Web Analytics Dives Deep Into a Sea of Data
Web analytics has come a long way from its humble origins in hit counting. Today, the process can capture a vast range of data -- and the sheer breadth of all this information creates problems for companies who need to know just what to measure, how to transform measurement into customer conversion, and how to learn more about their end customers.
"There's just so much data," explains Peter Johnson, vice president of research strategy for the Direct Marketing Association (DMA), which has just released its first annual Web Analytics Report
. "You can track everything -- but that's not a useful approach." The DMA's report, based on detailed input from 130 marketing organizations, hopes to enlighten companies on what elements of Web analytics they ought to employ for specific business goals, such as:
- increasing sales;
- improving customer loyalty; and
- monitoring Web site usability.
Specifically, the DMA report contains Web analytics feature rankings (e.g.
, the disclosure that companies consider internal search tracking to be "extremely effective" for improving conversion rates) and is interspersed with explanations and commentary from direct marketing guru "Wandering" Dave Rhee.
Eugenia Steingold, senior research manager for the DMA, explains that there are many different components to Web analytics, and that the Web Analytics Report
deep-dives into over 20 specific metrics and tools, including:
- hit reports;
- browsing patterns;
- online order volumes;
- conversion rates; and
- internal search results.
Steingold points out that both standalone and CRM-oriented Web analytics vendors deliver the goods from a functionality perspective, but that many companies are neglecting to incorporate these Web metrics into their sales and marketing strategies. "A lot of SVPs don't look at data as often as they should," Steingold points out. "You need the right people to collect and analyze data. You need to develop decision-making sensibilities so that you can adjust sales and marketing campaigns in response to real-time trends."
Johnson believes that it will take marketing organizations "another decade" to evolve beyond the status quo of campaign postmortems to a real-time model based on incoming feedback from online customer and prospect behavior. He adds that moving to this real-time, analytically driven marketing orientation can help adopters get much closer to their customers' actual needs and wants. Of course, this is only possible in the case of online
customers, who still do not constitute a majority of all customers. For example, during this year's Cyber Monday (November 26), U.S. consumers bought $733 million worth of products and services online, according to online tracking firm ComScore. While this was a 21 percent improvement over Cyber Monday 2006, it is still less than a tenth of an average day's brick-and-mortar shopping activity.
These figures indicate that Web analytics does not yet rival brick-and-mortar analytics in importance. However, given the National Retail Federation's estimates that online consumption is growing five times as fast as brick-and-mortar consumption, all marketing organizations would do well to incorporate Web analytics into their long-term planning.
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