Applying analytics effectively-constructing a useful A/B test

Analytics show us how people behave when they are on their own and not being observed or directed. However, analytics are ambiguous because we cannot identify user intentions, expectations, or satisfaction with analytics. They just show behavior and not why it is happening. For example, if the conversion rate from visitor to buyer on an e-commerce site is below expected, visitors not converting because of your terrible checkout process or the high prices of your products? If we consider page views, another popular metric; are users visiting a lot of pages because they are exploring your site, or because they cannot find what they want?

It is very easy to gather analytics with sites ...

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