From WorkCDN

Contents 1 The Facebook Platform 1.1 History 1.2 General Statistics 1.3 User Demographics 1.4 Applications 2 Development Environment 2.1 Development Documentation 2.2 Exposed user data 2.3 Development Legalities 3 Facebook Game Design Space 3.1 Analysis of the App Statistics 3.2 Target Audiences 3.3 App Distribution Models 3.3.1 The Hot Potato 3.3.2 The Pyramid 3.3.3 The Parlor Game 3.3.4 The Mustard Seed 3.3.5 The Gadget 3.4 Facebook Design Models

The Facebook Platform

History

Facebook started as a service for college students, then expanded to high school, then the workforce, and finally to the public. Facebook has been playing catch-up to MySpace for some time, but finally passed its rival earlier this year.
Social Network Stats
Facebook vs. MySpace

General Statistics

Facebook has over 175 million active users.
General Facebook Statistics
Facebook Statistical Analysis

User Demographics

More than half of Facebook users are outside of college. The fastest growing demographic is those 30 years old and older. Still, the 18 – 25 category dwarfs all others by 2:1 over 25 – 35, and many, many more multiples over all others. In short, aim for the 18 – 35 crowd. The average user has 120 friends on the site. Females outnumber males by 50%. I have not been able to find any statistics on the "Religious Views" setting in Facebook, but similar data from MySpace indicates about 40% of the members are Christian, but only about 15% feel strongly enough about the label to openly claim it on their profile.
Demographics Chart
Study of Social Network Users
Growth Trends on Facebook
Religious Stances on Social Networking Sites

Applications

More than 660,000 developers and entrepreneurs from more than 180 countries. More than 52,000 applications currently available on Facebook Platform. 140 new applications added per day. More than 95% of Facebook members have used at least one application built on Facebook Platform. The slight majority of user interactions are in game apps, but functional apps still have the lion’s share of actual installed users. A Pet nurturing game is the number one with player interactivity (2.5 mil users daily), although a poker game actually has the highest number of subscribed users (~10 mil).
Facebook Application Index
Application Statistics
More App Statistics

Development Environment

Development Documentation

Facebook’s developer site: http://developers.facebook.com/
Facebook developer wiki: http://wiki.developers.facebook.com/index.php/Main_Page

Exposed user data

API: http://wiki.developers.facebook.com/index.php/API

Development Legalities

Can’t use “face” in the title.

Facebook Game Design Space

Analysis of the App Statistics

There are a lot of Apps on facebook. Current count is more than 50,000, with 140 new applications every day. But even with all those apps, the first thing to note from the statistics is that even the largest of the games lack any serious market penetration compared to the whole of the active user base. This indicates that the market is probably heavily siloed, by game preferences types, social connections, and more recently, internationalization.

Another interesting fact is that out of the games with the top numbers of active users, there are quite a few repeats of certain companies. So, although the market seems very saturated, there’s definitely an indication that most people just aren’t getting it yet – and the few companies that have got it are staying on top. Out of the top 12 games listed on Facebook’s “Most Active” games page, six are from Playfish, and three are from Zynga. That means that out of the 63.6 million players represented there more than 75% play games from one of two companies. These companies are doing something right.

The games with the best membership seem to fall into one of two categories - either they are decent stand-alone, casual or social games in themselves, or they are games that require returning to them to perform maintenance. In either case, most of the successful games only lightly leverage the Facebook data, but still do so enough to differentiate themselves from the standard games they mimic.

From what I can tell, none of the current top games represent a new genre, or really anything that leverages Facebook data in a new way. I’m not sure yet whether that represents a lack of access to meaningful data by the API, or whether Facebook just doesn’t represent a platform that people go to, to try new game concepts.

The good news is that even thought penetration in the community is small per app, the market is large enough that even terrible apps tend to make it a surprising distance. Part of this is because of the Facebook model where users are prompted to pass on an app as they receive it.

Target Audiences

The main points from the demographics surveys are that women in their twenties and thirties are going to be the main recipient of any app on Facebook. These are also usually women that have completed at least some college, and are now just entering the workforce.

Recently there has been a lot of growth in the international sector as well. I’m not sure how easy internationalization will be to add to an app (it depends on the amount of text in the game), but it’s something to keep in mind.

As listed before, I think we can safely assume that close to 30% of the people on Facebook hold to some form of Christianity. Especially within the friend circles of existing Christians, we can expect a large number of the possible recipients to be Christian. I think this means that even an overtly Christian labeled product has the possibility of spreading well. In fact, it may help – as the user may find themselves deciding who to forward the game on to based on whether they are a Christian or not, as opposed to solely on whether they think the person will like the game.

This is also probably the place to bring up the issue that there are a lot of junk apps out there getting passed around. Due to some of the schemes listed in the Distribution Models section, too many bad apps are making the rounds and reducing much of the Facebook app system to something akin to spam. Because of this, I think we’re going to see a couple transitions in the app space. One, as in the e-mail world, people will start to become savvier about apps. I think before long many people will outright reject apps from friends unless they feel there is some extremely compelling to add yet another app to their library. Second, Facebook themselves is likely going to have to take measures to regulate “spam-like” activity. We’ll need to keep in mind that in the near future we may see the architecture or rules change suddenly to restrict what we can access or do with apps.

