Whenever we interact with the Internet or make a commercial transaction on the Web, some aspect of our life and behaviour is tracked by someone. Our personal information is extremely valuable and although we may not know when, and how often it happens, the likelihood is that we appear on hundreds (or thousands) of lists regularly traded between commercial and state organisations, providing information on numerous aspects of our lives.
Organisations (both private and public) will have information stored about us covering not only our purchase behaviour, but our viewing habits, our health, our personal attitudes and views, our families and many predictions about us based on a series of geodemographic profiles such as age, class and where we live. Although this information may be held in specific, focused lists, the ability to aggregate these details into a comprehensive database has the potential to form a ‘womb to tomb ‘dossier about us all.
‘The Catalogue’ video included in this post is produced by artist Chris Oakley (2004), and explores corporate intrusion into our everyday lives. As Chris says:
‘The loyalty card, RFID (Radio Frequency Identification) chip, and facial recognition software as means of corporate data harvesting have achieved real-time tracking capabilities. Data brokers can show where we are, what we are buying, and what our wants will be. The potential already exists to extend this data beyond our purchasing habits and lifestyle choices to our very fabric, with predictions of our future health prospects made en masse via analysis of the data from our weekly shop. The Catalogue offers an analogue to this process, forcing the viewer into the position of a remote and dispassionate agency, observing humanity as a series of units, whose value is defined by their spending capacity and future needs.‘
Rencontres Internationales Paris
This video closely mirrors the commercial technique of geodemographics that emerged from the late 1970s with the launch of PRIZM by Claritas in the US and ACORN by CACI in the UK using information from geographical databases as well as from electoral registers, market research records and credit agencies to create idealised purchasing profiles and characteristics for consumers in a particular locations. Whole regions are then segmented into neighbourhoods groups known as ‘clusters’, often with shorthand catch phrases to describe the essence of the stereotypical consumer group living in each location, such as ‘pools and patios’, ‘shotguns and pickups’, ‘money and brains’ and ‘God’s Country’. Cluster systems are based on the premise that birds of a feather tend to flock together. Indeed, if you look at your own neighbourhoods (certainly at a postcode or zip code level) it is likely that the homes and cars are probably of similar size and value. If you then examine purchasing behaviours in your area, you will probably find that these are similar too. For example, consumers in clusters including houses with large gardens are likely to buy gardening related products; those dominated by apartments will not. Naturally the clustering system is not that simple, with hundreds of different overlays focusing on specific attributes to allow more informed targeting:
Possible Cluster description (compare this with ‘The Catalogue’ tags):
“Primary age group: 35-64… Median household income: $120,600… Median home value: $347,000… Predominant ideology: moderate Republican… Preferences: car phones, domestic wine, Land Rovers.”
In 2005 the UK’s Office for National Statistics (ONS) in collaboration the University of Leeds, released a free Area Classification of output areas of the UK grouping together geographic areas according to key characteristics common to the population in that grouping.
There is little doubt that, in recent years, surreptitious (and not so surreptitious) tracking of Internet users has become more aggressive and widespread. The acceptance that the data harvesting process that surrounds our lives is inevitable, and that there is little we can do to protect our privacy if we wish to take part in digital society, has led some organisations to examine new business models to help people profit from actively providing their personal information to advertisers. Privacy itself is becoming a commercial commodity.
In January at the World Economic Forum in Davos, Switzerland, executives and academics gathered to discuss how to turn personal data into an “asset class” by giving people the right to manage and sell it on their own behalf.
“We are trying to shift the focus from purely privacy to what we call property rights,” said Michele Luzi, a director of the consulting firm Bain & Co. who led the Davos discussion.
“Data is a new form of currency,” says Shane Green, chief executive of a Washington start-up, Personal Inc., which aims to pay members a commission every time their personal details are used by marketing companies. Allow Ltd., another privacy related start-up, offers to sell people’s personal information on their behalf and gives them 70% of the sale value.
Other firms are producing similar free, and paid, products that help individuals manage the way companies track their online activities. Some offer free products to block online tracking, with the objective of selling users other services, including disposable phone numbers and/or email addresses, that make personal tracking tougher or sell services that offer the removal of people’s names from marketing databases.
Of course individuals do have some legal protection from inavisions of their privacy, although this varies significantly from country to country. In many countries, Data Protection legislation imposes a number of legal obligations on organisations, that hold data on individuals, to protect that information and to reveal the extent and nature of this information when requested to do so under a Freedom of Information request. Almost certainly, the authors of such legislation did not have zombie activity in mind when they constructed the rules!
IB style written questions
1. Using the link to cluster profiles, select three cluster groups and identify four products which should be targeted at each of these groups.
2. Explain how these marketing cluster groups are identified and labelled.
3. Analyse the usefulness of marketing segmentation and consumer profiles.
4. Discuss the ethical issues of using geodemographic profiling to market goods and services.