Google Inc.

Foley & Lardner Llp

Philip Andrew McDonnell

Shobhit Saxena

Vinod Kumar Ramachandran

Subhadip Sarkar

Shibani Sanan

Puneet Gupta

Mahyar Salek

Prashast Khandelwal

Shun Kawamura

Amit Khanna

David Owen Shanahan

Bryan Christopher Horling

Paul Haahr

Joshua J Sacks

Owen Daniel Otto

Kavi J Goel

Yair Kurzion

Michael Y Brukman

Sarvar M Patel

Michael Chu

Surojit Chatterjee

Zhengrong Ji

Taher H Haveliwala

Glen M Jeh

Amin Charaniya

Karn Seth

Lu Liu

Hyung-Jin Kim

Anshul Mohan Gupta

Mariana Raykova

Benjamin Kreuter

Sachin Kulkarni

Thai Duong

Srinivasan Seshadri

Eugen Cristian Nistor

Patrick McDonald

Mihaela Ion

Nemanja Pogarcic

Shreenath Regunathan

Amit Khann

Margo Narayan

David Owen Shanaha

Margo Werner

Yongle Cao

Vinay Goel

Systems and methods of matching identifiers between multiple datasets are described herein. A system can transmit a first identifier vector to a third party server. The first identifier vector can include a first identifier, first parameters, and second parameters. The system can receive, from the third party server, the first identifier vector encrypted based on a third-party encryption. The system can receive, from the third party server, a second identifier vector encrypted based on the third-party encryption associated with the third party server. The second identifier vector can include a second identifier, third parameters, and fourth parameters. The system can determine a correlation count between the first identifier vector and the second identifier vector. The system can determine that the first identifier corresponds to the second identifier based on the correlation count. The system can generate one identifier key for both the first identifier and the second identifier.

Generating bridge match identifiers for linking identifers from server logs

Location modeling may be generated for candidate locations based on validated location data. The location models for candidate locations may be based on validated location data associated with wireless access points that is validated using transaction data. Such validation may include comparing an identifier associated with candidate location data received from a client device to an identifier for a transaction account associated with a transaction from transaction data at a candidate location. Matching transaction data and candidate location data may generate validated location data to be used in generating location models for candidate locations.

Location modeling using transaction data for validation

A method disclosed herein may include receiving, at a first computing system, encrypted identifiers and encrypted values, performing, by the first computing system, a concealing operation on the encrypted identifiers to produce concealed encrypted identifiers, wherein the concealing operation conceals the encrypted identifiers from the first computing system and a second computing system but enables matching between the concealed encrypted identifiers, decrypting, by the second computing system, the concealed encrypted identifiers to produce concealed identifiers, and performing, by the second computing system, an aggregation operation using the concealed identifiers and the encrypted values to produce an encrypted aggregate value without accessing personally identifiable information associated with the encrypted values.

Methods for aggregating credit across interactions

A computer-implemented method for annotating online content with offline interaction data and offline interaction conversion data is implemented by a content annotating computing device in communication with a memory. The method includes receiving a set of content interaction data based on an online interaction between an online user and a first online content item, identifying at least one physical location associated with the online content provider, determining a set of offline interaction conversion data based on the set of content interaction data and a set of offline interaction data, receiving a second online content item associated with the online content provider, and annotating the second online content item based at least partially on the set of offline interaction conversion data and the set of offline interaction data.

Systems and methods for annotating online content with offline interaction data

Generating bridge match identifiers for linking identifiers from server logs

A method including receiving, at a first computing system from a second computing system, a first key and encrypted online interaction data, receiving, at the first computing system from a third computing system, a second key and encrypted offline action data encoding data indicating one or more offline actions, receiving, at the first computing system from the third computing system, executable code comprising a third key, and executing, by the first computing system, the executable code. The executable code causing the first computing system to decrypt the encrypted online interaction data and the encrypted offline action data using the first key, the second key, and the third key, correlate one or more of the offline actions in the offline action data to one or more online interactions in the online interaction data, and generate aggregate data indicating a number of offline actions correlated to the online interactions.

Data security method for privacy protection

Systems and methods of determining a geographic location based conversion via a computer network. A data processing system can receive, from a computing device, an indication of interest in an online content item that is associated with a commercial entity having a location. The system can also receive data points that each include time information and location information of a computing device. The system can generate a valid cluster indicating an activity at the location of the commercial entity by evaluating the time information and the location information of two or more data points with a duration threshold and a location threshold. The system can use the valid cluster to identify the indication of interest in the online content item as the location based conversion based on the activity at the location of the commercial entity.

Systems and methods of determining a geographic location based conversion

Multi-computing device network based cross-device conversion determination is described. A content selection computer server can identify cross-device conversions. A first computing device accesses third-party content via a first computer network connection. A second computing device accesses a webpage of the third-party content provider via a second computer network connection. The first and devices can be logged into a same online account. The content selection computer server can obtain, via a content tag that includes a script that executes on a webpage that includes the third-party content, data indicating that the first computing device accessed the third-party content. The selection computer server determines the conversion from the content tag and the second computing device having accessed the webpage. Based on a percentage of first and second sets of computing devices that have logged into common respective online accounts, the content selection computer server extrapolates an estimated number of cross-device conversions.

Multi computing device network based conversion determination based on computer network traffic

A method for linking user identifiers. The method includes receiving, by a linking server and from a company server, a first data structure comprising entries. Each entry comprising a user tag, a first hashed user information, and a second hashed user information. The method includes receiving, by a linking server and from a partner server, a second data structure comprising entries. Each entry comprising a bridge tag, a first hashed bridge information, and a second hashed bridge information. The method includes retrieving, by the linking server and from the first data structure, a first entry of the entries and retrieving, by the linking server and from the second data structure, a first entry of the entries. The method includes linking the user tag of the first entry of the first data structure to the bridge tag of the first entry of the second data structure to generate a first linkage.

Establishing a link between identifiers without disclosing specific identifying information

Systems and methods of correlating an online content interaction with an offline content interaction are provided. A data processing system can identify an online conversion by a first computing device of a content item associated with a content provider, provide an online conversion identifier to an offline conversion identification unit, receive from the offline conversion identification unit detection data indicating that the offline conversion identification unit has detected the online conversion identifier on one of the first computing device and a second computing device, and provide the detection data to a content provider computing device associated with the content provider.

Correlating online and offline conversions with online conversion identifiers

Systems and methods of estimating call conversion rates are described herein. The system can include a conversion tracker, which can receive, from a client device, an identification of a conversion event at a first time. The conversion event can be associated with a content item, content item provider, and phone number of a content item provider. The conversion tracker can transmit a request that can include the identification of the conversion event. Once received, the client device can scan the call log for the phone number and send an response indicating the phone number's existence. The conversion tracker can determine a time window in which the client device called the content provider. The conversion tracker can also aggregate the responses across multiple client devices to estimate the call conversion rate for the content item associated with the content provider.

Measuring call conversions for ads using aggregated call log data

Growing community of inventors

Mountain View, CA, United States of America

Philip Andrew McDonnell