App Distribution Models

Clearly, for an app to thrive, it needs a method for propagation. One of the fascinating factors with Facebook apps is that they don’t really have a good distribution method other than through people passing it onto their immediate friends. Having a high feedback count on the app list, or even advertisements is a lost cause. Furthermore, even those spreading the app only have influence over their immediate friends during its spread. You can’t write a note to your friend’s friends and tell them “Keep passing the app on!” This means motivations for spreading need to primarily reward the passing of the app to a user’s immediate friends.

I’ve tried to compile a list of what I see as the various logical methodologies to employ in trying to convince users to spread your game.

The Hot Potato

There are also a lot of apps that have made passing them on as their primary game interaction. Basically, the game is reduced to the action of passing the product on to your friends in some creative way. Games in this category are things like “Kidnap” and “Snowball Fight”. Although these spread fast virally initially, because they have no continuing play drive, they burn out pretty quick. The users play with them due to curiosity, and forward them on to some friends, but after that never go back. Although adding the viral spread mechanic seems like an easy win, it also seems like a pointless endeavor unless we’re playing a numbers game. We want to make a game that engages the players, as well as hopefully encourages on-going friend interactions. Furthermore, people are becoming more wary of apps, so blind app forwarding will likely see a significant reduction over time.

The Pyramid

Another distribution model focuses on giving in-game rewards / progress for the forwarding on of the game. Players are given more units / money per each of their friends that they cause to join. While this might again work as a model for quickly spreading a game, the model detracts from the fun of the actual game mechanics (instead of succeeding because of your skill, your success is largely affected by how gullible your friends are. I feel that a game we create ought not to need to bribe its players into spreading it. Or at least try to be subtle about it.  :)

The Parlor Game

The best model for passing on games focuses on the inherent social nature of the product to encourage players to get more on their friends involved. Sure, you could play poker with anyone, but having your friends there to play seems like it could be a really fun thing. And so people forward the game on because they like the idea of playing it with their friends. Unfortunately, some of these apps still use the mechanic of having you forward it on to all your friends before you’ve actually tried it. Therefore you can end up with some really poor apps getting forwarded on just because they sounded like something that would be fun to play together.

The Mustard Seed

It seems like one last model for apps revolves around the idea of a product that gets better the more people are using it. This goes beyond just having your friends involved and deals more with the macroscopic view of the product. There are several apps that leverage this – such as the largest app on Facebook: “Causes” – and even a few apps that call themselves games are in the top numbers. Most of these really seem more focused on cause still (There’s a rainforest saving “game” and another one for reefs). Still if we could combine the Christian Game cause with a fun game that works on the local level as well, this could be a really strong distribution model.

The Gadget

One draw to pass on an app would seem to be just to make something so useful that people would want to pass it on to all there friends. Unfortunately the numbers indicate that this model by itself just doesn’t work. Especially in the game space, creating a really fun game, but one that does not leverage one of the other distribution motivators, just doesn’t seem to get the traction it needs.

Facebook Design Models

Based on the above analysis, it seems like the best model for a game would be to focus on games that get better the more people that are involved, and specifically the more friends involved. So, we should strive to include in our games either a social gameplay factor or leverage social data.

Some of the most popular social factor archetypes are as follows:

• Competitive Games: Games where the driving factor is competing with other players, either competing directly against them, or passively outdoing their score.
  • Classic casual games w/ shared high scores (and filtering to degrees of separation.)
  • Classic C.O.D. games (Make Circle of Death be Circle of Friends?).
• Cooperative Games: Games that rely on friends helping each other out to accomplish a goal. Since concurrency can not be assumed for many of these games, creating games where the teamwork can be provided adjunct would be best.
  • Teamwork based platformer or top-down shooter.
  • Cause-based interactive toy that grows a plant as the cause expands.
• Creative Feedback: Games where the player’s creative effort is shared with their friends and enhances their friend’s experience within the game.
  • Hidden object game you can create for your friends using your Facebook photos.
  • Flower arrangement game where you can send bouquets to your friends.
• Data Leveraging: Games that utilize personal or friend data to enhance the game experience. Facebook appears to expose a lot of data both for the player, and for any friends that are registered. We should seek to leverage this where ever we can.
  • Friend Mad-lib.
  • Scavenger-hunt with friend data.
  • Mystery adventure game using real friend data (locations, likenesses, etc.)
• Social Prediction: A new genre I’m working on that rewards players for being able to accurately predict popularity of items or social trends within their friends, or the populace at large.
  • Facebook virtual stock market.
  • Fashion predictor.

Naturally, the above models can be mixed to create even more interesting experiences.

• A cooperative platformer with user-generated levels (Cooperative w/ Creative Feedback), like Little Big Planet.
• A prediction based value game with user-generated content. Clint was working on this with his “Sketch-Quest” game – we were specifically aiming for a Facebook game with that. This could also be done in something like the flower shop game above, where arrangements also get valued.
• A team-based competitive game, where you and your friends compete against other teams (Cooperative and Competitive.)