Conversion Rate, Average Order Value, and Revenue Per Visitor
Analyzing, predicting, and influencing consumer behavior is a critical part of all successful eCommerce operations. Sellers often struggle, however, to understand and control outcomes as changes intended to improve a core variable – such as conversion rate or average order value – often trigger unexpected declines elsewhere. In this article, learn more about the interplay between conversion rate, average order value, and revenue per visitor as we address the following guiding questions:
What is the relationship between conversion rate, average order value, and revenue per visitor?
What factors influence conversion rate and average order value?
How do you effectively research and experiment with each variable to maximize store profitability?
Conversion Rate (CR): the percentage of website visitors who make a purchase
Average Order Value (AOV): the average amount of money a customer spends when he or she places an order
Revenue Per Visitor (RPV): the average amount of revenue generated from each website visitor
The Relationship:CR x AOV = RPV
A store’s conversion rate (CR) multiplied by the average order value (AOV) yields the revenue per visitor (RPV): CR x AOV = RPV. It’s a disarmingly simple formula in its implications: increase either the conversion rate and/or the average order value and the revenue per visitor will increase – as will, ceteris paribus, the profitability of the store! But, is it really so easy? Unfortunately, no – in fact, it is quite common for tweaks designed to effect desired changes in one variable or another to trigger adverse changes elsewhere.
What Factors Influence Conversion Rate and Average Order Value?
Conversion rate and average order value are influenced by a number of core factors including:
Each of these factors is discussed in depth below.
CR: Inverse relationship: if price increases, CR tends to decrease; if price decreases, CR tends to increase.
Example: Less expensive items often yield a higher conversion rate and more expensive items often yield a lower conversion rate.
AOV: Direct relationship: if price increases, AOV should increase; if price decreases, AOV should decrease.
Example: If the items in a store are more expensive, the AOV should go up, and vice versa.
Discussion: Price is a fickle variable – any changes businesses make are likely to impact both CR and AOV in materially different ways. For example, a price increase should lead to an increase in AOV, but a decrease in CR. Is such a change going to be good for your business? It’s hard to say – and it is likely to require a lot of careful experimentation.
CR: Direct relationship: if value increases, CR tends to increase; if value decreases, CR tends to decrease.
Example: If customers perceive greater value from a deal or offer, they are more likely to convert. Bundling products into useful, discounted collections, for instance, can help customers to perceive greater value – which, in turn, should increase CR.
AOV: Direct relationship; if value increases, AOV should increase; if value decreases, AOV should decrease.
Example: Strategies like targeted upselling and cross-selling (gift wrapping, customization, etc.) which increase perceived value should increase AOV.
Discussion: The impact of value on CR and AOV is straight-forward on the surface: by offering more value, both CR and AOV should increase. There is, however, a natural limit — taken to the extreme, maximizing value would require giving everything away for free, which clearly wouldn’t be a good idea. Additionally, the long-run implications of aggressive deals and offers can be quite limiting as customers can easily become conditioned to wait for similar deals before purchasing again in the future.
CR: Direct relationship: when urgency increases, CR tends to increase; when urgency decreases, CR tends to decrease.
Example: When a company leverages the power of urgency and scarcity in their marketing (whether on the front-end of the sales process, with high-end merchandise drops, or on the back-end, with closeouts and sales), customers tend to be more likely to convert.
AOV: Direct relationship: when urgency increases, AOV tends to increase; when urgency decreases, AOV tends to decrease.
Example: Urgency and scarcity encourage customers to make significant purchases now – if customers aren’t going to be able to get the same deal tomorrow, they are much more likely to not only buy immediately, but also to buy more.
Discussion: Urgency and scarcity frequently work together to drive both CR and AOV upwards; however, these tactics come with their own challenges in the longer term about which business owners should know. As a rule of thumb, urgency and scarcity must be deployed with great care.
CR: Direct relationship: if the buying experience improves, CR should increase; if the buying experience degrades, CR should decrease.
Example: Having a professional storefront, clearly displaying products, and using functions like one-click ordering should make it easier to convert a prospect into a customer.
AOV: Direct relationship: if the buying experience improves, AOV should increase; if the buying experiences degrades, AOV should decrease.
Example: Consistency throughout the sales funnel and seamless transactions should increase average order value.
Discussion: This is largely self-evident – improving the buying experience encourages your customers to convert more frequently and to buy more on average.
CR: Direct relationship: building trust should increase CR while an erosion of trust should decrease CR.
Example: Businesses may signal trustworthiness through high-quality websites, the inclusion of customer reviews and social proof, a consistent buying experience at all stages of interaction, and the perception of quick order turnaround times – all of which should make a website visitor more likely to execute a purchase.
AOV: Direct relationship: building trust should increase AOV while an erosion of trust should decrease AOV.
Example: Again, businesses may signal trustworthiness through high-quality websites, the inclusion of customer reviews and social proof, a consistent buying experience at all stages of interaction, and the perception of quick order turnaround times – all of which should make a website visitor not only more likely to execute a purchase, but also more likely to spend more.
Discussion: In large part due to the sensory limitations inherent to eCommerce, customers have trust issues when it comes to online shopping. By investing heavily into the quality of your brand assets, you are sending a signal to the marketplace that you are willing and able to make good on your promises (as consistent failure to do so will render your brand investments less valuable) – which is a core building block of trust.
