2011 Experimentation Measurement Metrics 
Occam's Razor
APRIL 8, 2013
To win in business you need to follow this process: Metrics > Hypothesis > Experiment > Act. We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. That metric is tied to a KPI.
The Unofficial Google Data Science Blog
OCTOBER 7, 2015
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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The Unofficial Google Data Science Blog
OCTOBER 12, 2017
With more features come more potential post hoc hypotheses about what is driving metrics of interest, and more opportunity for exploratory analysis. We data scientists now have access to tools that allow us to run a large numbers of experiments, and then to slice experimental populations by any combination of dimensions collected.
Occam's Razor
OCTOBER 21, 2013
In late 2011, Google announced an effort to make search behavior more secure. This is a simple custom report I use to look at the aggregated view: As the report above demonstrates, you can still report on your other metrics, like Unique Visitors, Bounce Rates, Per Visit Value and many others, at an aggregated level. One product line.
The Unofficial Google Data Science Blog
MAY 31, 2016
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).
Occam's Razor
NOVEMBER 2, 2015
Success Metrics. In my Oct 2011 post, Best Social Media Metrics , I'd created four metrics to quantify this value. For the rest of this post, I'm going to use the first three to capture the essence of social engagement and brand impact, and one to measure impact on the business. It is not that hard.
O'Reilly on Data
MAY 11, 2020
It predates recommendation engines, social media, engagement metrics, and the recent explosion of AI, but not by much. The Entertainment” is not the result of algorithms, business incentives and product managers optimizing for engagement metrics. And like a lot of near-future SciFi, it’s remarkably prescient.
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