2011 Experimentation Measurement Reporting 
Domino Data Lab
AUGUST 6, 2021
It was first defined by the US Federal Reserve and Office of the Comptroller of the Currency ( SR 11-7 ) in April 2011. The process of doing data science is about learning from experimentation failures, but inadvertent errors can create enormous risks in model implementation. Model implementation.
Occam's Razor
OCTOBER 21, 2013
In late 2011, Google announced an effort to make search behavior more secure. The Multi-Channel Funnels folder in Google Analytics contains the Top Conversion Paths report. At the highest level, across visits by focusing on unique people, the report shows the role search plays in driving conversions. See Page Value there?
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Occam's Razor
APRIL 8, 2013
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. First, you figure out what you want to improve; then you create an experiment; then you run the experiment; then you measure the results and decide what to do.
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).
The Unofficial Google Data Science Blog
OCTOBER 12, 2017
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. Make experimentation cheap and understand the cost of bad decisions. This leads to the proliferation of post hoc hypotheses. What is to be done?
Occam's Razor
NOVEMBER 2, 2015
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 covers, content, marketing and measurement.
O'Reilly on Data
MAY 11, 2020
Television only lacked the immediate feedback that comes with clicks, tracking cookies, tracking pixels, online experimentation, machine learning, and “agile” product cycles. YouTube’s algorithm was measuring what kept viewers there the longest, not what they wanted to see, and feeding them more of the same. And the cycle goes on.
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