Lost in the Matrix of Data? Learn How Leading Companies Optimize Their Customers' Digital User Experience

By John Kim, Product Manager —

"All I see now is blonde, brunette, redhead."


Image courtesy of The Matrix

For those of you who aren't nerds like me (but since the movie grossed $263M, it seems a lot of you are), that line is from "The Matrix." It’s about a computer hacker who discovers that the world is just a computer simulation. When he escapes and sees the simulation code from the outside for the first time, another escapee mentions that eventually he'll get used it and will be able to make out what the code represents, notably blondes, brunettes, and redheads. My reaction to that was, "yeah, right."

I'm sure any of you who have done web analytics probably feel the same as me. Most tools and packages provide you with an endless stream of data running across your screen like a torrent of numbers. What they don't give you is the why. When I worked at a small consumer web start-up, we instrumented our site to measure every metric we possibly could. We also used as many free web analytics packages as we could find (we were a startup, after all). Sure, we could find out the basic stuff like overall conversion rate or response time, but my boss would pound his fists on the desk asking, "What happened on step X that caused a 30% drop to step Y?" It's unlikely that a 600ms vs. 300ms response time was the primary culprit. We eventually had usability clinics where we brought people in but ran into a basic issue time and again: it's not real. The usability clinics were helpful but they were still just simulations. I could see that the subjects didn't want to seem stupid and tried a lot harder than they would've sitting at home. What we wanted/needed was a way to see what people were doing in the real world.

That's why I came to Tealeaf. It was not (just) because of my boss' fist pounding but because I wanted to figure out why customers weren't continuing from step X to Y. And many larger companies come to Tealeaf for the exact same reason. Traditional web analytics tools can take them only so far, and they want to go the last mile. One of the first times I heard of this was from a leading travel company. They noticed they were having significant drop-off during the checkout process on the billing page. They also noticed that many customers were getting billing address verification errors. They kept asking how this was possible. How many people don't know their home address? It turns out that it wasn't the home address that was causing the problem. When they ran a Tealeaf replay of some of the sessions that had this issue, they found that the issue was the layout of their billing form. It had fields for Name, Company, Address, Credit Card, etc. Because the Company field was just before the Address field, many customers were entering their employer's address in the Address field, not their own. This would cause the credit card address verification to fail. This issue cost them literally millions of dollars a year in bookings and the fix took less than a day to implement (they simply hid the Company field).

As another example, a leading financial site noticed that many customers were having difficulty signing up. Worse yet, users kept trying to sign up and continued to fail over and over again, specifically on the email validation section. Replaying these sessions revealed that many customers were typing a "2" instead of the "@" sign or didn't include the domain at all. But the original error message simply said that the email address was invalid without indicating why. So people kept repeating the same error over and over again. The fix was to simply show an example of how the email address was supposed to be formatted. As a result, their conversion rates jumped significantly.

You're probably asking yourself, "they probably have millions of sessions a day, that's like finding a needle in a haystack," and you'd be right. It's like finding a diamond-encrusted $10 million dollar needle. But take heart because these companies did, in fact, find them. How? By using Tealeaf scorecards, events, and search, they were able narrow the segment to just the affected sessions. Then, they simply took a sample of sessions from that segment.

It should be noted that both of these companies also use other web analytics tools. In fact, many Tealeaf customers do. But why did they need Tealeaf to discover these issues? Because although the other tools could provide data as to what was happening—the unending flow of numbers as seen in "The Matrix"—but only Tealeaf could show what was happening in the real world. These customers also admit that they probably could have eventually realized what was going on just using numbers. But that was not the point for them. They were losing revenue every day because of these issues and Tealeaf helped them discover and resolve these issues significantly faster. Besides, how long would it take you to see a blonde, redhead, brunette in the picture above?