Experimentation

Experimentation is one of the fundamental areas of analytics and data science. It delivers tremendous value when applied correctly.
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The reality is that experimentation, or A|B testing, is over applied in areas where it's often least necessary but seldom applied in the cases where it can deliver the most impact.

Experimentation

Testing Everything

Many organizations fall into the trap of testing, almost compulsively, all that can be tested. The paradox of experimentation is that it gravitates towards areas of the business or product where it can be readily applied without being a necessity. This leads to over testing.

What Needs to be Tested

Better to orient testing towards major changes - the significant transformations with difficult to predict impacts. These are often the most challenging things to test. This leads to less frequent, more valuable testing.

Testing without Testing

Hakuin is an expert in experimentation, both the classical approach as well as continuous experimentation methods, using Bandits and Reinforcement Learning. But most of all, Hakuin is expert at proposing measurement without A|B testing, so that organizations can reduce testing overhead.

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Hakuin approaches analytical development as a joint venture with key executives to understand potential and design customized plans, role descriptions, architecture, and org structure with essential project deliverables in mind.

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Reduce your churn.