Insights in this post come from our CRO team's decade of experience working with eCommerce brands. Written by Sumedha Gurav and Abhishek Talreja. Reviewed by Harsh Vardhan.
What if we told you that you could grow revenue without a single new visitor showing up?
That's what average revenue per user actually measures: it’s how much more you can get out of the customers already on your site, instead of paying to bring new ones in.
It's the question Convertcart's conversion team has spent a decade of experience answering for top eCommerce brands.
We have optimized websites for more than 500 eCommerce stores across the US.
Along the way, we have learned which strategies move ARPU and which ones just look good on paper.
And in this piece, we walk you through the framework we use, the eighteen tactics inside it, and five real stores where we put those tactics to work.
But before we dive into the crux of this article, let’s understand how you can calculate average revenue per user and how it’s different from other similar eCommerce metrics.
Here’s the simple formula to calculate ARPU:
ARPU = total revenue during a period ÷ unique users during that same period
Let’s say a store brought in $500,000 in revenue last quarter from 100,000 unique shoppers. That store's ARPU is $5.
To move that $5 higher, you don't necessarily need more traffic. You need the same people to buy either more or higher value products from your store.
It's easy to get confused between ARPU and a handful of related metrics; let’s understand the nuances before moving further.
Now let’s understand the connection between these metrics:
Average order value and purchase frequency are the direct, short-horizon drivers of ARPU.
But improving customer lifecycle value helps you get longer-term results for your ARPU.
Let’s understand that ARPU is not one single eCommerce metric. It works alongside many other relevant conversion metrics smart eCommerce founders track.
Through our years of working with eCommerce stores, we found that the following 4 drivers are the key to strengthening a store’s ARPU.
At this stage, it’s ideal to understand that not every store has the same problem, and so not every store needs the same fix.
You simply need to match your numbers against that table before picking a tactic.
Here’s what the final report will contain:
“The report was deep and super insightful. Can’t believe it’s free.”
Logan Christopher CEO, Empire Herbs
The most direct way to move ARPU is to get more out of a transaction a shopper already intends to make.
Volume pricing is the simplest version of this idea. Instead of a flat discount, let shoppers earn a better price by adding more to the cart.
Profit per item drops a little, but the shopper is buying more units to get there, so total revenue per user climbs regardless of the thinner margin.
Getting the thresholds right takes some judgment, and Tiered discounts in eCommerce: 5 frameworks to increase AOV without eroding margins is a useful reference if the goal is a deliberate structure rather than a guess borrowed from a competitor.
Bundling works on a related principle, though it only holds up when the products genuinely belong together, the way a phone case belongs with a phone or batteries belong with a torch.
Group items around a real need instead of a discount, and order value usually rises on its own. High-converting product bundling strategies for eCommerce has a handful of examples worth studying for the pairing logic alone.
Upselling and cross-selling follow a similar path inside the cart itself.
Offer a better version of what a shopper already wants, or something closely related to it, and keep the price gap small enough, ideally around sixty percent below whatever is already in the cart, that saying yes requires almost no thought.
eCommerce product recommendation: examples, ideas, do's/don'ts and The high-converting cart page: learn from 29 real world examples both dig deeper into what makes those suggestions land.
Three smaller levers round out order value, and they all lean on the same psychological trick: make the bigger cart feel like the easy choice.
None of this matters much if a shopper can't tell why the product is worth buying in the first place.
A short, scannable list of benefits sitting just below the buy button, icons rather than paragraphs, makes it easier to justify adding a few extra items instead of just the one someone came for.
It's a small addition to a page, but it's often the difference between a shopper who adds one thing and a shopper who adds three.
Getting an existing customer to buy again is almost always cheaper than finding a new one, though it rarely happens without a nudge.
A coupon on the thank-you page, reinforced by an email a few days later, takes advantage of a shopper's buying momentum instead of waiting for them to think of the brand again unprompted.
Subscriptions push the same idea further by making the repeat purchase the default rather than a decision a customer has to remake every time.
Put the subscription option next to the one-time purchase option, attach a clear discount to it, and recurring revenue stops being the exception.
Loyalty programs work through a different kind of pull. Give a shopper a visible goal, spend a hundred dollars and unlock a thousand points plus a free product, and show them exactly how close they already are.
That sense of nearly arriving somewhere brings people back faster than the reward itself does.
Two more channels round out this lever, and both work between purchases rather than at the moment of one:
Holidays and back-to-school season do something similar at scale, giving a store a built-in reason to re-engage its list on a predictable schedule instead of leaving repeat visits to chance.
Lifetime value compounds in a way a single order never can, and the clearest way to move it is relevance.
Recommendations built from past purchases, browsing behavior, or what similar shoppers bought, placed on category pages, product pages, and sparingly in the cart, turn a single purchase into an ongoing relationship without asking a shopper to do any extra work.
The effect takes longer to show up than something like a bundle or a discount, but it's usually the most durable improvement a store can make to this number.
There's a second, less obvious version of the same idea: recommending something for someone other than the shopper.
Suggesting a product for a partner, a child, or a dog taps into a motivation that has nothing to do with personal need, and it multiplies the reasons a customer has to keep coming back to the same store.
51 marketing ideas for online pet stores (with examples) leans on this constantly, and the loved one in question usually has four legs.
A new visitor carries no history, which means a store gets exactly one shot at making that first visit worth something.
