Analysis: Decision Trees Boost Web Site Performance - InformationWeek

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Software // Information Management

Analysis: Decision Trees Boost Web Site Performance

Too much data to make sense of the customer? Slow, one-dimensional analytics won’t cut it when Web site visitors need to see cross-sell offers in milliseconds. Decision trees help clear the path to buyer--and seller--satisfaction.

Is your company having trouble seeing through the "data smog"? That's what some have come to call the massive amount of highly relevant but disconnected and disorganized data confronting them as they try to perform Web analytics. An enterprise may have in its possession all the data it needs to make the right offer to the right customer at the right time. But the company stumbles as it tries to pull data together and mine it to discover how to make targeted offers to Web site visitors--all in the few milliseconds it has to remain competitive.

Decision trees can help you see through the data haze and improve the relevance and accuracy of Web analytics. With a long history in data mining and machine learning, decision trees aren't new. But once you see how they've been developed and deployed, you can understand their use for Web analytics.

Silos Of Smog

Businesses commonly look at a variety of data types to execute real-time customer acquisition and retention on their Web sites. Sources and types include Internet click streams, marketing campaigns, affiliate information, demographic sources, transaction data, call-center data and other information about customers and their lifestyles. An array of departments and internal and external organizations often own the data, making it hard to combine the different types. Working with each source leads to its own management and access overload; integrating the data types can be flat out overwhelming, especially in terms of expense. And you can't be sure that in the end you will have solved the problem of real-time targeting.

But the obstacles can't stop companies, which know that by combining diverse data sources, they'll arrive at a critical understanding of "who" and "what" drives online and offline sales and revenue. A Web site is a looking glass through which an organization can see the desires and needs of its customers and partners, especially when online behavioral data can be integrated with lifestyle, demographic and transactional data.

Web analytics should be the means by which a company can see through the "smog" to understand their core customers. In so doing, the company can develop consumer profiles that help align sales and marketing with specific products and services.

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