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Web Analytics Turn Art Into a Science

What's the secret to running a successful Web site? Web analytics tools can help track and analyze online behavior, opening up a world of possibilities that brick-and-mortar businesses never dreamed of.

What's the secret to a successful Web site? For many companies, it's nothing short of a change in internal culture--from artful, marketing-style intuition to scientific, analyst-style number crunching. The level of sophistication in using analytics tools runs the gamut, ranging from companies relying on Web activity data and using it proactively, to others that have no idea what the metrics mean. A big part of the difference has to do with the way people think and their corporate culture.

"How do they decide what to put on their site?" asks Forrester Research analyst Megan Burns. "How do they think about the whole process? Are they more scientific and data-focused?" Burns is aware of one company that wouldn't go online at all until it had a way to measure what was going on from day one. But that's the exception.

Although nearly all retailers now make concerted efforts to carefully display assortments of new products and top sellers on their home and section pages, and provide richer imagery, something is still missing from online merchandising. The evidence: Conversion rates--the percentage of site visitors who complete a transaction--have hovered stubbornly in the 2 percent to 3 percent range for the past five years. While those percentages are enough to make a direct marketer drool, they are disappointing if you take into account that site visitors are "entering" a store and obviously looking for something.

Left Brains Needed

Online enterprises have a distinct advantage in that they have Web analytics tools available to track and analyze online behavior, opening up a world of possibilities that brick-and-mortar businesses never dreamed of. How can Web analytics be used to help improve results? One thing retailers should be doing is looking at different metrics, says Sucharita Mulpuru, Forrester's senior analyst for consumer markets. "For the first time we're starting to see an opportunity for science to take a more prominent role versus the art of merchandising," Mulpuru says. She advocates applying the principles of what colleague Shar VanBoskirk termed "left-brain marketing planning" to merchandising. Left-brain merchandising is a customer-focused and data-driven approach to online retail that, in its most reduced form, means that merchandisers scrutinize the data from site analytics, business intelligence tools and transaction databases to create a 360-degree picture of their customers. This helps them understand Web site behavior and thereby drive the factors within their control, such as site navigation, product assortment and display, adjacencies and cross-sell rules.

Data Driving The Customer

One approach to becoming a data-driven online merchandiser, Mulpuru says, is to apply the principle of the planogram, which exists at many brick-and-mortar retailers, to the Web. A planogram shows what items go where. The purpose is to improve overall sales and make optimal use of consumer traffic patterns. Similarly, a "Webogram" helps companies create business rules that optimize margins and inventory turns on key pages, such as home pages, popular paid search landing pages and checkout pages. With these practices, online retailers can capture incremental gains that will sustain the double-digit annual growth many have experienced. Those business rules could be created by expanding the list of metrics (such as the rarely used conversion rate by item) that online merchandisers look at, and by creating different executions of key Web site pages and testing them.

For any enterprise with a Web component, the Web site goal that is common across multiple business models--and the chief determinant of Web site "success"--is the extent to which site visitors ultimately do whatever it is your business would like them to do, whether it be placing an order, signing up for an account, completing a questionnaire or requesting more information. Since Web analytics look at behavior on a site, the only way to get meaningful metrics is to first define what it is you want people to do; only then can you also define success. If your goal is to deflect potential service calls, for example, that's one set of activities that defines success. Companies should start with business objectives, recommends Forrester's Burns. Retail tends to be the easiest to define--you want people to go to the site and place an order--but if you're not selling online, placing an order doesn't apply. "You need to ask, 'What are customers trying to do online that might not necessarily make us any money, but will help our company in the long run?'" Burns says. This variety of objectives, compounded by the increasing tendency of enterprises to depend on the Web channel for sales, lead generation, content distribution and customer support, means that more organizations are using their Web channels strategically rather than tactically. Such a change is especially significant because "this increasing strategic importance is driving the market away from basic Web site usage reporting tools toward Web analytics tools," states Gartner analyst Bill Gassman in his report, "MarketScope for Web Analytics, 2Q 2006."

Not all organizations are ready for the most-sophisticated analytics solutions. An organization's operational maturity must match the sophistication of the technical solution to achieve return on investment.

That the level of sophistication in using Web analytics varies widely is echoed by Jim Sterne, president of the industry advocacy group, Web Analytics Association (WAA). "There are pockets of really smart people doing really neat things, and others are flailing around wildly trying to get themselves wrapped around it," Sterne says--and which you are largely depends on whether you have a thought-out business model.

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