Originally posted February 8 on academy.b2xpartners.com
Visits x Conversion Rate x Average Order Value = Revenue
I promise this is the only math you need to know to manage your eCommerce website. Let’s look at some quick definitions:
- Visits. The number of times people, or visitors, come to your website.
- Conversion Rate. The percentage of web visits that lead to a transaction.
- Average Order Value. The average shopping cart value across all transactions.
- Revenue. The money your website brings in from selling services and goods.
A new idea is always better with an example:
| Visits | x Conversion Rate | x Average Order Value | = Revenue | |
|---|---|---|---|---|
| Ex 1. | 163,052 | 4.07% | $1,016 | $6.75mm |
Go ahead, use your calculator to check the equation. Other than a small rounding error, it’s pretty doggone close.
So why is this important? Because if you can positively affect just one of the variables on the left, you will increase your revenue.
Let’s think of some other examples that affect each of the variables and see how it then affects revenue:
Ex 2. You start AdWords campaigns to bid on keywords for products you sell on your website yielding a 10% increase in website traffic:
| Visits | x Conversion Rate | x Average Order Value | = Revenue | |
|---|---|---|---|---|
| Ex 2. | 179,357 | 4.07% | $1,016 | $7.42mm |
Boom! You just increased revenue by $670k.
Ex 3. You hire a consultant to perform conversion rate optimization on your checkout steps and see a 0.5% increase in conversion rate:
| Visits | x Conversion Rate | x Average Order Value | = Revenue | |
|---|---|---|---|---|
| Ex 3. | 179,357 | 4.57% | $1,016 | $8.33mm |
How about another increase in revenue of $910k?
Ex 4. You implement a product recommendation engine on your website resulting in a 30% lift in your average order value:
| Visits | x Conversion Rate | x Average Order Value | = Revenue | |
|---|---|---|---|---|
| Ex 4. | 179,357 | 4.57% | $1,321 | $10.83mm |
That’s more than a significant increase of $2.5mm, and an overall increase in revenue of $4.1mm by compounding three changes that affect each of the variables.
Obviously these examples are academic, and the numbers aren’t as clean as portrayed above – for example, if you increase the number of unqualified visitors to your website then you are bound to also increase the bounce rate which in turn decreases your conversion rate – but you should be able to see the value of focusing your team on just three variables to increase your revenue.