Question: what errors are your customers seeing during checkout? Standard checkout optimization has us creating funnels in our analytics packages, identifying the choke points, and A/B testing variations of poorly performing pages. But how do we decide what changes to make to the page? Where are shoppers having problems? What if we've moved to a single page checkout – how do we identify problem areas?

Capturing the Information

One way to help answer these questions is to track the validation errors that customers see by using Google Analytics' event tracking utilities. Event tracking allows us to store arbitrary information in a hierarchical format within Google Analytics, so that we can examine our data in typical Google Analytics fashion. Using a relatively simple snippet of code in our Elastic Path velocity templates, we can store our form validation errors:

#set($errorsObj = $springMacroRequestContext.getErrors("expressCheckoutFormBean"))
#if ($errorsObj.errorCount > 0)

     <script type="text/javascript">
          #if($errorsObj.globalErrorCount > 0)
               #foreach($error in $errorsObj.globalErrors)
                    _gaq.push(["_trackEvent", "Checkout Error", "$error.code", "global"]);
               #end
          #end


          #if($errorsObj.fieldErrorCount > 0)
               #foreach($error in $errorsObj.fieldErrors)
                    _gaq.push(["_trackEvent", "Checkout Error", "$error.code", "$error.field"]);
               #end
          #end
     </script>
#end

You'll need to substitute the name of your own form bean for the call to getErrors(). If you have a multi-page checkout process, you may want to use a different event tracking label for each page, rather than just Checkout Error. Note also that this code uses the newer asynchronous format of the Google Analytics tracker – if you are using the old format, call the _trackEvent function of your GA tracker object.

Analyzing the Data

Now that we have the event tracking in place, what can we learn from the data? If we navigate in Google Analytics to Content → Event Tracking → Categories → Checkout Error, we can see exactly which errors customers experienced (one thing to keep in mind: every error will be counted, so one page view can result in multiple errors being recorded). More interesting though is the Ecommerce tab, which shows us in the Transactions column whether or not customers eventually checked out:

This is over a 10 day time period. Not surprisingly, missing required fields are the most common error encountered. If we drill down into errors.required we can see exactly which required fields are tripping visitors up:

The big winner is CVV code! Fortunately only 6 of 128 people failed to eventually checkout, and it's possible that not all of those 6 were legitimate shoppers. Still, we may be able to make the checkout process smoother if we explain what CVV is and where to find it. A surprising number of people seem to have left off their credit card number as well. Potentially customers are simply missing the credit card section altogether. Now we have some ideas for A/B tests we can run.

Other problem fields seem to be email and phone number. Not too shocking; people are wary about giving these out and were perhaps hoping they weren't actually required. Maybe we should do a better job of explaining why we need this information.

Looking back at the first Checkout Error screen, the big conversion drop-offs seem to be in places we'd expect: rejected credit card authorizations, incorrect address data, asking the customer to phone in their order, and no inventory. Hmm, what's this errors.whitespace?

The validation rule is "no leading or trailing whitespace allowed", so someone probably had a space after their email address, couldn't figure out the error, and gave up. Stripping the whitespace prior to validation makes more sense and might have saved the order. From a net revenue standpoint this improvement isn't high on the list, but fixing it is 10 minutes of our time, and we can check to see if this rule applies to any other fields.

There is a great deal more information to delve into here, and over time we will build up a history that will allow us to spot new problems as they crop up. By adding a short and simple snippet of code, we've gained greater insight into our customers' behavior, and hopefully discovered some ways to increase our conversion rate and create a smoother checkout process.

David Minor works for women's sportswear retailer Team Estrogen, an Elastic Path customer.