A system for digitally testing one or more variants of a webpage, comprising: a processor; and a memory having programming instructions stored thereon, which, when executed by the processor, performs at least the following operations, comprising: initiating a testing service for one or more variants of a webpage associated with a client computing system; receiving, via one or more application programming interface endpoints, user data comprising one or more indications of one or more users interacting with the one or more variants of the webpage; inputting the one or more indications into a machine learning model comprising a Bayesian multi-arm bandit algorithm; generating, using the machine learning model, one or more results comprising causal performance estimates and a set of decision rules to adaptively design further testing experiments based on the causal performance estimates, the generating comprising: using results learned from experimentation on another webpage of a website comprising the webpage to inform allocation behavior of the webpage by identifying missing site content on the webpage that was expected to be presented based on the results learned from the experimentation on another webpage of the website and recommending a new module within the webpage based on the missing site content; and generating a portal comprising the one or more results, the portal accessible to one or more end users. a processor; and a memory having programming instructions stored thereon, which, when executed by the processor, performs at least the following operations, comprising: initiating a testing service for one or more variants of a webpage associated with a client computing system; receiving, via one or more application programming interface endpoints, user data comprising one or more indications of one or more users interacting with the one or more variants of the webpage; inputting the one or more indications into a machine learning model comprising a Bayesian multi-arm bandit algorithm; generating, using the machine learning model, one or more results comprising causal performance estimates and a set of decision rules to adaptively design further testing experiments based on the causal performance estimates, the generating comprising: using results learned from experimentation on another webpage of a website comprising the webpage to inform allocation behavior of the webpage by identifying missing site content on the webpage that was expected to be presented based on the results learned from the experimentation on another webpage of the website and recommending a new module within the webpage based on the missing site content; and generating a portal comprising the one or more results, the portal accessible to one or more end users. initiating a testing service for one or more variants of a webpage associated with a client computing system; receiving, via one or more application programming interface endpoints, user data comprising one or more indications of one or more users interacting with the one or more variants of the webpage; inputting the one or more indications into a machine learning model comprising a Bayesian multi-arm bandit algorithm; generating, using the machine learning model, one or more results comprising causal performance estimates and a set of decision rules to adaptively design further testing experiments based on the causal performance estimates, the generating comprising: using results learned from experimentation on another webpage of a website comprising the webpage to inform allocation behavior of the webpage by identifying missing site content on the webpage that was expected to be presented based on the results learned from the experimentation on another webpage of the website and recommending a new module within the webpage based on the missing site content; and generating a portal comprising the one or more results, the portal accessible to one or more end users. using results learned from experimentation on another webpage of a website comprising the webpage to inform allocation behavior of the webpage by identifying missing site content on the webpage that was expected to be presented based on the results learned from the experimentation on another webpage of the website and recommending a new module within the webpage based on the missing site content; and generating a portal comprising the one or more results, the portal accessible to one or more end users.