Loading the latest writing…
A tidy catalogue doesn't sell itself. This post breaks down how rules, bundles, cross-sell and upsell in Adobe Commerce work together as a merchandising system, not four separate tactics, to lift average order value and turn one-time buyers into repeat customers.
A well-built catalogue gets shoppers through the door. Smart merchandising is what gets them to buy more, come back sooner, and tell their friends. For merchants running on Adobe Commerce, the gap between a tidy product catalogue and a genuinely profitable storefront is almost always filled by merchandising strategy: the rules, bundles, cross-sells and upsells that quietly guide a shopper from browsing to checkout.
In this guide, we will walk through practical Adobe Commerce merchandising strategies you can use today to lift average order value (AOV) and encourage repeat purchases, without resorting to pushy tactics that annoy customers and hurt long-term trust.
Customer acquisition costs keep climbing, and paid media budgets stretch thinner every quarter. That makes the customers already on your site, or already in your database, your single most valuable growth lever. Getting each shopper to add one more item, choose a better tier, or return for a second order has a direct and compounding effect on revenue.
This is precisely where Adobe Commerce merchandising strategies earn their keep. Rather than depending purely on discounts to move product, merchandising uses timing, relevance and presentation to make a bigger basket feel like the obvious choice.
Average order value is a useful barometer here. When AOV climbs, it is usually a sign that your recommendations are relevant, your pricing feels fair, and your merchandising rules are doing their job quietly in the background rather than shouting at the shopper.
Adobe Commerce gives merchants four core merchandising levers. Used well, together, they form a system rather than four separate tactics bolted on at random.
Adobe Commerce's related product rules let you target which products appear as related items, cross-sells and upsells, based on conditions you define, such as category, attribute, price range or customer segment. Instead of manually curating "you might also like" sections product by product, you set a rule once and let the catalogue populate itself dynamically as new products are added.
Each rule can be tied to a customer segment, so a first-time visitor might see a different set of related products than a loyal customer with a history of premium purchases. Rules are also sorted by priority, with products from lower-priority rules only filling gaps left by higher-priority ones. That means you can layer several rules, a clearance rule, a seasonal rule, a margin-protection rule, without them fighting each other for the same slots.
Practical tip: keep rule logic simple to start. A rule such as "same category, price within 20 percent, in stock" will outperform a dozen overlapping conditions that nobody on the merchandising team fully remembers a year later.
A bundle combines multiple products into a single purchasable unit, priced and merchandised as one offer. Bundles work because they solve a decision problem for the shopper: instead of researching which accessories pair with a main product, the bundle has already made that decision for them, and usually at a small discount that feels like a reward rather than a compromise. Bundles are particularly effective for:
The key with bundles is that the combination should feel authentically useful, not like a way to clear a warehouse. If shoppers sense a bundle exists purely to shift dead stock, trust erodes quickly.
Cross-selling recommends a complementary product that improves or completes the original purchase, most commonly shown at cart or checkout, where the customer has already committed to buying and is thinking about what else they might need. A "frequently bought together" module on the product page, or a "customers also bought" carousel at checkout, are classic implementations.
Cross-sell works best when it is genuinely complementary. A phone case suggested alongside a new phone makes sense. A completely unrelated item suggested purely because it has high margin does not, and shoppers notice the difference.
Upselling moves the customer towards a higher-value version of the product they already intend to buy, a larger size, a better material, an extended warranty, or a higher software tier. Upsells typically sit on the product page itself, before the shopper has committed, since the goal is to shift their choice of product rather than add to an already-decided cart.
The most effective upsells frame the higher tier around a benefit the shopper already cares about, longer battery life, more storage, better durability, rather than simply presenting a bigger number next to a bigger price.
Individually, rules, bundles, cross-sell and upsell each nudge AOV upward. Used together as a coherent strategy, they compound. A shopper might be upsold to a better product on the product page, cross-sold a complementary accessory at cart, and later remerchandised into a bundle on their next visit based on purchase history.
A few principles help tie these together:
Match the tactic to the moment. Upsell before the decision is made, cross-sell once it is made, and bundle before the shopper has even started deciding.
Use segmentation, not guesswork. Adobe Commerce's rule engine allows merchandising to differ by customer segment. A returning high-value customer and a first-time browser rarely respond to the same offer.
Protect margin, not just revenue. A cross-sell that lifts basket size but triggers a wave of returns, or a discount so steep it erodes contribution margin, is not a win. Track margin alongside AOV, not instead of it.
Let AI recommendations do the heavy lifting where it makes sense. Adobe Commerce's AI-powered product recommendations analyse shopper behaviour and surface personalised suggestions across the storefront, on product pages, in cart, and at checkout, without merchandisers needing to hand-curate every placement. Roughly three in ten ecommerce revenue paths now begin with a product recommendation, which makes this far more than a nice-to-have feature.
Lifting a single basket is only half the story. The real prize is a customer who comes back. Merchandising strategies that respect the shopper's intelligence, relevant bundles, honest upsells, cross-sells that genuinely help, build the kind of trust that brings people back for a second and third order.
A few tactics specifically aimed at repeat purchase:
When you track repeat purchase rate alongside AOV, you get a much fuller picture of whether your merchandising strategy is building genuine customer relationships or simply squeezing a bigger basket out of a one-time buyer.
None of this is worth much without measurement. At minimum, track:
Where possible, use a holdout group before rolling a new rule or bundle out to the whole store. AOV can shift for reasons entirely unrelated to your merchandising change, a seasonal spike, a site-wide promotion, so isolating the actual effect of a new rule matters more than the headline number looks.
If you are new to building out Adobe Commerce merchandising strategies, resist the urge to launch everything at once. A sensible rollout looks something like this: Start with one or two related product rules on your highest-traffic categories Add a small number of genuinely useful bundles, tested against a control group Introduce cross-sell modules at cart and checkout for your best-selling products Layer in upsell messaging on product pages for items with a clear tiered structure Review AOV, attach rate and repeat purchase rate monthly, and prune anything that is not pulling its weight
If you are just getting started, the highest-leverage first step for most merchants is auditing your existing related product rules and cleaning up the category and attribute data they depend on, then layering in one or two bundles before touching cross-sell and upsell placements. Rules and bundles compound in value once that foundation is solid, but they underperform badly if the underlying catalogue data is messy or inconsistent.
Merchandising in Adobe Commerce is not about switching on every feature at once. It is about sequencing rules, bundles, cross-sell and upsell against a data foundation and a measurement plan that can actually support them.
Want to dig into this further with people actually doing the work? This is exactly the kind of topic we'll be discussing at Mage Camp, alongside merchants and Adobe Commerce specialists sharing real, practical experiences rather than vendor pitches. Register for free at Mage Camp and join the conversation.
Many new stores wait too long to set up their analytics, missing out on crucial historical data. This guide covers the foundational data strategy, GA4 implementation, and the key KPIs every Magento store needs to track from launch to ensure sustainable growth.
Every merchant running an eCommerce store eventually hits the same wall: a key person leaves, peak trading exposes a gap, or a competitor pulls ahead. For Magento and Adobe Commerce merchants, this piece looks at three habits that separate businesses who scale smoothly from those who don't: investing in the people behind the platform, building genuine platform literacy across the whole business, and staying connected to the wider community.
AI promises to fix your search, recommendations, and merchandising overnight. In practice, it only works if you sequence it right. Here's a practical, phased roadmap for bringing AI into Magento and Adobe Commerce, including what's built-in, what needs a third-party tool, and where to start first.