CR: The relationship varies.
Example: High-quality traffic and low-quality traffic impact CR differently. If traffic is being generated by email campaigns that are directed solely to engaged customers, for instance, then conversion is likely to be pretty high (as long as the company is offering new products, new deals, etc.) If traffic is coming off of fresh pay-per-click (PPC) campaigns which are hitting people with no prior brand experience, however, then conversion is likely to be lower.
AOV: The relationship varies.
Example: Again, much depends on the quality of the traffic being generated: traffic from email campaigns to existing customers, for instance, will likely yield higher average order values than traffic from cold PPC campaigns.
Discussion: Traffic is a complex concept and depends a great deal on quality, segmentation, and other related factors. Keep in mind the 80/20 rule – the tendency for a small subset of customers to drive an overwhelming proportion of revenue.
CR: Inverse relationship: when shipping costs increase, conversion tends to decrease; when shipping costs decrease, conversion tends to increase.
Example: If a business offers free shipping without any minimum order threshold, conversion should go up; if the threshold is increased, conversion should drop.
AOV: The relationship varies.
Example: When companies offer free shipping for all orders (as opposed to setting a threshold at a higher amount of spend), AOV typically decreases; however, as the threshold is increased, the AOV tends to rise as consumers are incentivized to spend more in order to get free shipping. If the threshold is moved too far beyond the typical average order value though, it tends to lose its effectiveness and AOV is likely to drop.
Discussion: The interplay between shipping costs, CR, and AOV is nuanced. While increasing shipping costs may make customers think twice before executing a purchase, it may increase AOV as long as thresholds for free shipping are thoughtfully set. Similarly, though free shipping might seem attractive due to its standard effect on CR, the adverse impact of free shipping on AOV could more than offset any potential benefits to be gained.
Cutting through the Noise: Maximizing RPV by Improving CR and AOV
Sellers looking to maximize RPV would do well to first experiment with the following low-risk changes:
Improve website quality. While investing in a good website can be expensive, the rewards are often outsized. Improving the copy, creative, and usability of a website is likely to both improve the buying experience and heighten trust – with the end result being an increase in both CR and AOV.
Add social proof and other customer-created content to your sales funnel. Adding positive reviews, ratings, and other customer-generated content as social proof has few obvious downsides. It creates trust and should increase both a customer’s willingness to spend and the overall amount that he or she is willing to pay: raising both CR and AOV. One caveat is that the inclusion of insufficient social proof – such as a low number of product reviews – betrays a seller’s size.
Bundle related items at a discount. Bundling is a useful tool for increasing AOV without hampering CR – especially for customers who are already interested in and/or using a brand’s products. It also has the added benefit of being a great way to profitably reduce inventory levels of less successful products (by bundling them with things that customers want).
Target customers with upselling. Offering useful, trustworthy upselling and/or cross-selling options like customization, gift wrapping, discounts on related products, and expedited shipping helps drive AOV for customers who are already in the funnel (without hampering CR).
Employ urgency with care. If a business is able to generate a sense of urgency or otherwise leverage scarcity, customers generally respond – with both CR and AOV rising as a consequence. Urgency can be employed in a variety of places: ad copy, email copy, website banners, etc. Be careful, though – relying too much on urgency and scarcity can jeopardize trust in a company’s brand and/or cause customers to become conditioned to wait for sales.
Experimenting with the following factors may also prove beneficial, but the nuanced – and often disparate – ways in which CR and AOV respond to them increases the risk:
Shipping thresholds. The relationship between shipping, CR, and AOV is complex and depends in large part of whether or not a brand chooses to offer free shipping for all orders or requires a minimum purchase amount to unlock free shipping. Of course, free shipping on all orders usually boosts CR; however, it erodes AOV. Higher thresholds for free shipping, on the other hand, often increase AOV, but erode CR. Optimization, therefore, requires carefully orchestrated testing.
Price. Higher-priced items often decrease CR and increase AOV. Many businesses, however, are able to build comprehensive catalogues of products – some of which appeal to the higher-end buyer and some of which appeal to the lower-end buyer – in an attempt to enjoy the best of both worlds.
Value. Offering really good deals – via deep discounts, extreme urgency, etc. – can be a great way to generate results in the short-run; however, in the long-run, customers can easily become conditioned to wait for the same type of deal to come around again before reconverting. Once earned, the deep discount mantra is a difficult one to shake indeed.
A Few Thoughts on Experimentation
When testing CR and AOV, sellers should carefully design and execute A/B (split) tests. This topic is well beyond the scope of this article; however, there are a few things to keep in mind:
Execution. When executing an A/B test, be sure to change only one variable at a time. This requires careful experimental design and rigid controls.
Discipline. Allow each change to run for an adequate period of time to accommodate for uncontrollable forces (algorithm changes, day of the week, etc.)
Unknowns. Correlation and causation can be difficult to disentangle. What appears to be a material relationship between some independent variable and either CR or AOV could actually be the result of some other unidentified force(s).
Nothing about eCommerce is really all that complicated; however, there is a lot of nuance which should be recognized, analyzed, and understood. Though you can learn a lot from others, nothing can replace nonstop experimentation.