Fuera de Control, cómo los consumidores son explotados por la industria de la publicidad en línea. Digital Marketing Advertising

How clients are exploited by the net advertising industry14. 01. 2020Table of contentsTable of contents . 21 Summary .

51. 1 Introduction . 82 Background: The digital advertising and adtech industry . 122. 1 Profiling and centered advertisements .

122. 2 Actors in adtech and electronic advertising and marketing . 132. 3 Alternative company models for electronic marketing . 162. 4 Tracking and private data processing by third party owners .

17 2. 4. 1 Data brokers. 19 2. 4. 2 Third party data providers .

22 2. 4. 3 Measurement, attribution, and ad verification . 232. 5 Unique identifiers . 25 2.

5. 1 Matching identifiers through ID syncing . 25 2. 5. 2 Google Play Android Advertising ID .

28 2. 5. 3 System level opt out settings. 312. 6 Real time bidding .

342. 7 Push from civil society and regulators . 393 The harmful outcomes of profiling and behavioural ads . 433. 1 Consumers do not are looking to be tracked, but feel powerless . 433.

2 Power asymmetries and shortage of transparency . 453. 3 Manipulation. 463. 4 Discrimination . 473.

5 Purpose creep . 493. 6 Security and fraud . 513. 7 Chilling consequences and freedom of expression . 523.

8 Reduced trust in the digital economic climate . 533. 9 Ad fraud and degradation of online amenities . 544 Methodology: Observing data flows from apps to third events . 554.

1 Method . 564. 2 Expected and sudden data transmissions. 584. 3 Limitations of the data flow evaluation . 585 Information and selection in apps .

605. 1 Review of ten apps. 61 5. 1. 1 Perfect365: One Tap Makeover .

63 5. 1. 2 MyDays Ovulation Calendar and Period Tracker. 67 5. 1.

3 Period Tracker Clue Ovulation and Cycle Calendar. 68 5. 1. 4 Tinder and OkCupid . 70 5.

1. 5 Grindr . 72Page 2 of 186 5. 1. 6 Happn.

READ  Free Traffic Sources for Affiliate Marketing in

75 5. 1. 7 My Talking Tom 2 . 76 5. 1.

8 Muslim Qibla Finder, Prayer Times, Quran, Azan . 78 5. 1. 9 Wave Keyboard Background Animations, Emojis, GIF . 806 Analysis of information flows and third parties receiving own data.

816. 1 Location data agents . 82 6. 1. 1 Fysical .

83 6. 1. 2 Safegraph . 86 6. 1.

3 Fluxloop. 89 6. 1. 4 Unacast . 92 6.

1. 5 Placer . 95 6. 1. 6 Placed/Foursquare .

996. 2 Behavioural personalization and focused on . 102 6. 2. 1 Receptiv/Verve . 103 6.

2. 2 Neura . 106 6. 2. 3 Braze .

108 6. 2. 4 LeanPlum . 1126. 3 Systemic oversharing . 115 6.

3. 1 AppsFlyer . 1176. 4 Google and Facebook . 120 6.

4. 1 Google . 121 6. 4. 2 Facebook . 1227 Cascading data sharing via Grindr .

1237. 1 The advertising era in Grindr. 123 7. 1. 1 Twitter’s MoPub .

125 7. 1. 2 AppNexus ATandT . 131 7. 1. 3 Bucksense .

135 7. 1. 4 OpenX . 140 7. 1. 5 PubNative.

144 7. 1. 6 Vungle . 147 7. 1. 7 AdColony .

153 7. 1. 8 Smaato . 1577. 2 Self certification and cross device tracking . 160 7.

2. 1 The challenge of self certification . 1618 Legal evaluation . 1628. 1 The General Data Protection Regulation . 163 8.

1. 1 Data topics, controllers, and processors . 164Page 3 of 186 8. 1. 2 Definition of personal data .

1668. 2 Legal basis for processing of own data . 167 8. 2. 1 Consent .

168 7. 2. 1. 1 Freely given and exact . 168 7. 2.

1. 2 Informed and unambiguous . 169 7. 2. 1. 3 Explicit .

170 8. 2. 2 Fulfilment of a contract. 171 8. 2.

3 Legitimate interests . 172 8. 2. 3. 1 Interests, rights, and freedoms of the data field .

173 8. 2. 3. 2 Interests of the controller . 1758.

READ  How to Choose the Right Ad Server Plus Top Ad Servers Reviewed

3 Conclusion of legal evaluation . 1779 What needs to be done?. 1788. 1 The spread of own data is against the law. 1798. 2 Authorities must implement the law .

1808. 3 Marketers and publishers must take responsibility . 1828. 4 Conclusion. 1839 Glossary . 184Page 5 of 186 highly sensitive infer attributes adding sexual orientation and non secular beliefs.

o The dating app Grindr shared specified user data with a large selection of third events which are concerned in advertising and profiling. This data included IP tackle, Advertising ID, GPS location, age, and gender. Twitter’s adtech subsidiary MoPub was used as a mediator for much of this data sharing, and was observed passing own data to a couple of other commercials third events including the foremost adtech businesses AppNexus and OpenX. Many of these third parties reserve the proper to share the info they bring together with a very large number of companions. o The makeup app Perfect365 shared user data with more than 70 third events.

This data included the Advertising ID, IP address, and GPS location. Many of the third events that were receiving this knowledge are in the enterprise of gathering, using and selling vicinity data for lots of commercial purposes.