You've distilled checkout into a single, user-friendly page. Great ... except your analytics tool can no longer track the process.
ROI analysis and Web analytics packages go hand in hand. But a Catch-22 is slowly taking shape: funnel analysis has led to redesigns that condense the user experience, effectively eliminating the funnel. Once the funnel is gone, there's no way to get good analytics.
This holds true for companies across the board: from retail to financial, from B2C to B2B. Let's look at some trends, and factors to consider when choosing how to maximize your online ROI.
One Page or Long Process?
Several high-profile companies have condensed their checkout funnel to have the minimum number of pages possible. In retail, "Persistent Carts" present shopping cart mini-views so the user must no longer leave the product page when adding an item to the cart. Many companies have created one-page checkout systems. Existing users are sent immediately to a "review your order" page, at which point they can make any changes. If there are none, they need only click "checkout." The process is basically the same for new, unregistered customers. In financial services, calculators and other tools that were once several pages long are now single Flash-based components.
These advances create terrific user experiences -- at a cost. It's tougher to perform analytics on these streamlined sites. Traditional "funnel reports" show customer flow through a process. The retail checkout process is basically shopping cart; sign-in/registration; billing info; shipping info; order review; and order confirmation. For a mortgage calculator, the process was enter a page or two of information; request more information and/or create an account.
When these processes take place on only one page, it's difficult to analyze why people are dropping off. How can you say, "people aren't purchasing when the shipping costs are more than X percent of the total price," when shipping information is presented at the same time as sales tax, delivery details and other information? How can any analysis be performed on just one of these data points?
Major e-commerce players BN.com reverted from "Persistent Carts" back to a traditional shopping cart page (though now a fully merchandised page). Amazon.com doesn't have a persistent cart, but it does have a one-page checkout process. BN.com has a traditional checkout process, and replaced its persistent cart with an Amazon-like shopping cart.
A Middle Ground
TJ Maxx recently launched a very cool shopping cart and checkout process created in Flash. Macromedia has long shown how their technology could be used to create a shopping cart, but most retailers haven't integrated this type of functionality into their Web site's "core" (the checkout funnel), and for good reason: checkout is not the place where you want to experiment with new technologies.
TJ Maxx's shopping cart at appears like a pop-up window when you click "Add to Cart." The Flash-based pop-up window displays what was added to the cart, then gives you the option of closing the window (leaving you back at the product page), or proceeding to checkout. The checkout process is the same as every other site, but it's been condensed onto one Flash-based page. This is a huge improvement over the traditional checkout process. All the information is on one page, and the user can easily go back and forth between checkout steps (billing, shipping, credit cart info, review). Because these remain individual steps, funnel analysis is the same as with traditional sites.
The TJ Maxx site is a good example of a happy middle ground between streamlining the user experience without disabling site analytics. At the end of the day, the bottom line is the most important analysis. If one-page checkout shows a huge increase in sales, this certainly outweighs the fact a detailed funnel analysis no longer exists.
New ROI Analytics Must Emerge
Web-based analytic engines have a fundamental flaw: they show you where things happened, hoping you can figure out why things happened. If users dropped out on the "shipping information" page during checkout, it must have been the shipping price, right? Or perhaps the user didn't really want the product. After three pages of filling out purchase information, he finally realized it. Maybe it was a spontaneous purchase, and a four-step checkout process is an impulse buy buzz-kill.
An analytics package may never reveal why something happened, but one thing is certain: analytics packages are primarily page-based. As more and more sites become Web applications (through Flash, Java, etc.), Web analytics packages must offer hooks that can be embedded in these applications for reporting purposes. New reports detailing how users interact with the application interface must be developed and integrated into traditional reports.
Good news: this is happening. With the release of Flash MX, Macromedia began to mature the reporting capabilities within Flash. Web analytics vendors like Web Trends have created specific extensions for Flash applications. Both Macromedia and various Web analytic companies have published white papers on how to integrate tagging into Flash applications.
Tracking users' paths through an application provides much richer data than merely tracking page flows. Because of the richness analytic data available in a Flash-based application, the reports generated can be much more detailed than tradition analytics (including what parts of a form were filled out before the user abandoned the site).
As Web analytics prove there's a need to streamline our sites, more granular analytics must emerge. Once the site is streamlined, traditional page-view analytics may no longer be applicable. Applications such as Flash can provide a more granular look into that page, and how users interact with it. The trick will be to combine this information with traditional reports for a cohesive view of online performance, including all pages and Web applications.
Until next time. . .
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