The music retailer is using Web analytics to see how customers play with the site. Their discovery: Music lovers don't surf Web sites the way the books say they are supposed to.
Controlling how people listen to a song on a CD is as easy as humming compared with controlling how 70,000 people every day navigate an e-commerce site, executives at Tower Records have discovered.
Like every other e-commerce outfit, Towers Web team makes a long list of assumptions about how people will interact with the site right before launching a new site capability. Those assumptions are often wrong because, among other reasons, the thinking process of a Web developer/designer doesnt always mesh with the thoughts of the sites visitors.
The gap between developer assumptions and site visitor realities has widened over the last few years, as visitors have become more comfortable with the Weband therefore less willing to acquiesce to the sites way of doing thingsand more empowered with conflict-friendly software such as firewalls, pop-up blockers and non-traditional browsers.
To get more in synch with visitors, Tower brought in a piece of high-end analytical software from TeaLeaf Technology. Although the software cannot see what is on the customers screen, it can get a lot closer than typical Web analytics software can, according to Kevin Ertell, Tower Records vice president of operations.
"Were seeing what they see and what they typed in and what they did," he said. "It allows us to replay sessions that people have so that we can almost see what they see."
For example, one of the Tower assumptions was that consumers would fill out online forms sequentially, answering the questions in the order they were asked. But many customers wanted to answer certain later questions first, an approach that confused the sites validation routines.
The challenge of predicting how users want to work with Web pages was recently attacked by Tower music rival Amazon.com. To read how Amazon resolved their interface issue, click here.
"People took a path that we didnt anticipate," Ertell said. "The checkout process is fairly linear. But this customer went right to the bottom of the page where the gift cards were and did that first before filling out any other information on the page. That should have been fine" but instead it delivered some "really ugly errors."
Because the error message was not explicit and customer service representatives didnt anticipate the sequence in which customers would complete forms, the errors baffled customer service until they used the TeaLeaf program to search for transactions where that error materialized. Then they played back the customers input and discovered the pattern.
Tower is the nations ninth-largest music Web site, seeing about 70,000 unique visitorsand processing about 3,000 ordersevery day, Ertell said.
"One of the big things were trying to do is make sure that we provide the best possible experience for our customers," Ertell said. "But before we start getting into any whiz-bang technology, the most basic thing is to make sure that the things we do offer work correctly. And that hasnt always been the case."
What the TeaLeaf package attempts to do is recreate what the user is seeing. It has limitations, though. It cant know, for example, what font size the customer has chosen, which might make some information appear beyond the viewing area of the screen. It may know what firewall, pop-up blocker or anti-virus programs are installed and have a list of known conflicts with those programs, but it wouldnt definitively know what impact those programs are having on the customers screen.
Part of the problem of anticipating user interface needs is that audiences can be diverse. To read about the unique e-commerce challenges of working with a very young audience, click here.
"We know the browser engine, and we know what plug-ins are plugged into the browser. For example, you can see that you have the Google pop-up blocker," said Geoff Galat, TeaLeafs VP of marketing and product strategy. "We dont see what the effects of the blockers are, but we do know that theyre there."
That said, the program analyzes a lot of available information and presents a likely view of what the customer is seeing.
The program sniffs all input at the TCP/IP level, examining "all the traffic that comes in and out. We look at everything the browser is submitting to the app and everything the app is serving out to the browser," Galat said.
Next Page: How to index everything a site visitor does?