Beyond Upsells: 7 AOV Opportunities Shopify Brands Often Overlook

When an ecommerce team wants to increase Average Order Value, the usual ideas appear quickly: add an upsell, introduce a bundle, set a free shipping threshold or recommend another product in the cart.

None of those ideas are inherently wrong. The problem comes when increasing Average Order Value becomes synonymous with adding more offers.

The better question is:

What would make it genuinely easier or more valuable for this customer to add another product, buy a larger quantity or choose the higher-value option?

In our Shopify CRO work at Blend Commerce, the answer is often found much earlier in the buying journey than brands expect. It may be in how products are merchandised, how different sizes are compared, where relevant recommendations appear or whether the customer feels confident enough to complete a larger purchase.

AOV should therefore be treated as part of the wider commercial picture, rather than a metric to optimise in isolation.

Here are seven opportunities we regularly think established Shopify brands should examine more closely.

1. Treat free shipping thresholds as a merchandising decision

A free shipping threshold should not simply be a round number that feels commercially convenient.

Start with the basket itself.

What is your current AOV? What do your most common orders contain? What are the natural next products a customer might buy? How much additional spend would typically be required to reach the threshold?

A customer sitting at £42 is much more likely to respond positively to a £50 threshold if there is an obvious, relevant £8–£12 addition than if the next sensible product costs £30.

That makes threshold setting partly a merchandising exercise. You are designing an achievable next purchase, not just putting a target above the cart.

The same thinking applies to visibility. If free delivery is available but shoppers only discover the threshold late in the journey, the incentive has little opportunity to influence what they buy.

A free shipping progress bar can make the gap visible. But the technology is the implementation layer. The commercial decision is still where the threshold sits, which products can realistically close the gap and whether the offer makes sense against your margins.

That threshold is something worth testing rather than assuming.

2. Make the next product obvious

Good cross-selling is less about how many recommendations you can display and more about whether the recommendation makes sense.

If somebody is buying the core product, what are they most likely to need next?

That could be an accessory, refill, compatible product, second flavour, replacement part or another item needed to complete a routine.

This sounds simple, but recommendation logic is often treated as a widget decision rather than a merchandising decision.

In one Stone Creek Coffee experiment, we kept the number of PDP recommendations, their design and their position consistent, and changed the recommendation logic being used. Conversion increased 23%, Revenue per Visitor increased 25% and AOV increased 2%.

The test ran for four days across 3,452 visitors and ended earlier than originally planned, so the result should be interpreted with that limitation. Even so, it provided useful evidence that which products were being recommended mattered, rather than simply whether a recommendation block existed.

That is the principle we would take into any Frequently Bought Together or cross-sell strategy.

Start with relevance. Then test placement, presentation and quantity.

3. Look at the PDP before blaming the cart

Many AOV conversations begin in the cart.

By that point, an important part of the decision has already happened.

Product pages influence whether somebody chooses a single item or a multipack, a smaller or larger size, a one-off purchase or subscription, a base product or higher-value variant.

If those choices are difficult to compare, the cart cannot fix the decision afterwards.

We saw this with Jackson's. Two pack formats shared the same headline price, but contained different quantities by weight. Customers effectively had to calculate which represented better value while also considering pack format and purchase type.

We tested adding a consistent price-per-ounce message close to the Add to Cart controls.

Subscription orders per visitor increased 80%, while subscription revenue per visitor increased 29.31%. Overall Revenue per Visitor increased 2%, despite Add to Cart rate falling 12%.

That last metric is important.

If we had looked only at Add to Cart, we could have concluded that the change made the page worse. Completed subscription behaviour told a very different story.

The wider lesson is that AOV opportunities often begin with how customers understand the purchase before they add anything to their basket.

4. Don't make customers do the maths

If buying more represents better value, make that value immediately understandable.

Customers should not need to calculate whether three units are cheaper per item than two, whether the larger pack saves enough to justify the additional spend or what a percentage discount means in practical terms.

The incremental benefit should be visible at the decision point.

For Stone Creek Coffee, a larger bag updated the product price but did not explicitly show the saving per ounce. We tested dynamic “Save X% per oz” messaging against the different sizes.

Conversion increased 41% and Revenue per Visitor increased 26%. Subscription orders per visitor increased 117%.

