Most marketers track and analyze a variety of metrics when it comes to their digital marketing efforts, especially for e-commerce. Some of the metrics are largely useless, others are very interrelated, and maybe only a few are the critical KPIs. Here, we’ll examine the most important metric of them all when assessing your e-commerce website. Specific to digital marketing and e-commerce, I’ll argue that the most important (and often most misunderstood) metric is Revenue Per Visitor, or RPV.
Marketers know to pay attention to Conversion Rate (CR or eCR) and Average Order Value (AOV). But many don’t realize that RPV is a composite metric comprised of these two that is an actionable data point in optimizing revenue performance. As the name suggests, RPV measures the amount of money a website makes for every visitor.
Let’s compare these three intertwined metrics to investigate why RPV is superior to the other two.
Situation 1: Focus on Conversion Rate
If we define a completed checkout/order as a conversion, then Conversion Rate (CR) is simply:
CR = Orders/Unique Visitors
For example, if 10,000 people visited your site last month and you had 100 orders placed, your Conversion Rate was 1%. If the number of visitors stays relatively constant, you can increase revenue by increasing the proportion of visitors who convert, thereby improving revenue performance while cost remains unchanged. This brings you more revenue for each marketing dollar spent, regardless of the channel (SEO, PPC, email, social media, etc.).
But what if your conversion rate rises for a lower-priced product you carry and simultaneously drops for a higher-priced product. Specifically, let’s say last month you got 900 orders for a $1 product and 100 orders for a $100 product. This month, you got 950 orders for the $1 product and 90 orders for the $100 product. Conversions increased by 4% (from 1,000 to 1,040). Specifically, your conversion rate for the aforementioned 10,000 visitors has improved from 1% to 1.4%. But revenue dropped by 9% (from $10,900 to $9,950).
Clearly, there’s more to the story.
Situation 2: Focus on Average Order Value
Average Order Value (AOV) is exactly what the name implies:
AOV = Revenue/Orders
In Situation 1, Average Order Value was the blind spot. For the first month’s $10,900 in revenue, the AOV was $10.90. For the second month, AOV dropped to $9.57 since visitors bought slightly more of the $1 product and less of the $100 product, resulting in the overall decrease in revenue.
Comparing AOV to your average cost per order, you can look at average profit per order. By keeping cost consistent and increasing AOV, you stand to gain a pure increase in profit per order.
But what if you successfully increase your Average Order Value by offering a minimum purchase discount, but fewer visitors convert as a result, leading to a drop in revenue? In this situation, Conversion Rate would be the blind spot when tracking AOV in isolation, as CR would drop with fewer visitors making a purchase.
Situation 3: Focus on Revenue Per Visitor and Eliminate Blind Spots
RPV is simple yet often misunderstood. It tells you how much revenue each unique visitor is contributing to your website.
RPV = Revenue/Unique Visitors
What makes it so powerful? To see that clearly, let’s break down the metric into its individual components.
We can rewrite Revenue as:
Revenue = AOV x Conversions
So, we can rewrite the above RPV equation as:
RPV = (AOV x Conversions)/Unique Visitors
Since (Conversions/Visitors) = Conversion Rate, we’re left with this result after some mathematical hand waving:
RPV = AOV x CR
We know revenue is king for any e-commerce business. And we know you need traffic to get revenue. Once you get traffic, theoretically holding it constant, we know you increase revenue by either increasing Conversion Rate or Average Order Value.
This is what makes the composite RPV metric so powerful — it encompasses AOV and CR in a single trackable data point, and eliminates the aforementioned blind spots. If RPV drops, we know that it could be due to an increase in unqualified visitors with less buying intent. You can identify this traffic by segmenting inbound channels. It could also mean customers are simply spending less in their cart, or are preferring lower-priced items to higher-priced ones, causing a drop in AOV. Segment your product performance to identify and investigate this trend.
I would argue that Situation 1 above is what most website owners find themselves in. They believe Average Order Value is a relatively stable variable dictated by their niche and target audience, and that they can only significantly influence Conversion Rate. Furthermore, I would suggest there’s a strong positive correlation between catalog size (number of SKUs) and AOV volatility (in terms of standard deviation from a non-negative “mean” value), making this line of thinking particularly problematic for larger e-commerce stores, especially when there exists a wide range of prices for products.
A few caveats …
To maintain the fundamental integrity of the RPV metric, we need to ensure a couple things:
- Use Unique Visitors, not Total Visitors — Each individual must count as one visitor. This is because the vast majority of first-time visitors to a website do not make a purchase. They usually want to shop around, research information and/or compare prices. Thus, using Total Visitors can ramp up the denominator on the RPV calculation, negatively skewing it and increasing its volatility.
- Segment your channels — Without strong analytics in place for your e-commerce site, tracking and improving the aforementioned metrics will be close to impossible. I’d argue the most important step in that process is to make sure you’re properly segmenting your traffic channels so that you’re able to pinpoint one that may be significantly influencing something.
How Can I Improve RPV?
Use the following tactics to improve RPV:
- A/B testing
- Free shipping thresholds
- Minimum-purchase discounts
- Volume discounts
- Abandoned-cart emails
- Reward/loyalty programs
- Live chat
- Conversion Rate Optimization (CRO)
- Usability testing and User Experience (UX) optimization
As you can see, this famous alphabet-soup metric debacle can easily be solved by focusing heavily on RPV and by understanding its underlying components, through which you can increase revenue in the long term.