Remove 2015 Remove Experimentation Remove Measurement Remove Metrics
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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.

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Experiment design and modeling for long-term studies in ads

The Unofficial Google Data Science Blog

by HENNING HOHNHOLD, DEIRDRE O'BRIEN, and DIANE TANG In this post we discuss the challenges in measuring and modeling the long-term effect of ads on user behavior. Nevertheless, A/B testing has challenges and blind spots, such as: the difficulty of identifying suitable metrics that give "works well" a measurable meaning.

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Magnificent Mobile Website And App Analytics: Reports, Metrics, How-to!

Occam's Razor

But why blame others, in this post let's focus on one important reason whose responsibility can be squarely put on your shoulders and mine: Measurement. Create a distinct mobile website and mobile app measurement strategies. Media-Mix Modeling/Experimentation. Remember my stress earlier on measuring micro-outcomes?).

Metrics 141
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The 2015 Digital Marketing Rule Book. Change or Perish.

Occam's Razor

Most companies are astonishingly blasé about data and possibilities of measurement. " Sad, unimaginative measurements of their sad, unimaginative campaigns. Allocate some of your aforementioned 15% budget to experimentation and testing. This blog is about the joys of measurement and the transformative power of data.

Marketing 140
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To Balance or Not to Balance?

The Unofficial Google Data Science Blog

In an ideal world, experimentation through randomization of the treatment assignment allows the identification and consistent estimation of causal effects. See Hainmueller (2012), and the work of Zhao & Percival (2015) for more details on how this optimization problem is solved, and for further discussion.

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Introducing the vector engine for Amazon OpenSearch Serverless, now in preview

AWS Big Data

The vector engine supports the popular distance metrics such as Euclidean, cosine similarity, and dot product, and can accommodate 16,000 dimensions, making it well-suited to support a wide range of foundational and other AI/ML models. To create the vector index, you must define the vector field name, dimensions, and the distance metric.

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Estimating causal effects using geo experiments

The Unofficial Google Data Science Blog

It is important that we can measure the effect of these offline conversions as well. Panel studies make it possible to measure user behavior along with the exposure to ads and other online elements. Let's take a look at larger groups of individuals whose aggregate behavior we can measure. days or weeks).