There are literally hundreds of marketing metrics to choose from, and almost all of them measure something of value. The main metric that will help you achieve revenue growth to your e-Commerce website is Revenue Per Visit (RPV).
- Site metrics interact with each other
- Customer interaction can be either positive or negative
- Revenue Per Visit is a composite index influenced by conversion rate and average order value
Increasingly, CEOs and CFOs do not pay attention to about 99% of marketing metrics. They are focusing more on the areas of primary concern such as: revenue, margin, profit, cash flow, ROI, shareholder value – in other words, your company’s ability to generate more profit and faster growth than your competitors.
Revenue per visit (RPV) is one of the key financial performance metrics of your e-Commerce site, and one of the primary objectives in any revenue performance optimization strategy. This composite metric combines conversion rate and average order value into an actionable data point. It measures the money a website makes every time a customer enters your ecommerce store.
e-Commerce professionals often think that Conversion Rate or Average Order Value are the best metrics to use for revenue generation. Unfortunately, RPV is poorly understood and rarely used as a metric. You may be surprised that using RPV can help increase revenue significantly on your e-Commerce site!
Conversion Rate (CR)
If your goal is to generate more revenue on your e-Commerce site it is very logical to think that increasing number of conversions (i.e. visitors who buy product on your site) will result in revenue growth.
In e-Commerce marketing, the global conversion rate is the proportion of unique visitors that converted (i.e. made a purchase on the site). Micro conversions are defined as proportions of unique visitors that performed a desirable action on the e-Commerce site. For example, a micro conversion can be a proportion of unique visitors that selected any product on the site. They did not make a purchase yet, but by selecting a product they moved one step further in the site’s sales funnel. Mathematically speaking, the conversion rate (CR) can be expressed as:
The problem is that the measures taken to increase conversion rate can backfire and produce lower overall revenues.
Here is how. Your overall e-Commerce revenue is a function of the total number of sales (CONVERSIONS) and Average Order Value (AOV).
Mathematically speaking, Revenue (R) is represented by the formula below:
As shown in the picture below the amount of revenue is proportional to the area between number of CONVERSIONS and AOV.
By increasing your CR, you could have negatively impacted AOV which will lower overall revenue:
Increase in CR might produce more visitors who will buy lower priced items, which will ultimately hurt overall sales.
Average Order Value (AOV)
Some companies think that the key for their revenue growth is to take measures to increase the average order value (AOV). That is why product recommendation solution are so widely in use.
Average Order Value (AOV), or as it is sometimes referred to as an average ticket, is a metric representing the value of an average order within a period of time. It is simply calculated by dividing Revenue by Number of Conversions (Orders) in a specific Period of Time, as follows:
Similar to an increase in conversion rate, there are no guarantees that a lift in AOV will translate into a proportional increase in revenue:
This approach may stimulate sale of higher priced items, but the number of people who will make a purchase might go down, resulting in a decrease of your overall sales.
Revenue per Visitor (RPV)
Revenue Per Visitor is a composite metric that combines Conversion Rate and Average Order Value into a single number.
Revenue Per Visitor (RPV) is a metric representing the value of revenue per visitor within a period of time. It is calculated by dividing Revenue by Number of Visitors in a specific Period of Time, as follows:
It represents an interaction between Conversion Rate and Average Order Value, and it is the most reliable predictor of e-Commerce revenue.
Visitors to an e-Commerce site are the common denominator of e-Commerce activity. The demand generation cost is measured per visitor terms, therefore it makes sense to divide overall revenue by the number of visitors:
Which produces the following result:
Mathematically speaking, revenue per visit (RPV) equates to a multiple between conversion rate (CR) and average order value (AOV). This proves that RPV is a composite metric that encompasses the impact of two key revenue performance related metrics: CR and AOV.
RPV and Optimization for Revenue Growth
When optimizing e-Commerce sites for revenue growth, most companies are focused on the conversion rate. They are under the impression that the AOV is a fairly stable number that moves in proportion to conversion rate:
The picture above shows that +17.92 lift in conversion rate has also boost AOV and RPV which in return produced the overall revenue growth.
The real life situation is much more complicated. The interaction between CR and AOV can often be negative. One can be successful in raising CR but still lose money.
In the example below, a client got a +10.23% lift in CR which negatively impacted AOV and produced a drop in overall revenue.
To solve this optimization metric conundrum, e-Commerce companies should use RPV as the primary optimization metric as a way to optimize of the basis of both metrics (CR and AOV) at the same time. The example below shows how use of thr RPV metric has ensured overall revenue growth, even though AOV dropped during the time interval.
This blog post was inspired by our recent conversation with a prospect who wanted to optimize his e-Commerce checkout funnel. He was attracted to our real-time optimization methodology, but did not understand why we recommended RPV as the primary optimization metric.
After a lengthy explanation about RPV metrics, he said that he could see the value of using RPV for optimization of the general e-Commerce pages of his site, but not for the checkout funnel. His argument was that the best metric for the checkout funnel is CR since the products are already selected, and our optimization campaign will not be able to increase or decrease the number of products (and associated value) in the cart. He assumed that more conversions should mean more sales.
We had to bring to his attention the fact that not all visitors select the same number of products, and that the value of the products placed in the cart can vary significantly. The optimization campaign will attempt to increase the checkout funnel throughout. If the optimization goal is to increase CR (number of purchases), then it is possible to achieve an optimal user experience that will deliver more visitors whose order value is smaller, and as result produce a lift in CR and loss in revenue.