Advertising Testing Uncertainty 
Smart Data Collective
SEPTEMBER 30, 2022
Last decade made a pretty bold promise to digital advertising, which more than other industries suffers from insufficient transparency and a fraudulent environment. Currently, buy-side is most enthusiastic about blockchain implementation in ad tech, because advertisers and media buyers need good quality traffic.
O'Reilly on Data
SEPTEMBER 15, 2020
Customer stakeholders are the people and companies that advertise on the platform, and are most concerned with ROI on their ad spend. Technical competence results in reduced risk and uncertainty. In the case of Twitter, the business stakeholder’s top goals are likely centered around profits and revenue growth.
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DataRobot
JUNE 1, 2021
Even digital advertising campaigns might have specific regulatory requirements. You should first identify potential compliance risks, with each additional step again tested against risks. Recognizing and admitting uncertainty is a major step in establishing trust. Interventions to manage uncertainty in predictions vary widely.
The Unofficial Google Data Science Blog
MAY 31, 2016
However, it is generally not possible to determine the incremental impact of advertising by merely observing such data across time. One approach that Google has long used to obtain causal estimates of the impact of advertising is geo experiments. What does it take to estimate the impact of online exposure on user behavior?
Domino Data Lab
JUNE 23, 2019
As a result, Skomoroch advocates getting “designers and data scientists, machine learning folks together and using real data and prototyping and testing” as quickly as possible. That’s not very useful for finding candidates for job matching, for all the other things you want to do, or for advertising. Testing is critical.
The Unofficial Google Data Science Blog
MARCH 31, 2016
In the context of prediction problems, another benefit is that the models produce an estimate of the uncertainty in their predictions: the predictive posterior distribution. Column "a" is an advertiser id, "b" is a web site, and "c" is the 'interaction' of columns "a" and "b". $y$ y$ feature (a) feature (b) feature (c) $sigma^2$ 1.2
The Unofficial Google Data Science Blog
APRIL 16, 2019
Such decisions involve an actual hypothesis test on specific metrics (e.g. This is not the classic case of hypothesis testing via experimentation, and thus the measured effects are subject to considerations that come with the territory of unintentional data. Are the potential improvements realized and worthwhile?
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