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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 conferencejournal
| last = Kohavi
| first = Ron
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| year = 2013
| doi = 10.1145/2487575.2488217
| isbn = 9781450321747
}}</ref>
* Robots, whether [[web crawlers]] from valid sources or malicious [[internet bots]].{{clarify|reason=what about them? do they affect the reliability of the results?|date=May 2019}}
* 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 conferencejournal
| last = Kohavi
| first = Ron
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| year = 2014
| doi = 10.1145/2623330.2623341
| isbn = 9781450329569
}}</ref>
 
* Ability to use the pre-experiment period as an A/A test to reduce variance.<ref name="cuped">{{cite conference