The Challenge

Most challenges you will face when optimizing dynamic checkouts are rooted in data. Bad data can cause you to misinterpret, misreport, and miss what’s really going on. As an example, when taking a high level look at your checkout conversion rate, you’ll probably create a report that measures drop off in each step of your checkout. Chances are that there is a problem already, because most people ignore the fact that not all users move through a purchase path the same way.

How would users move through a checkout path differently? Any time a user has the chance to skip a step or a page, there is a potential for anlaytics data to misrepresent that user’s actions. The most common cause of this would be a quick checkout feature, but also could be due to purchasing different product types, gift options, alternate payment methods… etc.

On most sites, returning and new users experience different paths through the same checkout.

Reporting by Segments

The solution to the challenge of reporting on dynamic checkouts is to have multiple stats. Your site conversion rate is an important number, but probably not as important as the conversion rates of your top marketing channels. When analyzing what’s really happening, you dig into the the numbers for search, feeds, etc. Doing the same with your checkout conversion rate will allow you to diagnose what’s really going on and where to focus your efforts.

Getting Started

1. Define and map out all paths through or branches in your checkout process.
2. Focus on the paths that are most used, but don’t ignore the ones that aren’t.
3. Setup reports via your analytics platform to track each path separately.

Now, when asked about the checkout conversion or shopping cart abandonment rate, you’ll be able to communicate where the opportunity really is.