Increase Average Order Value Onsite: How One Brand Leverages Four Core Products to See Results

In this article, we’ll walk through four strategic ways to improve average order value onsite. To illustrate these strategies, we’ll cover how UK sports gear retailer SkateHut uses four of Nosto’s core products in full harmony in order to improve AOV.

Average order value (AOV) is a magical metric and, unarguably, one of the most important tactical and strategic metrics in ecommerce. Improving it brings down relative cost per delivery and drives customers to shop multiple product categories versus just one – which, as a result, positively impacts crucial metrics like customer lifetime value (CLTV) and revenue per visitor (RPV). Finally, if executed accordingly, it can also beef up margin-per-sale/checkout, which in exchange allows bigger marketing spend and delivers even more sales.

Covering every imaginable trick to increase AOV would be worth a playbook of its own. So, in this article, we’ll show you how one brand uses four of Nosto’s core products (Onsite Content Personalization, Dynamic Bundles, A/B Testing & Optimization and Segmentation & Insights) in full harmony to increase their AOV onsite.

The Starting Point: Identifying Challenges with Increasing AOV

SkateHut is the UK’s favorite shopping point for skateboards, scooters, bikes, longboards and hoverboards for adrenaline junkies. While SkateHut makes most of its sales through their key product ranges, accessories and equipment such as pads, helmets and the like are a crucial part of their inventory and a clear method to increase their AOV. Naturally, their challenge is that the majority of shoppers show a buying intent for skateboards and other key product ranges; so how do they provide direct, visual cues for these shoppers to buy the entire kit versus just a skateboard?

The key benefit of AOV

In this context, AOV is an imperative metric and serves as a guide to optimize individual site visits. It’s equally as important to get a shopper to buy from multiple product ranges instead of just one, as that increases the probability they will eventually return to shop for a broader range of needs. This can be measured by tracking and optimizing for Customer Lifetime Value (CLTV) and using product based metrics which reveal the range of categories bought by an individual shopper.

1. Increasing AOV Through Relevant Add-ons and Promotions

To improve AOV on their Product pages, SkateHut offers affordable add-ons based on product range, such as trainer skateboards for skaters and scooter stands for scooters. Accessories and equipment, meanwhile, are applicable to all key ranges. The brand actions this by using Dynamic Bundles, as seen on their “You Might Need These” section on Product pages (image 2 below).

In context of the website promotion, the mission was to expose shoppers to different content banners on product detail pages. Fueled by Content Personalization, the content in these banners is dependent on the product range browsed by the shopper and also promotes and highlights matching accessories to complete the shopper’s purchase.

In the examples below, you can see how both approaches are executed on the same product detail page:

2. Testing Strategies Onsite to Boost AOV (and Tapping Into Data to Make the Best Decision)

To make the scenario a little more complex (but still easy to action), SkateHut offers similar but varied promotions for scooters, which requires matching onsite promotions with the top-level category and product range, depending on what the shopper is browsing:

The question at hand:

Which one of these two strategies, if any, yields a bigger impact on increasing average order value? To find out, we turn to the data and test, test, test.

Leveraging A/B Testing & Optimization and Segmentation & Insights

Since shopping is very much a contextual experience, the final step would be to figure out not only which one of these approaches delivers the stronger impact to the bottom line, but also determine if shopping behavior differs between mobile and desktop users.

For example: perhaps personalized content would work better for mobile users as an ongoing campaign, while full-screen desktop shoppers might be more keen to spend time onsite and purchase a complete set of products with accessories. That’s where Nosto’s A/B Testing & Optimization and Segmentation & Insights come into play:

• A/B Testing & Optimization is used to split-test the strategies to determine which one yields a bigger impact.

• Segmentation & Insights is used to break down split-test results by device, as seen below.

We’re not at liberty to reveal the winning experience in this example (and regardless, perhaps results would differ on your website based on your clients and products). But all in all, setting up the experience and test, from start to finish, took a mere 30 minutes.

In Summary: 4 Core Products, One Cohesive Shopping Experience

Here’s a quick breakdown to summarize the products that SkateHut used to increase AOV:

• Dynamic Bundles to create automated bundled offers on product pages, similarly to content depending on the browsed product range.
• Onsite Content Personalization to deploy promotional banners which adjusted depending on the product category (in this case, scooters and skateboards).
• A/B-testing and Optimization to split-test which one of the selected tactics yields bigger commercial impact.
• Segmentation & Insights to break down the split-test results by device to review how mobile and desktop behavior differs.

Interested in setting up your own strategy to increase AOV using these core products? Contact your Customer Success Manager or ping us in the pink chat bubble below and we can help you get started in no time.