Interestingly, AOV fell 10%.

More customers selected subscriptions, which had a lower average value per individual order. So the store generated more revenue per visitor despite the headline AOV moving in the “wrong” direction.

It is a useful reminder that value communication does not necessarily mean steering everyone towards the most expensive possible basket.

Sometimes clearer value helps more customers choose the purchase option that suits them.

The same principle applies to product bundles, quantity breaks, subscriptions and gifts with purchase: make the incremental value obvious instead of expecting the customer to work it out.

5. Use the cart for reassurance first and upselling second

The cart is one of the highest-intent stages of the ecommerce journey.

That makes it valuable real estate. It also makes it dangerous real estate to clutter.

Before asking, “What else could we sell here?”, ask:

• Is it obvious what the customer is buying?

• Can they change quantities easily?

• Are delivery expectations clear?

• Can they understand the total cost?

• Is checkout easy to find?

• Are the payment options they expect available?

In a Fame test, the existing cart drawer offered the standard Checkout button. We compared passive payment reassurance with a treatment that added a dedicated Shop Pay action alongside checkout.

The dedicated Shop Pay treatment increased conversion by 47.75%, Revenue per Visitor by 69.30%, checkout-begin rate by 19.33% and AOV by 14.59%.

No extra upsell was responsible for the result.

The intervention made it easier for an already interested customer to progress.

That does not mean cart recommendations are a bad idea. Relevant additions can absolutely belong in a cart drawer. The point is sequencing: protect the cart's primary job first, then test whether additional merchandising adds value without interrupting purchase completion.

6. One AOV strategy will not work for every customer

A shopper returning for a specific replacement product is behaving differently from somebody discovering your brand for the first time.

Yet many stores show both people exactly the same promotions and recommendations.

Customer intent can change by:

• new versus returning customer

• product or category

• basket value

• subscription versus one-off purchase

• purchase frequency

• journey stage

One of the clearest examples we've seen came from a mobile search experiment for PerTronix.

Returning visitors represented 23% of visits but 43% of revenue. When search was made persistently visible on mobile, the returning-customer segment saw AOV increase 45%, revenue increase 46% and Average Purchase Revenue per User increase 35%.

New visitors did not respond in the same way.

The result was therefore not “exposed search increases AOV”. It was that a particular change better supported a high-intent customer segment with a strong reason to use search.

That distinction matters.

Relevance beats volume. The aim should not be to expose every shopper to every AOV mechanic available. It should be to understand which customers have a genuine reason to buy more and make that route easier for them.

7. Test for revenue, not just AOV

This may be the most important point.

A higher AOV is not automatically a better commercial outcome.

Imagine a change increases AOV by 10%, but conversion falls enough that fewer visitors purchase. Depending on the size of that decline, the business could generate less revenue overall.

That is why we assess AOV alongside conversion and measures of revenue efficiency when running Shopify A/B tests.

One useful guardrail is Revenue per Visitor:

Revenue per Visitor = Conversion Rate × Average Order Value

Used consistently, it helps show how the two metrics interact.

The Stone Creek dynamic-savings experiment is a good example. AOV decreased 10%, which would look negative if viewed alone.

At the same time:

• Conversion increased 41%

• Revenue per Visitor increased 26%

• Subscription orders per visitor increased 117%

• Subscription revenue per visitor increased 50%

The business outcome was stronger even though the average individual order became smaller.

This is why CRO needs more than a dashboard target. At Blend, our Shopify CRO audits look across the customer journey and commercial metrics before deciding what deserves to be tested first.

The real AOV opportunity is usually bigger than another upsell

The goal of an AOV strategy should not be to persuade every customer to spend more.

It should be to make the higher-value purchase more relevant, obvious and worthwhile for customers who already have a genuine reason to make it.

That usually means looking beyond the offer itself.

Better merchandising can make the next product easier to discover. Clearer price framing can make a larger pack easier to compare. Better reassurance can give customers confidence to complete a purchase. Segmenting behaviour can stop brands applying the same tactic to shoppers with completely different intentions.

And testing protects you from assuming that a higher AOV must mean success.

For established Shopify brands, “How do we add another upsell?” is rarely the most useful question.

A better one is:

What is currently making the right higher-value purchase harder than it needs to be?