Hit and Miss: Why High Traffic Streams Need not Lead to More Online Business (page 1 of 2)

In their paper "Capturing Evolving Visit Behavior in Clickstream Data," Peter Fader, a professor of marketing, and Ph.D. student Wendy Moe point out that commonly used measures of web store success-such as number of hits, page views, and average time spent at a site-provide only generalized information about customers, lumping together everyone from brand-new Internet surfers to serious repeat buyers. In search of more detailed information, the authors scrutinized clickstream data for two powerhouse websites: A leading online bookstore and a popular online CD store from 1998 over an eight-month period. They came up with a unique model of consumer behavior at the individual level, which they say yields a new wellspring of knowledge to help e-businesses manage and market their web stores more successfully.

"A lot of sites right now are looking at their values and saying, 'Our traffic is increasing, our company is doing great, our long-term future is wonderful,'" comments Moe. "But if you look at it on the level of the individual customer, that's not the case." Moe and Fader found that individual consumers' behavior-especially in a changing environment like the Internet-tends to evolve over time. As they visit repeatedly, the behavior of site users starts to change. Moe explains, "As people start learning about a site, they start using internal knowledge to make their decisions: They don't need to actually go to the store to access information. As a result, they'll go to the store less frequently." Another evolving behavior to take into account, she says, is that "a lot of people are hopping on the Web and surfing just out of novelty. But eventually that novelty's going to wear off, and people will go to a website only when they need to."

The Moe-Fader model reveals that evolving individual-level behavior patterns appear actually to contradict the conventional larger-picture perspective. Specifically, the summarized data for each of the two leading e-commerce sites they examined seemed to suggest an acceleration in customer visits. Yet their analysis suggests that the typical household is in fact experiencing a gradual slowdown in visiting rate over time. How could this difference be explained? The authors found that an increasing number of new visitors were coming to each site over time, masking the possible slowdown or even dropout of many experienced visitors. This effect, say Moe and Fader, could have dramatic implications for managers who neglect to examine their data at a sufficiently close level: "If such a pattern were to continue, future prospects for the store would appear less promising, especially when the arrival of new users inevitably begins to taper off."

How is it possible to track the evolution of consumers' visiting behavior in such detail? For their study, the authors mined Internet clickstream data collected by Media Metrix, a New York-based digital media measurement company. Media Metrix maintains a panel of some 10,000 participating households who have installed special software on their personal computers so their Internet behavior can be recorded, pageview by pageview, over time.

Using this data, Moe and Fader were able to glean cross-sectional variations in store-visit behavior as well as changes over time in consumers' behavior as they gained experience with the two sites. "Thanks to rich new sources of data such as Media Metrix," they point out, "we can now examine behavioral phenomena that would be impossible to study using more traditional sources," such as grocery store scanner data or traditional retail loyalty cards, both of which only record visits that end in a purchase.

Besides uncovering significant facts about the evolution of customer behavior at web stores, Moe and Fader identify a valuable new target market.