September 20, 2007, 12:00 AM

Making sense out of web analytics data

Although web analytics data can be overwhelming and difficult to interpret, retailers can take steps to understand it, apply it to improving web site operations and share its value across departments, experts said at the Shop.org conference.

Although web analytics data can be overwhelming and difficult to interpret, retailers can take steps to understand it, apply it to improving web site operations and share its value across departments, experts said at the Shop.org conference.

“Web analytics can bring more questions than answers,” said Kim Weller, senior manager of web analytics for multi-channel consumer electronics retailer Circuit City Stores Inc., who appeared on a web analytics panel. Weller was joined on the panel by retailers Dylan Lewis, senior manager of web analytics for the Intuit Turbo Tax unit of financial software retailer Intuit Inc. and Michael Fried, director of strategic analytics for outdoors sports gear retailer Backcountry.com.

Indeed, 80% of retailers in a recent study noted that they have doubts about the accuracy of their web analytics data, said Eric Peterson, CEO and founder of consultants Web Analytics Demystified, who co-moderated the panel with Patti Freeman Evans, senior retail industry analyst at JupiterResearch.

Retailers on the panel said it’s important to organize data to make it more useful, but to also get cooperation from multiple operating departments in interpreting and applying the data.

“You can lose focus on the true goal of serving customers” by concentrating too much on isolated key performance indicators without considering the overall context of a web site’s activity, noted Lewis.

“We put the same focus on web analytics data as on financial data,” said Fried. The retailer breaks down analytics data so that it can compare “apples to apples” in viewing changes in site activity, and it also combines analytics data with the results of direct surveys of customers about their shopping preferences.

At Circuit City, a careful review of analytics data revealed that shoppers were struggling with the checkout process, which enabled ther retailer to identify where to make necessary changes. Likewise, Intuit made improvements after it realized that many shoppers apparently weren’t noticing certain text intended to help make purchase decisions.

It’s a challenge, however, to make sure that all people within a retail organization charged with using analytics data actually know how to interpret and use it, Fried said. “We teach people how to use it and what the value of it is,” he said. “Then we hold them accountable to actually use it.”

To get started, it can be helpful to focus on one particular metric of site operation, such as conversions of visitors to buyers in particular product categories. Then create a flow chart to show with analytics data what leads to either an increase or decrease in that metric, Lewis said.

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