Multi-Dimensional Consumer Groups

I'm not sure, but from what I've seen in the dev update video I had the impression consumers are devided into groups by just one dimension; meaning they are either commuters or families or sportscar fans or whatever, and that's that.
Real human beeings are much more complex. They have gender, age, income, lifestyle etc. and can therefore be grouped by many different criteria. My suggestion is to implement at least a few of these different dimensions/criteria.
My thinking is this:
In each dimension a company has the possibility of sticking out by appealing to a certain group. This would give more possibilities to get into a market and make marketing more complex but also more fun in my opinion.
For example targeting young males would probably result in getting you into the budget-sport category, since there would be a strong covaraince between those groups.
So instead of simple normal distribution you would use multivariate normal distributions with covarainces, at least, maybe even some non-normals.
In my studies I've done such things quite a few times (mainly pattern recognition) and since three months summer vacation is coming up next month I'd have a lot of time on my hands, so if you like I could then give it a try.
The only question remaining is, whether the added complexity would actually be more fun or not for most people. I'm afraid I can't answer that one...
Real human beeings are much more complex. They have gender, age, income, lifestyle etc. and can therefore be grouped by many different criteria. My suggestion is to implement at least a few of these different dimensions/criteria.
My thinking is this:
In each dimension a company has the possibility of sticking out by appealing to a certain group. This would give more possibilities to get into a market and make marketing more complex but also more fun in my opinion.
For example targeting young males would probably result in getting you into the budget-sport category, since there would be a strong covaraince between those groups.
So instead of simple normal distribution you would use multivariate normal distributions with covarainces, at least, maybe even some non-normals.
In my studies I've done such things quite a few times (mainly pattern recognition) and since three months summer vacation is coming up next month I'd have a lot of time on my hands, so if you like I could then give it a try.
The only question remaining is, whether the added complexity would actually be more fun or not for most people. I'm afraid I can't answer that one...