Web Mining: Demystifying E-Commerce Data

In this white paper by Zeke Hamdani, directory of web services at Celerant Technology Corporation takes a look at Big Data, understanding retail data that is collected online, creating a seamless cross-channel experience, and using business intelligence to analyze the data retailers already have.

It also talks about how data access and analysis initiatives need executive buy-in and empowerment to be successful. In order to get this buy-in for e-commerce business intelligence initiatives the starting point should be creating an executive-level dashboard view of key metrics that drive online operational improvement. Celerant e-commerce customers have the ability to easily create custom dashboards reports from their integrated Web mining database and business intelligence (BI) server.

Here is an excerpt from the paper:

Ceasing Cart Abandonment
In addition to understanding page level customer abandonment, it’s extremely valuable to analyze cart abandonment to understand why consumers leave potential purchases before consummating the sale. Web Mining gives merchandisers an “over the shoulder” view of consumers’ shopping patterns, allowing them to understand what drove click-through and checkout behavior at the brand, department, or style level. Collection and analysis of this data is the only accurate means of narrowing down cart level problems that lead to abandonment. This “over the shoulder” view of checkout activity can help e-commerce operators isolate such specific drivers of abandonment as shipping charge sticker shock (a high rate of customers abandoning the shopping cart at the “choose shipping method” window) or payment insecurity (a high rate of abandonment at the payment details page).

Download this white paper below to read more.