Between Ad Exchanges Using Retargeted Ads Muhammad Ahmad Bashir , - PowerPoint PPT Presentation

Data Collection Overview Visit Persona Visit Publishers Single Persona 150 Publishers 10 websites/persona 15 pages/publisher 10 products/website 14

Data Collection Overview Visit Persona Visit Publishers Single Persona 150 Publishers 10 websites/persona 15 pages/publisher 10 products/website Store Images, Inclusion Chains, HTTP requests/ responses 571,636 Images 14

Data Collection Overview Visit Persona Visit Publishers Single Persona 150 Publishers 10 websites/persona 15 pages/publisher 10 products/website Store Images, Inclusion Chains, HTTP requests/ responses 571,636 Images 14

Data Collection Overview 90 Personas { Visit Persona Visit Publishers Single Persona 150 Publishers 10 websites/persona 15 pages/publisher 10 products/website Store Images, Inclusion Chains, HTTP requests/ responses 571,636 Images 14

Data Collection Overview 90 Personas { Visit Persona Visit Publishers Single Persona 150 Publishers 10 websites/persona 15 pages/publisher 10 products/website Store Images, Inclusion Chains, HTTP requests/ responses Ad Detection Potential Targeted Ads Filter Images 31,850 571,636 which appeared Images in > 1 persona 14

Data Collection Overview 90 Personas { Visit Persona Visit Publishers Single Persona 150 Publishers 10 websites/persona 15 pages/publisher 10 products/website Store Images, Inclusion Chains, HTTP requests/ responses Ad Detection Crowd Sourcing Potential Targeted Isolated Ads Retargeted Ads Filter Images 31,850 571,636 which appeared Images in > 1 persona 14

Crowd Sourcing We used Amazon Mechanical Turk (AMT) to label 31,850 ads. 15

Crowd Sourcing We used Amazon Mechanical Turk (AMT) to label 31,850 ads. • Total 1,142 Tasks. • 30 ads / Task. • 27 unlabeled. • 3 labeled by us. • 2 workers per ad. • $415 spent. 15

Crowd Sourcing We used Amazon Mechanical Turk (AMT) to label 31,850 ads. • Total 1,142 Tasks. • 30 ads / Task. • 27 unlabeled. • 3 labeled by us. • 2 workers per ad. • $415 spent. 15

Crowd Sourcing We used Amazon Mechanical Turk (AMT) to label 31,850 ads. • Total 1,142 Tasks. • 30 ads / Task. • 27 unlabeled. • 3 labeled by us. • 2 workers per ad. • $415 spent. 15

Crowd Sourcing We used Amazon Mechanical Turk (AMT) to label 31,850 ads. • Total 1,142 Tasks. • 30 ads / Task. • 27 unlabeled. • 3 labeled by us. • 2 workers per ad. • $415 spent. 15

Final Dataset 5,102 unique retargeted ads • From 281 distinct online retailers 35,448 publisher-side chains that served the retargets • We observed some retargets multiple times 16

Data Collection Classifying Ad Network Flows Results 17

A look at Publisher Chains 18

A look at Publisher Chains Publisher-side chain Example 18

A look at Publisher Chains Shopper-side chain Publisher-side chain Example 18

A look at Publisher Chains Shopper-side chain Publisher-side chain Example • How does Criteo know to serve ad on BBC? 18

A look at Publisher Chains Shopper-side chain Publisher-side chain Example • How does Criteo know to serve ad on BBC? • In this case it is pretty trivial. • Criteo observed us on the shopper. 18

A look at Publisher Chains Shopper-side chain Publisher-side chain Example • How does Criteo know to serve ad on BBC? • In this case it is pretty trivial. • Criteo observed us on the shopper. • Can we classify all such publisher-side chains? 18

What is a Chain? 19

What is a Chain? 19

What is a Chain? 19

What is a Chain? 19

What is a Chain? 19

What is a Chain? 19

What is a Chain? 19

What is a Chain? 19

What is a Chain? 19

What is a Chain? 19

What is a Chain? 19

What is a Chain? e a e a 19

What is a Chain? e a e a a$ e .* ^pub 19

Four Classifications Four possible ways for a retargeted ad to be served 1. Direct (Trivial) Matching 2. Cookie Matching 3. Indirect Matching 4. Latent (Server-side) Matching 20

Four Classifications Four possible ways for a retargeted ad to be served 1. Direct (Trivial) Matching 2. Cookie Matching 3. Indirect Matching 4. Latent (Server-side) Matching 20

1) Direct (Trivial) Matching Shopper-side Publisher-side Example Rule 21

1) Direct (Trivial) Matching Shopper-side Publisher-side Example Rule ^shop .* a .*$ ^pub a$ 21

1) Direct (Trivial) Matching Shopper-side Publisher-side Example Rule ^shop .* a .*$ ^pub a$ a is the advertiser that serves the retarget 21

1) Direct (Trivial) Matching Shopper-side Publisher-side Example Rule ^shop .* a .*$ ^pub a$ a is the a must appear … but other advertiser that on the shopper- trackers may serves the side… also appear retarget 21

2) Cookie Matching Shopper-side Publisher-side Example Rule 22

2) Cookie Matching Shopper-side Publisher-side Example Rule ^pub .* e a$ ^shop .* a .*$ 22

2) Cookie Matching Shopper-side Publisher-side Example Rule ^pub .* e a$ ^shop .* a .*$ e precedes a, which implies an RTB auction 22

2) Cookie Matching Shopper-side Publisher-side Example Rule ^pub .* e a$ ^shop .* a .*$ a must appear e precedes a, on the which implies an shopper-side RTB auction 22

2) Cookie Matching Shopper-side Anywhere Publisher-side Example Rule ^pub .* e a$ ^shop .* a .*$ ^* .* e a .*$ a must appear e precedes a, Transition e  a is where on the which implies an cookie match occurs shopper-side RTB auction 22

3) Latent (Server-side) Matching Shopper-side Publisher-side Example Rule 23

3) Latent (Server-side) Matching Shopper-side Publisher-side Example Rule ^shop ^pub .* e a$ [^ea]$ 23

3) Latent (Server-side) Matching Shopper-side Publisher-side Example Rule ^shop ^pub .* e a$ [^ea]$ Neither e nor a appears on the shopper-side 23