Systems and Methods for Predicting and Pricing of Gross Rating Point Scores by Modeling Viewer Data

Patent №

US 10,049,382

Granted

2018-08-14

Filed 2013

Owner

TUBEMOGUL, INC.

Lab

AI components

4

ml · kr · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

14143984

Systems and methods are disclosed for characterizing websites and viewers, for predicting GRPs (Gross Rating Points) for online advertising media campaigns, and for pricing media campaigns according to GRPs delivered as opposed to impressions delivered. To predict GRPs for a campaign, systems and methods are disclosed for first characterizing polarized websites and then characterizing polarized viewers. To accomplish this, a truth set of viewers with known characteristics is first established and then compared with historic and current media viewing activity to determine a degree of polarity for different Media Properties (MPs)—typically websites offering ads—with respect to gender and age bias. A broader base of polarized viewers is then characterized for age and gender bias, and their propensity to visit a polarized MP is rated. Based on observed and calculated parameters, a GRP total is then predicted and priced to a client/advertiser for an online ad campaign.

AI classification

Knowledge representation1.00
Planning1.00
Machine learning1.00
AI hardware0.96
Vision0.24
Natural language0.01
Speech0.00
Evolutionary computation0.00

Ownership

TUBEMOGUL, INC.

assignment · 321090912

Assignors

HUGHES, JOHN, ROSE, ADAM, TRENKLE, JOHN M.

On an employer assignment, the assignors are typically the inventors.

From the same owner

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