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* Logging: user interactions can be logged reliably.
* Number of users: large sites, such as Amazon, Bing/Microsoft, and Google run experiments, each with over a million users.
* Number of concurrent experiments: large sites run tens of overlapping, or concurrent, experiments.<ref name="ExPScale">{{cite
| last = Kohavi
| first = Ron
|author2=Deng Alex |author3=Frasca Brian |author4=Walker Toby |author5=Xu Ya |author6= Nils Pohlmann
|
| chapter = Online controlled experiments at large scale
▲ | journal = Proceedings of the 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
| date = 2013
| volume = 19
| pages = 1168–1176
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* Ability to ramp-up experiments from low percentages to higher percentages.
* Speed / performance has significant impact on key metrics.<ref name="surveyarticle" /><ref name="ExPRulesOfThumb">
{{cite
| last = Kohavi
| first = Ron
| author2=Deng Alex |author3=Longbotham Roger |author4=Xu Ya
|
| url = http://www.exp-platform.com/Pages/SevenRulesofThumbforWebSiteExperimenters.aspx▼
|
| date = 2014
▲ | journal = Proceedings of the 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
▲ | chapter-url = http://www.exp-platform.com/Pages/SevenRulesofThumbforWebSiteExperimenters.aspx
| volume = 20
| pages = 1857–1866
| |||