original flow here on Figma and follow along according to their descriptions in this prototype breakdown!
Flow 1: Find a guide. Margot, the chill game player, wants to find a video guide and rate it.
Flow 2.1: Save a guide. Tav, the intense game player, wants to save a guide.
Flow 2.2: View saved guide. Tav wants to view their saved guides.
Flow 3: Ask a question. Margot has a question for GG Guides.
Flow 4: Submit a guide. Luis, the contributor, found a great guide and wants to submit it to GG Guides.
Extra: Anatomy of a game (page).
A closer look at the game page view, the most content-dense section of the site
Part 4
Future Thinking
Learnings
I discovered 3 key relevant points while learning what’s possible versus plausible in a future version to the types of users that would enjoy the site most:
Lesson 1: How, Not What. People who play games define themselves by how they choose to play less than what they play.
Lesson 2: Save Their Time. The site should be optimized to reduce the need for bookmarks, tabs, and memorization. Become a better way to track guides than a browser.
Lesson 3: Visibility Is Key. Ensure that users can access features where they expect. Run tests to validate, or invalidate, assumptions.
Challenges
It was difficult being constrained to a 7-week work cycle, since it limited initial exploration and ability to test in smaller intervals. With such a short project, the user testing pool ended up relatively small, and I didn’t gather get to gather much information on features beyond the basics. Also, real functionality is far out of this project’s initial scope. Access to a database of games and creating a search algorithm are time and money investments that would likely require funding and more team members.
What’s next?
I wanted to demonstrate the viability of a more curated, easy-to-use experience for game guides across the internet, all in 8 weeks. While there’s evidence that people playing games would enjoy a site like GG Guides, additional ideation and research would help solidify the concept and turn it from an effective experience, to something delightful. I identified three goals for future development to bring GG Guides to life:
Goal 1: Additional User Testing. Recruit more testers for high-fidelity prototype and analyze the results.
Goal 2: New Features. Add more features from the original MoSCoW analysis and the user testing process.
Goal 3: Expand Research. Find participants for additional interviews and surveys; generate journey maps.
In conclusion:
I believe GG Guides is in an early stage but could absolutely expand into a viable answer to the problem of too many guides, too many places—most not done well enough.
Citations & Links
This case study was generated by me—Taylor B. Dallas—for the Winter 2022 capstone of the Master in UX Design program at the Maryland Institute College of Art. The research and design for this case study was performed by Taylor B. Dallas, unless otherwise cited.
The images and text were originally posted on Notion.so and has been adapted for my personal site. You can view the original case study here!
iPhone 14 Pro mockup frame: @svstudioart on freepik
High-fidelity type family: Expressway on Adobe Fonts
High-fidelity UI kit: Ant Design Mobile on Figma
Low-fidelity UI kit: Lo-fi Wireframe Kit on Figma
Persona portraits: Katerina Limpitsouni on undraw.co