REAL-TIME BIDDING SYSTEM THAT ACHIEVES DESIRABLE COST PER ENGAGEMENT

Patent №

US 10,949,893

Granted

2021-03-16

Filed 2019

Owner

TUBEMOGUL, INC.

+2 more

Lab

AI components

4

ml · kr · planning · evo

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

16572299

Systems and methods are disclosed for optimizing an online advertising campaign both before the campaign begins, and dynamically during the campaign. Optimizations are performed comparatively between a plurality of MPs (Media Properties) based on their relative cost-per-engagement. Comparisons are performed by first stack ranking MP inventory including any of sites, feeds, and verticals, based on cost per engagement. Once ranked, scores are assigned to the targeted inventory and a mean score is determined. Then, the inventory is rated as high, normal, or low impact based on their scores compared with the mean and a standard deviation for all scores. Higher impact sites with scores at least a standard deviation above the mean are initially favored, and the MP targeting strategy is dynamically adjusted during the campaign based on periodically re-evaluating the MP rankings, frequencies of engagement, and campaign progress relative to fulfillment in an allotted run time.

AI classification

Planning1.00
Knowledge representation1.00
Machine learning0.73
Evolutionary computation0.58
AI hardware0.40
Vision0.00
Natural language0.00
Speech0.00

Ownership

TUBEMOGUL, INC.

assignment · 503920996

ADOBE SYSTEMS INCORPORATED

assignment · 503930001

ADOBE INC.

namechg · 503930814

Assignors

THAKKAR, KEVIN, TRENKLE, JOHN M, HUGHES, JOHN, ROSE, ADAM, LOPATECKI, JASON

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

From the same owner

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