Retail Metrics, eCommerce Data Models and Personalization – SemAngel

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Traditional eCommerce Web analytics implementations have focused on capturing the basic product funnel: from view to detail to cart to checkout. By cross-tabulating this information, you can easily see which products are moving and which aren’t. You can also tell which campaigns drive to which products. It’s certainly useful information and well used can help a product manager in a wide range of tasks.However, if all you’re capturing in your Web analytics solution is product/category information relative to the funnel, you’re missing out on many of the most interesting and most actionable from a targeting and personalization perspective variables. You may not realize this, because the analytic opportunities in a Web analytics tool can be quite limiting. But if you are moving this data to a warehouse, you can do far more. And the data you’re moving to the warehouse is – in the majority of cases – the data you’re capturing in the Web analytics tool.

via Retail Metrics, eCommerce Data Models and Personalization – SemAngel.

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