Examples:
• Most purposes explained in this notice rely on the storage or accessing of information from your device when you use an app or visit a website. For example, a vendor or publisher might need to store a cookie on your device during your first visit on a website, to be able to recognise your device during your next visits (by accessing this cookie each time).

Vendors 856

Examples:
• A car manufacturer wants to promote its electric vehicles to environmentally conscious users living in the city after office hours. The advertising is presented on a page with related content (such as an article on climate change actions) after 6:30 p.m. to users whose non-precise location suggests that they are in an urban zone.
• A large producer of watercolour paints wants to carry out an online advertising campaign for its latest watercolour range, diversifying its audience to reach as many amateur and professional artists as possible and avoiding showing the ad next to mismatched content (for instance, articles about how to paint your house). The number of times that the ad has been presented to you is detected and limited, to avoid presenting it too often.

Vendors 799

Examples:
• If you read several articles about the best bike accessories to buy, this information could be used to create a profile about your interest in bike accessories. Such a profile may be used or improved later on, on the same or a different website or app to present you with advertising for a particular bike accessory brand. If you also look at a configurator for a vehicle on a luxury car manufacturer website, this information could be combined with your interest in bikes to refine your profile and make an assumption that you are interested in luxury cycling gear.
• An apparel company wishes to promote its new line of high-end baby clothes. It gets in touch with an agency that has a network of clients with high income customers (such as high-end supermarkets) and asks the agency to create profiles of young parents or couples who can be assumed to be wealthy and to have a new child, so that these can later be used to present advertising within partner apps based on those profiles.

Vendors 640

Examples:
• An online retailer wants to advertise a limited sale on running shoes. It wants to target advertising to users who previously looked at running shoes on its mobile app. Tracking technologies might be used to recognise that you have previously used the mobile app to consult running shoes, in order to present you with the corresponding advertisement on the app.
• A profile created for personalised advertising in relation to a person having searched for bike accessories on a website can be used to present the relevant advertisement for bike accessories on a mobile app of another organisation.

Vendors 643

Examples:
• You read several articles on how to build a treehouse on a social media platform. This information might be added to a profile to mark your interest in content related to outdoors as well as do-it-yourself guides (with the objective of allowing the personalisation of content, so that for example you are presented with more blog posts and articles on treehouses and wood cabins in the future).
• You have viewed three videos on space exploration across different TV apps. An unrelated news platform with which you have had no contact builds a profile based on that viewing behaviour, marking space exploration as a topic of possible interest for other videos.

Vendors 265

Examples:
• You read articles on vegetarian food on a social media platform and then use the cooking app of an unrelated company. The profile built about you on the social media platform will be used to present you vegetarian recipes on the welcome screen of the cooking app.
• You have viewed three videos about rowing across different websites. An unrelated video sharing platform will recommend five other videos on rowing that may be of interest to you when you use your TV app, based on a profile built about you when you visited those different websites to watch online videos.

Vendors 238

Examples:
• You have clicked on an advertisement about a “black Friday” discount by an online shop on the website of a publisher and purchased a product. Your click will be linked to this purchase. Your interaction and that of other users will be measured to know how many clicks on the ad led to a purchase.
• You are one of very few to have clicked on an advertisement about an “international appreciation day” discount by an online gift shop within the app of a publisher. The publisher wants to have reports to understand how often a specific ad placement within the app, and notably the “international appreciation day” ad, has been viewed or clicked by you and other users, in order to help the publisher and its partners (such as agencies) optimise ad placements.

Vendors 925

Examples:
• You have read a blog post about hiking on a mobile app of a publisher and followed a link to a recommended and related post. Your interactions will be recorded as showing that the initial hiking post was useful to you and that it was successful in interesting you in the related post. This will be measured to know whether to produce more posts on hiking in the future and where to place them on the home screen of the mobile app.
• You were presented a video on fashion trends, but you and several other users stopped watching after 30 seconds. This information is then used to evaluate the right length of future videos on fashion trends.

Vendors 406

Examples:
• The owner of an online bookstore wants commercial reporting showing the proportion of visitors who consulted and left its site without buying, or consulted and bought the last celebrity autobiography of the month, as well as the average age and the male/female distribution of each category. Data relating to your navigation on its site and to your personal characteristics is then used and combined with other such data to produce these statistics.
• An advertiser wants to better understand the type of audience interacting with its adverts. It calls upon a research institute to compare the characteristics of users who interacted with the ad with typical attributes of users of similar platforms, across different devices. This comparison reveals to the advertiser that its ad audience is mainly accessing the adverts through mobile devices and is likely in the 45-60 age range.

Vendors 583

Examples:
• A technology platform working with a social media provider notices a growth in mobile app users, and sees based on their profiles that many of them are connecting through mobile connections. It uses a new technology to deliver ads that are formatted for mobile devices and that are low-bandwidth, to improve their performance.
• An advertiser is looking for a way to display ads on a new type of consumer device. It collects information regarding the way users interact with this new kind of device to determine whether it can build a new mechanism for displaying advertising on this type of device.

Vendors 689

Examples:
• A travel magazine has published an article on its website about the new online courses proposed by a language school, to improve travelling experiences abroad. The school’s blog posts are inserted directly at the bottom of the page, and selected on the basis of your non-precise location (for instance, blog posts explaining the course curriculum for different languages than the language of the country you are situated in).
• A sports news mobile app has started a new section of articles covering the most recent football games. Each article includes videos hosted by a separate streaming platform showcasing the highlights of each match. If you fast-forward a video, this information may be used to select a shorter video to play next.

Vendors 181

Examples:
• An advertising intermediary delivers ads from various advertisers to its network of partnering websites. It notices a large increase in clicks on ads relating to one advertiser, and uses data regarding the source of the clicks to determine that 80% of the clicks come from bots rather than humans.

Examples:
• Clicking on a link in an article might normally send you to another page or part of the article. To achieve this, 1°) your browser sends a request to a server linked to the website, 2°) the server answers back (“here is the article you asked for”), using technical information automatically included in the request sent by your device, to properly display the information / images that are part of the article you asked for. Technically, such exchange of information is necessary to deliver the content that appears on your screen.

Examples:
• When you visit a website and are offered a choice between consenting to the use of profiles for personalised advertising or not consenting, the choice you make is saved and made available to advertising providers, so that advertising presented to you respects that choice.

Examples:
• You used your loyalty card when purchasing sunglasses at a local boutique. If you later browse content relating to summer travel, this information may be combined with your previous purchase recorded by the boutique’s loyalty program to present you with ads for swimsuits or other beach accessories.

Examples:
• You visited an online retailer website from your computer to look at mystery books and you consented to your data being used to create profiles for personalised advertising. If you later browse on your phone using the same Wifi, a vendor may infer you have been using both devices and you may be presented with an ad about the same mystery books in the mobile app you are using, but only if you have consented to receiving personalised advertising on this app.

Examples:
• When you see an ad in your weather forecast app, some technical details that your device always transmits when accessing the Internet (such as the IP address of your Wifi and the version of your device’s operating system) can be used for instance to limit the number of times you see the same ad in other apps.