Oath Inc.

Amobee, Inc.

Excalibur Ip, LLC

Verizon Media Inc.

Yahoo Ad Tech LLC

Wentong Li

Yi Mao

Kuang-chih Lee

Quan Lu

Jian Xu

Ali Dasdan

Goutham Kurra

Burkay Birant Orten

Hang Qi

A system for retargeting customers is based on a mobile device query initiated by a user, and includes a query module configured to receive a query with geographical information from the mobile device and determine geographical identifiers of the mobile device. An indexed database stores an aggregated plurality of customers having a geographical identifier proximate to the determined geographical area, and a processor selects an advertiser located proximate to the determined geographical area. A performance feedback module is configured to assign an effectiveness rating to one or more advertisements provided by the selected advertiser based on marketing attributes of the aggregated plurality of customers. An advertisement recommendation module then recommends one or more advertisements provided by the selected advertiser based on the assigned effectiveness rating, and the aggregated plurality of customers are retargeted by transmitting the recommended advertisements to one or more customers of the aggregated plurality of customers.

Location retargeting system for online advertising

A system is provided for retargeting advertisements and is based on a database storing user behavior data related to information for a plurality of consumers. An index-lookup processes the user behavior data and translates the user behavior data into a plurality of indices. A data loading module processes the plurality of indices and generates a multi-indexed user behavior cube. An online query module receives a request for an advertisement and processes the request to determine one or more related user attributes and retrieves user behavior data from the multi-indexed user behavior cube using the related user attributes. An ad recommendation module receives the set of user behaviors and generates a list of recommended advertisements using the set of user behaviors data and an advertiser retargeting criterion.

Behavioral retargeting system and method for cookie-disabled devices

A system may provide for mobile application based online advertising via mobile application interface. A database may be configured to store data corresponding to a plurality of visual elements for rending an advertisement. An advertising server may be in operative communication with the database and configured to receive requests for advertisement campaigns. A mobile interface may allow submission of information relating to an advertisement campaign to the advertising server. A generator engine may be configured to select from the plurality of visual elements and generate display logic for displaying an advertisement corresponding to the advertisement campaign.

Systems and methods for implementing a mobile application based online advertising system

Described herein are techniques and systems for online ad campaign pacing. The techniques described herein use budget allocation along with the estimations of bids and response rates. With use of budget allocation, the techniques can use budget pacing to enhance impressions and maximize desired responses, such as desired click-through rates. These techniques focus on enhancing pacing and performance of ad campaigns, such as enhancing performance across distinct and/or unified online ad marketplaces. These techniques are especially useful in the context of a demand-side platform (DSP). In some examples, the techniques assume that impression supply is much larger than advertiser demand for impressions of their ads, so such techniques focus on selecting high performing inventory of ad space. Yet, with such a focus, a smooth or consistent delivery of ads over time is used.

Pacing control for online ad campaigns

Embodiments of the invention present an approach to conversion rate estimation which relies on using past performance observations along user, publisher, and advertiser data hierarchies. More specifically, embodiments of the invention model the conversion event at different select hierarchical levels with separate binomial distributions and estimate the distribution parameters individually. It is shown how to combine these individual estimators using logistic regression to identify conversion events accurately. Embodiments of the invention can also handle many practical issues, such as data imbalance, missing data, and output probability calibration, which render this estimation problem more difficult for a real-world implementation of the approach.

Estimating conversion rate in display advertising from past performance data

For each of various sites, a mathematical representation is computed according to prescribed characteristics of users that have conducted one or more predetermined types of interaction with the site. Cluster of the sites are identified whose computed representations are similar according to prescribed criteria. Responsive to notification of an opportunity to deliver unidentified advertising to a given user via a given site, at least one ad is selected based upon factors including the ad having a prescribed performance history at one or more clusters containing the given site. The selected ad is transmitted to the given user at the given site, or a bid is transmitted for such placement of the ad.

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Saratoga, CA, United States of America

Wentong Li