Presentation delivered during 9th Seminar on Media and Digital Economy (21-22 March 2019, Florence). http://fsr.eui.eu/event/annual-scientific-seminar-on-media-and-the-digital-economy-9th-edition/

1. Collecting and Selling Personal
Information:
the Two Faces of Data Brokers
David Bounie, Antoine Dubus, Patrick Waelbroeck

2. Introduction
• 2014: Oracle acquires Datalogix and Bluekai
– Datalogix:
• “Datalogix connects offline purchasing data to digital
media to improve audience targeting”
• “Datalogix aggregates and provides insights on over $2
trillion in consumer spending to deliver purchase-based
targeting and drive more sales.”

3. Introduction
– Bluekai:
• “runs the world's largest 3rd party data marketplace to
augment a customer's proprietary data with actionable
information on more than 700 million profiles.”

4. Question 1
• How does competition between data brokers
change their strategies of
– Information collection
– Information selling

5. Question 2
• What are the effects of competition between
data brokers on
– Consumer surplus
– Firms profits

6. Literature
– Bloch Demange 2018:
• endogenous collection of consumer information by a
monopolist
– Casadesus Massanell & Hervas Drane 2015:
• Privacy as competitive factor
• Competition encourages firms to lower the collection of
consumer information (unless they have a low willingness
to pay)
– Kesler & al. 2017:
• Empirically, competition between firms decreases
consumer information collection

7. Description of the model

8. Description of the model
Consumer

9. Description of the model
1
Consumer
0.50

10. 0 1
• Modelling Information:
1
𝑘
1 k2 .. ..i.. ..
Description of the model

11. Description of the model
0 1
p1 p2 … pi pk
p'1…p'ip'k

12. Description of the model
• We allow for the sale of any structure:
0 1
.. .... ..s1 s2 si sm

13. Description of the model

14. Description of the model

15. Description of the model
• Data brokers sell information:

16. Description of the model
• Data brokers compete in the price 𝑤𝑙(𝑘) and
the information partition that they sell.

17. Description of the model
• Each Data broker knows the precision of
information of its competitor
• Each firm knows whether its competitor has
acquired information and which one

18. Description of the model
• Timing:
– Stage 1: data brokers collect consumer
information with precision 𝑘1, 𝑘2
– Stage 2: data brokers set information structures
and sell them
– Stage 3: both firms set their prices and compete

19. Selling information in monopoly

20. Resolution: Optimal information selling
0
𝑗
𝑘
1 −
𝑗
𝑘

21. Resolution: Optimal information selling
• Monopolists data-brokers:
–Information sold to both firms until:
–Firms profits:

22. Resolution: Optimal information selling
• Information collection 𝑘 increases with 𝑗

23. Resolution: information collection and selling
0
𝑗
𝑘
𝑗
𝑘
0
𝑗′
𝑘
≥
𝑗
𝑘
𝑗′
𝑘

24. Selling information in competition

25. Nash Equilibrium when data brokers compete
0
p1 p2 … pi
pr
pl
p'1p'i …
• Maximum reached:
monopoly: j =
6𝑘−9
22
competition: j′ =
𝑘
3
−
1
2
0
p1 p2 … pi
pr
pl
p'1p'i …

26. Resolution: Optimal information selling
• 𝜋1 𝑘1 − 𝜋1 𝑘2
• 𝜋2 𝑘1 − 𝜋2(𝑘2)
0
0
DB2, 𝑘2
DB1, 𝑘1

27. Resolution: Optimal information collection

28. Resolution: Optimal information collection

29. Implications
• Data collection, selling and competition:
• Competition increases the precision of
information collected by the dominant data
broker
• Decreases the precision of information collected
by the smallest data broker or by both of them
when they are symmetric
• Data brokers sell more information when they
compete

30. Implications
• Consumer surplus always increases with
𝑙
𝑚

31. Implications
• The higher precision of information increases the
rent extraction effect
• The increase in the share of consumers identified
increases the competitive effect of information
• The latter dominates the former and consumer
surplus increases

32. Implications
• Firms’ profits always decrease with
𝑙
𝑚

33. Implications
• Information is more valuable for firms since the
dominant data broker collects more information
under competition
• Firms pay a lower price for better information
since data brokers compete in price, but this gain
is lower than the loss due increased competition

34. Implications
• Data protection laws and competition laws go in
opposite directions:
• Competition authorities prefer competition
between data brokers as it intensifies
competition on the product market and
benefits consumers
• Data protection authorities prefer data
brokers not to compete when they are
asymmetric in terms of market shares as the
dominant data broker collects more consumer
information

35. Questions?