Limited-edition products tied to a season or a moment give a first-time shopper a reason to act now instead of filing the idea under maybe, which is usually the same as filing it under never.
Featuring what's new at the top of the homepage works on a related principle, catching first-time visitors who have nothing else anchoring their impression of the brand.
The same logic applies on the returning-customer side too, and 26 brilliant ways to boost eCommerce repeat sales covers that half of the equation.
Urgency closes the gap for shoppers still on the fence. Flash sales and countdown clocks work especially well on new visitors, since they have no particular reason yet to assume the brand, or the deal in front of them, will still be there next week.
That is the framework this piece has been building toward.
It sits inside a broader approach to conversion covered in How to increase eCommerce conversion rate: a 3-tier framework to stop guessing, if you want the bigger picture.
Let’s now take you behind the scenes of how we helped some stores improve their average revenue per user.
Hardwood Lumber's product pages were trying to do far too much at once. There were specs, filters, cross-sells, and trust badges on the same small patch of screen.
This led shoppers to wander off before they ever reached the add-to-cart button. We stripped the page back to whatever mattered at each stage of the decision.
We then layered in product recommendations for the shoppers who were ready to see more. The leaner layout pushed revenue per user up 22X.
And when we added the recommendations on top, revenue per visitor climbed another 3.7X.
Finally, there were fewer distractions and more finished purchases and more revenue from every person who showed up.
You can read the original case study here: How Convertcart helped Hardwood Lumber enhance user experience and boost revenue.
For 4over4, the opportunity was sitting in the cart, where shoppers kept checking out with fewer purchases.
So, we tested smarter bundling and cross-sells at the point where someone was committed to buying, but not committed to buying quite enough.
This helped us raise the basket size by 30.1 percent, and overall revenue by 28.7 percent.
You can read the original case study here: We helped 4OVER4 increase overall revenue by 28.7% through continuous CRO.
The challenge for Sebastian Cruz Couture had nothing to do with the first visit. Our goal was to get hoppers to keep coming back for more.
So, we leaned on product recommendations that felt personal. We surfaced them at the moments shoppers were most likely to act.
The results were great. Lifetime value rose 127.63 percent, average order value climbed 12.86 percent, and conversion rate jumped 162 percent.
All this happened from the same recommendation engine.
You can read the original case study: We helped Sebastian Cruz Couture increase customer lifetime value by 127.63%.
Now, GetFPV was a store that already had loyal customers. But their customer weren't ordering as often as they could have.
So, we tested FOMO driven messaging around limited stock. We also added a sticky add-to-cart bar that kept a second purchase one tap away instead of a long scroll back up the page.
And here’s what happened: Repeat orders rose 20 percent, and it also added up to 3.4 million dollars in new revenue across 36,068 transactions.
You can read the original case study: We helped GetFPV generate $3.4 million in additional revenue.
For NewAir, the challenge was a lack of history to build on. So our focus went entirely to that first visit. We made sure the right products showed up fast enough.
This way, the revenue from new users doubled. It's the thinnest data point among the five stores here, but it rounds out the framework nicely.
Average revenue per user isn't only about existing customers spending more. Sometimes it’s about making sure the first visit already counts for something.
You can read the original case study: We helped NewAir increase revenue per visitor by 3.6X.
Here’s what the final report will contain:
“The report was deep and super insightful. Can’t believe it’s free.”
Logan Christopher CEO, Empire Herbs
Average revenue per user went up for five different brands for five genuinely different reasons.
Every one of those reasons traces back to the same four levers: order value, purchase frequency, lifetime value, and new user monetization.
None of it needed more traffic. It needed more value out of the traffic already showing up.
That's why the whole idea to treat ARPU as a serious metric when you're trying to scale an eCommerce business without scaling ad spend at the same pace.
If you are trying to improve your own ARPU, the honest answer is that it depends on which of these four levers you actually need to pull.
You increase ARPU by pulling one of four levers: raising order value, increasing how often shoppers buy, extending how long they stay customers, or converting new visitors faster on their first visit.
Most stores find the fastest early win in order value, through bundling, cross-sells, and thresholds like free shipping or a free gift.
You improve ARPU by getting more revenue out of the visitors already on your site instead of paying for more of them.
Personalized recommendations, subscriptions, and a cleaner product page all raise revenue per visitor without touching the acquisition budget.
Revenue per visitor usually rises fastest when friction comes out of the product page and checkout flow, since every extra click is a chance for a visitor to leave before buying.
Hardwood Lumber saw revenue per visitor climb 3.7X once product recommendations were added to a simplified page.
Average purchase revenue per user, more commonly shortened to ARPU, is total revenue divided by the number of users over a given period.
Whether you call it average revenue per user or average purchase revenue per user, it's the same metric, used across eCommerce, subscription, and app businesses to track how much value each user generates.
In eCommerce, ARPU measures how much revenue each shopper generates on average, whether they buy once or return repeatedly.
Average order value only looks at a single transaction. ARPU captures a shopper's total contribution over time instead.
Order value tactics like bundling and cross-selling tend to move ARPU fastest, since they don't need any additional traffic to work.
Personalized recommendations and subscriptions take longer to show results, but they produce the most durable gains, because they compound over a customer's lifetime instead of a single order.
Increasing ARPU lets a store grow revenue without a proportional increase in acquisition spend.
A store that doubles its ARPU effectively doubles the return on every visitor it already earns, and that's usually cheaper than doubling traffic itself.
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