Update on the social gaming space
A lot has happened to the social game space in the last year or so. Shortly after EA’s purchase of Playfish in 2009, a lot more developers began working on Facebook titles, and a number of new shops opened up to specifically target the platform. From the player’s perspective, there have been developments too – people are starting to scoff a little less at the idea of playing a game on Facebook as a legitimate activity, players have become increasingly comfortable with parting with money for the experience, and the more dubious methods for extracting revenue have largely fallen by the wayside.
What about the games?
These developments have more to do with the business imperative for games on Facebook, though, and less to do with what’s happening in the games themselves. On that front, things aren’t moving quite as fast. The bulk of the new games are generally functional copies of older ones, and even the more novel designs still feature a lot of plain token-passing and grind for the sake of grind. In particular, very few games are making use of the fact that they’re connected to an enormously valuable data source: The social network.
Making more out of the network
Social networks typically have “a high degree of partial overlap”. A person has an average of about 150 friends, and might share 75 or so with their closest friend, 60 with the next-closest, and so on. By looking at these measures of overlap, as well as indicators like wall-to-wall messaging, we can build a picture of who these friends are and what a user’s relationship to them is. A game could exploit this by encouraging cooperation (or rivalry) with your closest friends, or encourage you to get back in contact with people you haven’t spoken to recently. Finding clumps of densely-connected people probably means you have a ‘clique’ that might enjoy operating as a group in the game, and so group quests can be offered to them to encourage that participation.
Good for business
A better understanding of the of social connections – and quality of those connections – is going to be better for business, too. If a person has a higher friend count than the average friend count of their friends, they are generally a more influential person. If a ‘hub’ user has good things to say about your game, that praise will go out to more people. In fact, if you want to get really sneaky, you can bias the game in favour of these users, giving them more free stuff and making things slightly easier for them. It’s effectively making the game ‘cheaper’ for them in recognition of the fact that they’re likely to increase the Average Revenue Per-User (ARPU) through encouraging others to play. From a marketing standpoint, they are essentially micro-advertisers rather than sources of revenue. This tactic is hardly new – the promotion strategy for the first commercially-available toothpicks consisted of giving free packs to influential students at Harvard University, with a special request that the toothpicks be used as conspicuously as possible. The field of Viral Marketing calls these people Alpha users, though discussion seems to focus mainly on finding these users in the first place, rather than the tailoring of an adaptive system to bias alpha users in favour of it.
Other types of users
Another user of particular interest to social gaming is one who spends money on playing the game. These users are referred to as “Whales”, a term borrowed from the casino industry. In casinos, these people can often spend millions of dollars in a single visit. In social games, however, the figures are much more modest – a “Whale” is generally someone who spends around $20 per month. Often, though, it seems that players with money would be happy to spend a lot more. It would be possible to reveal progressively more extravagant purchases for a “Whale” to pick up, where the emphasis could shift from gameplay to collection and memorabilia. Examples could include a figurine of their in-game character, large-format schematics of a player’s farm/city/restaurant/etc, books that chronicle their progression through the game or simply an alternate electronic view of their game-worlds. As the top end of the available purchases climbs higher, the number of purchasers required to justify investment in them should hopefully decrease, since one purchase at a hundred dollars yields as much return as twenty purchases at five dollars.
While the discussion of these strategies here might seem cold, the role of the game designer is to pick methods for engaging the player, or game mechanics, that are appropriate both in the context of the underlying theme and in combination with one another. If used in the right context, a socially adaptive model can lead to a more personalized experience for individual players. It can expose certain mechanics to people who are likely to appreciate them, and keep those mechanics out of way the for people who won’t. Everybody wins!
[UPDATE] It turns out that Zynga does allow users to spend a lot more than the $20/month figure, but it seems like people only have a good reason to do so in their Poker game. Since poker requires players to engage in oneupmanship in the form of ever-increasing bets, it’s not really making use of an adaptive model for determining the best way to make use of a user. Still, it’s very interesting to know that someone is offering players the opportunity to spend as much as they want – and that some players are doing just that!