According to CBI Insights the biggest social media enterprise in world is seeking ever more detailed granularity about its users. Having already explored issue of emotion (an algorithm designed to predict emotions and adapt messages in response), Facebook is now seeking information relating to a class-related concept. This comes via a newly published patent from Facebook which is described as a system intended to assess the socioeconomic ‘class’ of each user.
The patent is based on a decision tree that takes a sample of information relating to each user. This is then assessed against some key metrics, such as whether the user is a homeowner. This information will then potentially be used to target adverts more accurately to the user.
In doing so the Facebook definition of class is conceptually weak, being based on the similar types of categories that advertising agencies use to target products at people based on demographics, educational attainment, or anticipated level of disposable income. Important as these may be for targeting consumer spending, the resultant divisions do not amount to ‘classes’ in any accepted sociological or economic sense. Social class is not fragmented in this fashion and instead it is a relational concept to the means of production from which there are only two true classes; with the overwhelming majority of a populace depend on being dependent upon a wage and a minority controlling capital. These two classes are locked in a permanent antagonistic relationship.
Putting aside the misconception about social class and focusing instead on what Facebook is actually attempting, the social media giant is attempting to process and analyze data about the consumer preference and spending power of different categories of users, as divided by geography, age, and gender. This will be in the form of creating different datasets.
Facebook already uses the following to develop niche adverts:
1. Location
2. Age
3. Generation
4. Gender
5. Language
6. Education level
7. Field of study
8. School
9. Ethnic affinity
10. Income and net worth
11. Home ownership and type
12. Home value
13. Property size
14. Square footage of home
15. Year home was built
16. Household composition
The collected information is used for targeted marketing purposes. Given that businesses that advertise with Facebook want to know more information about their customers, and how they can better reach them, the additional data analytics simply add to this purpose in finer detail.
