The topic of my last column was tools and strategies for measuring site usage. One of the most useful traffic-based metrics is conversion ratios, which you can take advantage of if you have some type of traffic measurement capability in place.
What Is a Conversion Ratio?
Because the term is used in several different ways, it's important to define it right off the bat. I'm going to use a fairly broad definition that highlights the usefulness of the conversion ratio as an all-purpose tool for measuring the effectiveness of various campaign types.
A conversion ratio is the number of times a desired action is taken, presented as a proportion of the number of opportunities for the action to be taken.
That definition is a mouthful. Why so complicated?
Two reasons. First thinking of conversion ratios this way will guide you toward using them correctly. And second this definition is general enough to apply to many different marketing scenarios. Conversion ratios can help measure the following:
Finding the Right Ratio
Let's revisit the buyer-to-browser ratio, which I briefly mentioned in my previous column. This metric aims at the first bullet point above: how well your Web site induces users to spend.
At a small-ticket retail site where frequent purchases are the norm, every visit to the site represents a potential sale. Therefore, the appropriate conversion ratio would be the number of purchases as a proportion of the number of visits (as opposed to a metric based on visitors). A campaign that induces a moderate-sized segment of users to buy multiple times may be much more valuable than one that induces a large segment of users to buy only once! All this, of course, ignores the actual value of purchases, which you would need to take into account for a complete analysis.
For large-ticket items (e.g., automobiles -- an extreme example) it would be unusual for a single user to make multiple purchases within a short time. So, for this case, each site visit can't be considered an opportunity to make a sale, and the buyer-to-browser ratio should be calculated using visitors rather than visits. This simple line of reasoning can guide you through all the variations of the conversion metric.
Using Conversion Ratios to Tune Your Site
Conversion ratios can be used to inform decisions about your Web site in at least two important ways: specific elements and global features.
First let's look at a specific site element, such as a link. You have several candidate links in mind and want to know which one is most attractive to users. The conversion ratio would be the number of users who clicked on the link as a proportion of the number of users who saw it. (Why is the user the right unit of traffic here? Once a user has seen the content behind a link, it is probably the content itself rather than the link that is inspiring the user to follow the link). Now you can try out several candidate links over a period of time and observe which one produces the best results.
Using conversion ratios to test global site features is often when the real value kicks in -- sometimes common sense or intuition about site design turns out to be wrong when viewed through the lens of conversion ratios. For example, suppose your Web site offers a service to users, and your desired action is a user sign-up. You may find some surprises when you measure the success of your site design using the sign-up to visitor ratio. Detailed corporate information and other fairly standard content may be a disadvantage because they provide more opportunities for users to become distracted and get off track. In this example, a site design that "pushes" users to the sign-up page may be more effective than one that allows more flexible navigation.
My aim is not to tell you how to design your Web site: Those matters clearly need to be decided case by case. But conversion ratios can supply you with a valuable metric to make decisions based on measurable outcomes instead of gut feelings or conventional wisdom.
I hope I have converted you to my point of view...
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Michael Hochster received his Ph.D. in statistics from Stanford University and a B.A. in mathematics with high distinction from the University of California at Berkeley, where he was elected to Phi Beta Kappa in his junior year.
Before joining cPulse, Michael worked as an applied statistician in the drug discovery group at Schering-Plough Research Institute. He has taught graduate-level courses in theoretical and applied statistics at Stanford University and The State University of New Jersey at Rutgers.
March 19, 2014