We obtain data compliantly from a variety of sources. These include:
Personal Data means any piece of information that can be used to identify you. Obvious examples of personal data might include your name and postal address, an email address or date of birth.
However, even 'online identifiers' such as IP addresses and cookie IDs could be personal data. In a world where our lives are increasingly lived 'online', we are all creating digital identifiers - when you're exercising, listening to music online, messaging friends or doing anything that involves a smartphone or connected device. Your fridge, car or washing machine can now be hooked up to the internet - all of these could be personal data when linked to other data about you.
Personal data may also include special categories of personal data, such as ethnic origin, religion or sexual orientation. These are considered to be more sensitive, and organisations may only process them in more limited circumstances, and with additional protections for you.
Special category data is personal data which the law says is more sensitive, and so needs more protection.
This refers to data about:
No "special category" personal data is obtained or processed by Experian Marketing Services in the creation of our own products and services.
We do, however, work with responsible organisations including those in the public sector and political organisations who use our marketing products and services to improve the relevancy of the messages they send you. These organisations may have collected special category data that they ask us to process on their behalf.
We conduct analytics projects on behalf of some of our clients, so we could process special category data provided to us by our clients (if they have it on their database) and they have instructed us to do so. For example, we may do analytics project work for organisations, which contain health information of individuals collected by the organisation. In all cases, any special category data processed on behalf of the client is done so under contract only for that client, on their instruction, and is not processed or used in any of Experian Marketing Services' marketing products and services. It is protected by strict Experian data security controls as well as abiding by the Australian Privacy Principles.
Whilst not personal data, we use aggregated and anonymised information from public data sources and market research surveys on some special category themes as part of the many measures we use to inform how segmentation clusters like Mosaic are described. For example, the Australian Census is accessible to anyone through the Australian Bureau of Statistics (ABS) website and contains information on topics such as ethnicity, religious beliefs and health (to name a few). However, this data is available from the ABS website only for geographic areas, for example for meshblocks, which contain an average of 50 households.
In our Marketing Services business, when we obtain personal data obtained from our third-party commercial data partners, we do not knowingly obtain or process data about individuals under the age of 18. While we insist that the personal data we receive from our data partners should only relate to individuals aged 18+, through our internal verification processes we take additional steps when this data comes into Experian to check that any personal data we handle relates only to Australian adults aged 18+.
Much of the data we obtain does not relate to individuals but rather to households, properties or geographic areas. Using statistical techniques, Experian uses non-personal data sources to build models to indicate the likelihood a household or geographic area exhibits certain characteristics and behaviours. For example, the likelihood of there being children present in the household, or the likelihood an area has lots of people who might visit a retail fashion outlet.
This is data that can't identify you. This might be because:
Lots of organisations use statistical techniques ('analytics') to identify patterns in behaviour across their customer base. For example, if a retailer uses data which contains a customer's name and address along with transaction history to create insight into trends and behaviours across the whole customer base, it is not necessary to know who the individual is, so the name and address can be removed leaving anonymised data to be used in the analytics process.