Remove 2006 Remove Experimentation 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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Analytics On The Bleeding Edge: Transforming Data's Influence

Occam's Razor

This is very hard to do, we now have a proven seven-step experimentation process, with one of the coolest algorithms to pick matched-markets (normally the kiss of death of any large-scale geo experiment). From 2006: Is Real-Time Analytics Really Relevant? ). The benchmark for the beautiful metric AVOC is 15.3%.

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Web Analytics: Frequently Asked Questions And Direct Answers

Occam's Razor

But each keyword gets "credit" for other metrics. I have personally had a lot of success using Controlled Experimentation techniques, such as, say, Media Mix Modeling, to understand both current available demand and also segment conversion effectiveness. And this has to be a continuous approach and not discreet.

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Excellent Analytics Tip #8: Measure the Real Conversion Rate & "Opportunity Pie"

Occam's Razor

Focus on the Why (use Surveys or Lab Usability or Experimentation & Testing for example). Is Real Conversion Rate metric a good one? Segment the Visitors in the Opportunity Pie to identify what their true levers are (in getting them to buy). What do you think? Do you already use it and this is old news?