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.



Searching For Profits

It's hard not to achieve greater profitability with even a cursory glance at how users interact with a Web site. A tantalizing recent statistic from a study by the Patricia Seybold Group and analytics provider WebSideStory is that shoppers who use the "site search" feature on an e-commerce site buy 270 percent more than shoppers who don't.

Automotive Web sites are among those in the forefront of analytics use. One sophisticated automotive tool is NewLeadsPlus, a lead-generation product developed for franchise dealers to reach active new-car shoppers in their area, launched by Cars.com in January using proprietary search-engine technology. An analysis by Experian Automotive of approximately 300,000 new car leads generated by Cars.com between February 2005 and January 2006 showed that more than 60 percent of those leads purchase a vehicle. The product captures active shoppers who submit their information when shopping through top search engines, including Google and Yahoo. Cars.com verifies these leads and sends them directly to the dealership within seven minutes of submission. With nearly nine out of 10 new car buyers using search engines to research vehicles they're considering, NewLeadsPlus lets dealers reach car buyers they might otherwise miss.

Ford Motor Company's FordDirect.com site lets consumers click on the vehicle of their choice, select the colors and options they want, and get a price quote from a local dealer. Based on what people are surfing on the Ford Web site, the company understands that people in the Southeast are looking for, say, beige convertibles; by analyzing the different categories in searches, they determine what vehicles they should be shipping to different areas. "This is unique among auto companies," says Sterne. But to show how underutilized such capabilities are, Sterne reports that after FordDirect was the subject of a presentation at an analytics summit, somebody stood up and asked incredulously, "Do you mean to tell me people are actually looking at Web analytics?"

Analytics Across The Channels

A third wave of the Web analytics market is beginning and involves cross-channel reporting and analysis, reports Gartner's Gassman. External users (customers, citizens, Internet surfers) interact with an organization in multiple ways, such as talking on the telephone, walking into a store, reading a newspaper ad and being visited by salespeople. While the Web is a channel with unique characteristics, it's simply another channel. "A strategic Web channel can't stand alone for long. Some organizations are already integrating Web-site-derived metrics with back-office metrics. Of these, many organizations are crafting integrated reports only several times a year," Gassman says. He believes organizations will soon demand cross-channel features from vendors that support online and offline channel management. Examples of integration include exchanging segmentation definitions, reconciling purchasing information, portal integration, and correlating Web site visits with in-store purchases across online and offline systems.

Web analytics tools could grow beyond the Web into a general customer analysis platform, reported Forrester Research's Bob Chatham last year. To find out if firms were really starting to use them that way, he surveyed Forrester's Web Analytics Peer Research Panel--admittedly, a group of early adopters. He found that while firms are most comfortable producing basic reports, they also have started exploring more valuable, complex uses, such as merging Web traffic stats with data from other channels and performing regular analysis. "Web analytics has traditionally been the domain of a small constituency within marketing," Chatham states, "but firms are finally breaking through internal barriers and connecting Web analytics to other departments, like customer service and IT." Two-thirds of respondents linked site analytics to site performance data at least monthly, and 75 percent of respondents used their analytics packages to analyze non-purchase-related self-service transactions, data that the customer service department owns.

Although such integration may not be the norm, use of the technology in most companies is somewhere in the middle. "There are companies doing it well in specific areas, but those doing it well are very shy about sharing," WAA's Sterne says. One example Sterne cites is National Semiconductor, which does a good job tying in Web site behavior with its contact-management system, letting its sales force see what customers have been searching for on the Web site.



Long Road Ahead

Some industry leaders, such as Amazon and eBay, are undoubtedly doing such data sharing and analytics, Forrester's Mulpuru says, but they are also among the most closemouthed because it is essentially their secret sauce. The job of analytics evaluation, particularly among online retailers, tends to fall to marketers, and they have enough other metrics coming at them that, beyond digging into high-level metrics like conversion and shopping cart abandonment, they simply don't have the time or the resources to look at it.

Lack of resources is seen by Sterne as "a big red flag" on the road to more advanced use of Web analytics. Although the technology is there, getting upper management to comprehend what it can do is a challenge. And once upper management understands, you still have to convince them you need the bodies to implement Web analytics, designers to build a Web site in this experimental mode, and skilled analysts to test, measure, retest, and measure again. "You need mathematical persons able to do analysis, as well as people who understand the results well enough to implement appropriate changes," Sterne says. Business users can easily find obvious problems, but good analysts see behavior patterns that point to less obvious, but still important, issues, points out Forrester's Burns in "The Business Case for Web Analysts," an August 2006 report that confronts the topic head-on. She gives the example of an analyst whose expertise at combining data from log files and page tags led him to find serious errors on a company's Web site; not only did these errors make it harder for visitors to use the site, they posed a serious security problem because they exposed sensitive client data to the public.

The argument is that by helping marketers better understand and target diverse online consumers with widely varying needs, an analyst who produces just a 5 percent improvement in the number of effective campaigns and a 10 percent lift in net revenue per campaign can improve the bottom line by more than 30 times his salary. B2B technology firms get the most lift from better site design; they get more value from deflecting call center costs through improved Web self-service than they do from better online marketing.

Short term, Web analytics tools can quickly point out problems that are easily fixed, so they offer a fast payback. But long term, the key to success with Web analytics lies in education--in making upper management aware of the value of the investment. The hard part of the equation is figuring out what it all means and what else it can help you achieve over time. "Poking the data with a stick won't do much for you," WAA's Sterne says. But if you have someone who can figure out the right questions, you can get the right answers.

Jeff Morris is a freelance writer and editor based in South Salem, N.Y. He covers topics as diverse as retail, supply chain and medical technology. he can be reached at [email protected].

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