This article has multiple issues. Please help improve it or discuss these issues on the talk page. (Learn how and when to remove these template messages)(Learn how and when to remove this template message)
Demographic profiling has long been a tool utilised by marketers so that they may be as efficient as possible with advertising products or services. By targeting certain groups who are more likely to be interested in what you are selling, you can more efficiently expend your advertising resources so that they may garner the maximum amount of sales (Arnott, D., & FitzGerald, M. 1996). This is a more direct tactic than simply advertising on the basis that anyone is a potential consumer of your product, as while this may be true, it does not capitalise on the increased returns that more specific marketing will bring (Jothi, A. L. 2015).Traditional demographic profiling has been centred around gathering information on large groups of people in order to identify common trends (GfK. 2016). These trends could be to do with members of a certain age group being more likely to buy a type of product or service, such as parents with young children purchasing diapers or children's toys. They could be identified through surveys, in-store purchase information, census data etc. (Arnott, D., & FitzGerald, M. 1996).
An effective means of compiling a comprehensive demographic profile is the panacea of marketing efforts. To know a person’s name, ethnicity, gender, address, what they buy, where they buy it, how they pay, etc., is a powerful insight into how to best sell them a product (GfK. 2016). The development of this profiling is the goal of many businesses around the world, who are pouring huge amounts of money into researching it. A recent discovery that has drastically changed the way we construct demographic profiles, is metadata (Needel, S. 2013). This is the digital footprint of everyone who uses online services, the more extensive your usage, the extensive the information available on you. Companies such as google and Facebook make enormous profits through the generation and processing of metadata, which can then be utilised by companies wishing to streamline their advertising to those best suited to seeing it. This is what controls the ads on a user’s news feed, or websites they visit (Needel, S. 2013), and means that for example, an avid mountain biker, is more likely to come across ads suited towards that interest. Metadata includes information such as the amount of time spent on a website, what websites you frequent, where you clicked and how many times, what you have purchased, whom you have talked to, what they have purchased and so on. It is so pervasive that most of what you do online contributes to the information being held about you by businesses, and will directly effect what is advertised to you and what mediums this is done through (GfK. 2016).
The gathering of metadata has proved to be a controversial topic, with large amounts of people around around the world expressing discomfort at the idea of their personal information being used to generate a virtual profile of themselves for businesses to take advantage of (Needel, S. 2013). This leads to businesses needing to progress with caution in this field, and not go too far with how they use this information. To avoid future legislation being enacted that would seek to limit the collection of metadata, companies must act ethically and have people’s privacy in mind when they target people for advertising (Needel, S. 2013). An example of how this could become an issue is presented by Vastenavondt, J., & Vos, K., & Ewing, T., & Wood, O. (2013), who propose the idea of a virtual reality shopping programme. Within this programme, the shopper is greeted by a virtual attendant who knows them by name and suggests an array of suitable clothing options based on their past purchases. The shopper is delighted by the seamless nature of this shopping experience, until it come time to make a purchase. When buying the items the shopper has picked out, they opt to use their credit card. They are then asked by the virtual attendee if they are sure they would like to use that option, as their credit history suggests that cash would be a wiser option and that they wouldn’t want to default on their payments as they have in the past. You would have every right to express outrage at the business you are frequenting for not only being privy to that information, but also for using it against you in such an embarrassing manner. This highlights the need for discretion in the extent to which information is gathered, and how it is applied (Vastenavondt, J., & Vos, K., & Ewing, T., & Wood, O. 2013).
- Market segmentation
- Mass marketing
- Niche market
- Population profiling
- Precision marketing
- Psychological development
- Target market
|This section is empty. You can help by adding to it. (January 2015)|
Arnott, D., & FitzGerald, M. (1996). Understanding demographic effects on marketing communications in services. International Journal of Service Industry Management, 7(3), 31-45. Retrieved from http://ezproxy.aut.ac.nz/login?url=http://search.proquest.com/docview/233640609?accountid=8440
GfK. (2016). Tech Trends 2016: Understanding the driving forces behind the connected consumer. Retrieved from
Jothi, A. L. (2015). A study on influence of demographic factors on customers' preference towards cosmetic products. Sumedha Journal of Management,4(4), 39-48. Retrieved from http://ezproxy.aut.ac.nz/login?url=http://search.proquest.com/docview/1776777815?accountid=8440
Needel, S. (2013). Why Big Data is a Small Idea: And why you shouldn't worry so much. ESOMAR: Congress, Istanbul. Retrieved from http://www.warc.com.ezproxy.aut.ac.nz/Content/ContentViewer.aspx?MasterContentRef=d6a6c104-3a25-46e3-9bcc-f3526be49f9d&q=(%22metadata%22)+AND+(demographic+OR+marketin
Vastenavondt, J., & Vos, K., & Ewing, T., & Wood, O. (2013). Feel Nothing, Do Nothing: Unlocking the emotional secret of online spending. ESOMAR: Congress, Istanbul. Retrieved from