The saying “If you can’t measure it, then you can’t manage it” definitely applies to web analytics as well. Take online coupons. If I can’t see any data about coupon usage in my web analytics reports then I won’t worry about it, let alone do any kind of optimization. But by all accounts, coupons play an important part in the marketing tactics for many online retailers.
By being able to see coupon usage in web analytics we can at least start asking some interesting questions and perhaps start uncovering some interesting nuggets.
First off, if you are giving out any kind of coupon, try to have a good estimate for the amount of visitors who have been exposed to your coupon. Email campaigns are ideal for this as you know how many email you will be sending out. If you are displaying coupons on your site, try to show coupons only to certain visitor segments by using dynamic web personalization techniques. You can also use AB testing. Once you have this number, go into your web analytics or back-end to find the number of times the coupon has been redeemed:
Now you can calculate the coupon redemption rate. In addition to knowing the number of visitors who are seeing your coupon, try to use control groups. What this means is that some visitors (the control group) should not be exposed to the coupon and you should compare their behavior – especially number of orders and order values – to the group who sees the coupon. If there is otherwise no difference between these groups you can attribute any kind of lift to the coupon.
To-do 1: Track coupon usage in web analytics.
To-do 2: Measure lift by using control groups in your campaigns.
Once we start tracking this type of data we can also start asking some related questions:
1. What is the coupon conversion rate once it has been applied?
2. What is the conversion rate of invalid coupons? If you have a coupon field on the checkout, do people who try out invalid coupons abandon their checkout?
3) Are certain visitor segments using coupons more often than others? For example, from a shopping comparison engine:
**4) What is the right type of coupon? **Percent off, dollar off, free shipping? In addition to conversion rate, pay attention to average order values and experiment with minimum order values before a coupon can be used.
These are some of the questions that you can get answers to before getting into optimization. Ideally, from a merchants perspective, you only want give a coupon to a visitor who “needs” a coupon, i.e. one who would otherwise not have placed an order. Sounds like a cliché, but you want to show the *right*** coupon or offer to the *right***** person at the *right***** time**. You also don’t want to teach all your customers to expect a coupon.
The Yahoo! Store platform offers some pretty comprehensive coupon management options. And you can really get into personalized offers by using one-off or single use coupons. And now you can track everything too!
Happy coupon analysis!