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online experiments

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Published By: Optimizely     Published Date: Apr 06, 2018
The Need When building websites and applications, too many companies make decisions- on everything from new product features, to look and feel, to marketing campaigns- using subjective opinions rather than hard data. The Solution Companies should conduct online controlled experiments to evaluate their ideas. Potential improvements should be rigorously tested, because large investments can fail to deliver, and some tiny changes can be surprisingly detrimental while have big payoffs.
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Optimizely
Published By: Optimizely     Published Date: Apr 06, 2018
Getting the most out of A/B and other controlled tests. In the fast-moving digital world, even experts have a hard time assessing new ideas. Case in point: At Bing a small headline change an employee proposed was deemed a low priority and shelved until one engineer decided to do a quick online controlled experiment—an A/B test—to try it out. The test showed that the change increased revenue by an astonishing 12%. That experience illustrates why it’s critical to adopt an “experiment with everything” approach, say Ron Kohavi, the head of the Analysis & Experimentation team at Microsoft, and Stefan Thomke, an HBS professor. In this article they describe: How to properly design and execute A/B and other controlled tests ? Ensure test integrity ? How to interpret results and avoid pitfalls
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Optimizely
Published By: Optimizely     Published Date: Dec 01, 2015
Statistics are the underpinning of how Optimizely’s customers use data to make decisions. We use experiments to understand how changes we make affect the performance of our online experiences. To do this, we need a framework for evaluating how likely those changes are to have an impact, positive or negative, on a business over time. To run great experiments, investing in an understanding of statistics is one of the most important skills you can develop. Statistics provide inference on your results and help to determine whether you have a winning variation. Using statistical values to decide leads to stable, replicable results you can bet your business on. Lack of understanding can lead to errors and unreliable outcomes from your experiments.
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statistics, experiments, data, customers, results, variation
    
Optimizely
Published By: Optimizely     Published Date: Jun 05, 2017
Learn about statistical significance, statistical error, and the concepts behind Optimizely’s Stats Engine: - Best practices for running your experiments to statistical significance - Tips for communicating results, optimizing low-traffic pages, using confidence intervals, and more - How Optimizely is creating an always-valid view of statistical significance
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optimizely, online experiments, statistics, statistical significance, optimizely stats engine
    
Optimizely
Published By: Optimizely     Published Date: Nov 05, 2015
Statistics are the underpinning of how Optimizely’s customers use data to make decisions. We use experiments to understand how changes we make affect the performance of our online experiences. To do this, we need a framework for evaluating how likely those changes are to have an impact, positive or negative, on a business over time. To run great experiments, investing in an understanding of statistics is one of the most important skills you can develop. Statistics provide inference on your results and help to determine whether you have a winning variation. Using statistical values to decide leads to stable, replicable results you can bet your business on. Lack of understanding can lead to errors and unreliable outcomes from your experiments.
Tags : 
statistics, experiments, data, customers, results, variation, crm & customer care, marketing research
    
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