Who Are These People and What Do They Want?

As mentioned in Chapter 1, “Introduction to Virtual Worlds,” the demographics of virtual worlds are important for two reasons:

• If you know who likes your virtual world (the actual demographics), you can use this to decide where to look for newbies.

• If you know who wants to like your virtual world (the target demographics), you can change the virtual world so as to appeal to those people.

Both of these are essentially marketing issues. In the former, the design group has the upper hand, delivering a product that the marketers have to sell; in the latter, the marketing group has the upper hand, selling a product that the designers have to deliver.

Demographics provide information as to the real-world make-up of your players (or intended players). What you do with that information is another matter, though. If there are relatively few men aged 30–45 in your user base, does that mean you should ignore that demographic (because they don’t want to play) or pander to it (because you want them to play)?

From the designer’s point of view, demographics mean generalizations, generalizations mean stereotypes, and stereotypes mean problems. These problems are four-fold:

• Some stereotypes are over-independent. If you design a game for boys aged 12–16, that’s all you’ll get.

• Some stereotypes are under-dependent. If you want to attract heterosexual men aged 18–30 to your virtual world then you should try to pack it full of heterosexual women aged 18–30.

• Stereotyping is patronizing. There are few slogans more likely to put women off a computer game than, “Designed by women, for women” ¹.

• Stereotypes force designers to embrace prejudice, whether or not they want to. All these examples, mild though they may seem, are offensive to one or another group of individuals ².

Demographic information of this nature is not generally helpful to designers of virtual worlds. Designers need to know what players want to do in the virtual world—their playing styles, rather than their socio-economic profiles. Actually, designers need to know a lot of other things about players, too, as we shall see later in this chapter; their playing styles, however, are the most important thing ³, so that’s what we’re looking at first.

Of course, members of a demographic group might share a particular playing style, but this doesn’t help unless you know what that style is; besides, not everyone will conform to the stereotype. If multiple playing styles can co-exist, so can multiple demographics, in which case actual demographics become less of an issue. This means that designers can focus on the practical matter of addressing what players of whatever background like doing, instead of what they believe players of a particular background will probably like doing.

Of course, this is useless unless you have a good categorization of playing styles.

Playing styles are defined by what players do; what players do depends on what they consider to be fun. The former can be divined from a statistical assessment of the demographic information and the latter from a psychological or sociological assessment. Unfortunately, the results of this kind of analysis aren’t always very useful. It’s all well and good knowing that some players are nurturing, helpful people, that others have problems with authority, that some like to collect objects, and so on; these may be valid playing styles, and may even be possible to address in terms of world design (introduce sick animals, quests for loners, coins with dates on them).

What such analyses don’t necessarily say is how one playing style interacts with another. What would be the effect of filling a game with nurturing types? Or loners? Or collectors? Categorizations are also more useful if they’re guaranteed to be complete. Is there an anti-nurturing type? Can an individual be both a loner and a collector? Can different virtual worlds be described in terms of their appeal to the various playing styles that have been categorized?

Players are all different, and they all behave differently. Nevertheless, there will be general playing styles that they adopt, and how these interact will have consequences on the success or otherwise of a virtual world. It would be very useful for designers if they had a demographic-independent theory of playing styles that could be used to predict the long-term future of a virtual world based on a sound categorization strategy. Armed with this, they could ensure that there were activities available for all playing styles (or be prepared to accept the consequences if there weren’t); they could introduce checks and balances to make certain that if one playing style came to dominate, the other styles would be compensated so as to keep a healthy balance; they could alter the form or functionality of the world itself to force it back into equilibrium if circumstances favored or disfavored one style over another; they could implement design protocols to guarantee that new additions to the world are always checked for their overall consequences on different playing styles.

Yes, I wouldn’t be banging on about this if it weren’t the case that there is indeed a proven model for player categorization that has sufficient theoretical underpinnings to allow for a predictive analysis of individual virtual worlds.