Ronald Boire, CEO of Sears Canada, will take the top post at the bookseller in September, and current CEO Michael Huseby will become executive ...
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Broad-match is used effectively in discovery, when the retailer is attempting to determine what combinations of keywords people type in that are most relevant to the retailer`s business, Silvestre says. Once that`s established, the retailer can purchase those keywords and phrases on exact match, a more narrowly defined category that connects more directly with interested buyers.
"That`s where web analytics is important," Silvestre says. "You want a web analytics application that will capture exactly what has been typed in by people to get to your site, not just the keywords you bought."
The conversion funnel leaks. The conversion funnel analogy is that the wide end representing all visitors to the site narrows along a set of progressively more specific behaviors to conversion at the narrow end. But not everyone who makes a purchase enters at the top of the funnel, and not everyone who enters at the top winds up making a purchase at the narrow end. Analytics show that people enter and exit the funnel at multiple points. Seeing not only where these points are, but also where visitors were immediately before and after entering or leaving can inform site design to keep traffic in the funnel and moving toward conversion.
"The home page isn`t a good overall gauge of how many people are entering the conversion scenario," notes web analytics provider WebTrends/NetIQ Corp.`s Jason Palmer, vice president of product marketing and product management. WebTrends analytics can show, for example, that while 20,000 visitors abandoned the site after hitting the home page, 80,000 of the 100,000 who entered a site at a product page abandoned at that point. "Your biggest opportunity to increase conversions is the 80,000 people who exited at the product page," says Palmer. "And without being able to see where people are going, it`s difficult to understand what to improve, because you are simply making guesses based on the number of people at each step rather than basing it on where they actually went."
One WebTrends customer, for example, found a high abandonment rate at the registry log-in. But analytics suggested the reason wasn`t that people seeing the page were choosing not to register. The problem was that the registration page served a number of purposes, such as providing the ability to check order status and sign up for a newsletter. That means a number of visitors were accessing the page with no intention to purchase, though that page was in the conversion funnel.
"By being able to say how many people exited, and if they did, where they went next, we started to see that online order status was a common exit point for the site," says Palmer. "So it became important to understand what percentage of people hitting that page were not interested in purchasing but in checking order status."
While that helped provide a more accurate picture of conversion, high abandonment rates at other points in the conversion funnel can point the way toward improvements. On one WebTrends client`s site, the top exit point in the conversion funnel was a page that listed what sales taxes the site charged in different states. "It was a dry, non-exciting page that didn`t reinforce the value of purchasing from that particular retailer," Palmer says. "By redesigning those pages to reinforce branding messages and make them easier to read and understand you can work to decrease abandonment off the pages. And then with analytics you can truly see whether you are making a difference, based on being able to see the number of people who are exiting the site off that page."
Bad spelling can cost sites big bucks. Fingerhut suspected that its site search function needed work, but didn`t pinpoint the problem until it implemented web analytics from Coremetrics Inc. Finding and fixing what was wrong netted the company an extra $1 million-plus in revenue, according to Mike Sidders, director of e-commerce at Fingerhut.
The Coremetrics analysis revealed that misspellings, plurals, and other derivatives of product words that shoppers typed into the search box weren`t accounted for in Fingerhut`s site search. Compounding the problem is the fact that site visitors are using site search more than ever.
People used to finding information on the web via search are also using site search to find products at retailers, says John Squire, vice president of product management at Coremetrics. "A large number of clients and prospects don`t have good analytics around site search, such as how much of their on-site sales are attributable to site search," Squire says. "Fingerhut didn`t realize that people were using site search as much as they were."
For example, the retailer had several products associated with the word "pool." While the word "pool," typed in exactly, would bring up those products, "pools" and related searches brought up nothing. As a result, Fingerhut was missing potentially valuable traffic that was looking for products using search terms they were accustomed to using and not just those recognized by Fingerhut`s site search engine. "No products were showing up in the search, though Fingerhut had a large number of products that would be relevant. Being able to see null sets and low results sets for specific high traffic keywords pointed them in the direction of where they should fix their search engine," Squire says.
Some campaigns aren`t as profitable as they look. Marketers typically gauge the success of online campaigns by looking at traffic or revenue generated, but profitability provides the most accurate picture of a campaign`s value. By going beyond the basics to incorporate data on campaign performance from external sources--adding external pay-per-click data so as to calculate marketing costs, for instance--marketers using WebTrends analytics have experienced a few surprises in discovering which individual campaigns are really the most profitable, says Palmer.
For example, a comparison of online campaigns A and B might show that B received more click-throughs but got fewer conversions and therefore produced less revenue than A, says Palmer. So is campaign A the better performer? Not necessarily.