Six Strategies That Can Increase Average Order Value by Up to 50%

Today, online shoppers have become quite adept at checking out more than one site. This helps them consider various options before making a purchasing decision. This is where product recommendations come in. In e-commerce, you use product recommendations to remarket, present advertisements, and display offers to customers to encourage them to buy more.

The primary challenge we’ve seen with many of our clients is that they already have a powerful tool at their disposal— a tool capable of increasing the average order value by up to 50%. Still, most clients either aren't aware of its existence, don't know how to utilize it effectively, or mistakenly consider it ineffective.

There are three main techniques you can use to meet shoppers where they are most likely to buy more or upgrade. These include:

• Related Products
• Cross-Selling
• Up-Selling

Whether you’re running an e-commerce site, app, or both, your primary goal is most likely to bring up sales by improving conversion rates, repeat purchases, and performing well overall.

In this article, we will discuss six product recommendation strategies that can help increase Average Order Value (AOV). But first, a brief dive into why product recommendations are essential for any e-commerce seller.

E-commerce product recommendations are important because they help customers make a purchase decision. Personalization helps to take it another step further. This is because customers are more likely to appreciate personalized recommendations and shopping experiences that are specifically catered to their needs.

By tailoring recommendations to individual preferences, as well as trending buys and bestsellers, businesses can present consumers with ways to check out products they may very well be interested in. This inevitably leads to increased customer retention and satisfaction.

There are many ways to present shoppers with product recommendations in e-commerce. They can be based on consumer trends and data from past sales or more personalized based on individual buying behavior, demographics, and browsing history. The general aim, however, is to get customers to purchase more to increase sales and drive average order value up.

AOV is a metric used in e-commerce to measure the average total per order placed with an e-commerce merchant over a set period. It is one of the most important metrics that e-commerce businesses need to monitor, as it drives many critical business decisions. These can include product pricing, advertising spend, store layout, and more.

E-commerce businesses can provide customers with relevant and personalized product recommendations that can make it much easier to find items they’re looking for. By presenting customers with the right product at the right time, businesses can create a seamless, delightful shopping experience to which they are more than likely to return.

Targeted product recommendations also improve overall customer experience and instill customer confidence in your brand. This translates to eventually turning curious browsers and casual shoppers into actual buyers, raising your conversion rate.

Product recommendations also add a touch of personalization to the customer experience by conveying that the brand knows what its customers want. This will likely reduce bounce rates, increase customer engagement, and raise your AOV.

Tailored, intuitive product recommendations can cement your status as a trustworthy retailer that makes credible product claims. Not only are you showing customers that you invest in technology to provide them with better experiences, but you’re also building trust in your brand by actually recommending products they may like.

Additionally, product recommendations let customers know that brands understand them as individuals. If your customers feel like their needs and preferences are being put into consideration, they are more likely to stay loyal to your brand. This is good news and can translate to repeat purchases, better engagement, and brand advocacy.

By using customer data to provide cross-sell and upsell suggestions at the point of purchase or on product pages, you can increase your AOV—or how much a shopper spends in one transaction. Customers are more likely to add more items to their cart when they see relevant product recommendations based on their preferences and browsing/ buying habits.

Apart from AOV, product recommendations can boost key metrics like conversion rate and repeat purchase rate. They are also an effective way to reduce customer acquisition costs because you’re able to get more out of your current customers.

Related Products

Related products are item recommendations to customers based on data about their browsing behavior and preferences. When making related product recommendations, the goal is to encourage additional purchases and increase AOV.

Let’s say a customer is buying a mobile phone and is more keen on technical specifications rather than focusing on a popular brand name. Related products may then display various phone brands that fit the specifications based on the customer’s needs. Complementary products like tablets, connectors, gadget bags, memory cards, tripods, lenses, and the like—may also be shown.

Up-Sell Strategies

Up-selling is about offering customers a more expensive or more advanced version of what they’re currently buying. For example, if a customer is buying a smartwatch that isn’t the latest model yet, then up-selling would mean offering the newest model by highlighting its added features.

You could also offer a discount if they purchase more, such as encouraging them to get another item and offering a 10% discount for the whole order. When up-selling, your customers can upgrade their order at the point of sale. Briefly put, you’re trying to get the customer to shell out more money than they intended in exchange for a better and pricier product.

Cross-Sell Techniques

Cross-selling, conversely, means offering your customers products and services that can complement what they’re currently purchasing. For example, if they’re buying a game console, then offering games, carriers, and other accessories—is a good cross-selling technique.

Placing these in the shopping cart as last-minute recommendations often works to create impulsive, last-minute purchases just before checking out. Cross-selling can be incredibly effective in increasing AOV, especially if you employ techniques to make these recommendations difficult to resist.

Manual, Semi-Automated, and Automated Solutions for Product Recommendations

Now that we have a basic understanding of these concepts, we'll show you how we can effectively use them. First, let’s explore a few modern, fully automated models for creating related products for your end customers.

The traditional model of making product recommendations is still manual related products, which remains reliable because most content management systems already have the feature built-in. Related Products are easy to use, especially if you already know your product range, have already analyzed your sales, and can offer alternative options or accessories for the main product.

For this reason, related product recommendations are a great starting point. However, despite being a cost-effective solution, doing things manually can take time and effort. Typically, you’ll still need to create the list of relationships for products, add new ones, make adjustments, and invest your time (or hire someone else) to do everything.

For stores with a small product range, this might not be too big of a hassle. However, for stores with over 10,000 products, it's possible that one content manager won't be enough. The situation becomes even more complex when you're constantly updating your product range.

Can this process be automated?

Definitely!

There are many solutions available in the market that can be installed and configured for automation.

Adobe Commerce

For instance, Adobe Commerce has a Related Product Rules functionality. This feature automatically determines and displays related products in an online store based on various criteria and customer data, such as:

• Purchase history
• Average order value
• Color preferences

You can then use different rules and conditions in combination with Customer Segments. This functionality can save you much time, but it won't be entirely hands-free. You'll still need to create, improve, and constantly update rules and conditions, especially if your product range frequently changes. However, you can finely tune related products and segment users so that the relevance of the recommendations remains high.

“Recommend” by Algolia

Another way to create related products is by utilizing cloud services that analyze your product feed and offer recommendations based on their own algorithms. Algolia, a headless search engine, is one example of this. The integration process is smooth, simple, and not very time-consuming. On some projects, our clients at Perspective offer several collections of recommended products to their customers, not only on product pages but also in the shopping cart.

Recommendations rely on supervised machine learning models that are trained on your product data and user interactions. ‘Recommend by Algolia uses collaborative filtering and content-based filtering algorithm types to make recommendations.

Collaborative filtering is about making recommendations based on the same set of users that interact with them or the same set of users that bought similar products. Content-based filtering, on the other hand, analyzes key attributes of items, such as their titles, descriptions, attributes, or characteristics, to find similarities.

The Trending Items model, on the other hand, looks for items in your product catalog that have recently become popular (based on conversion events). You can use both models together. For example, you can show trending categories on your home page in a carousel layout, and each carousel card will show the trending items for each category.

AI Integrations for E-Commerce Product Recommendations

By now, a lot of us are already familiar with ChatGPT and have already used it at some point. But did you know that you can have a ChatGPT Magento Integration on your website? This enables you to analyze user queries and provide product recommendations.

An essential step is training ChatGPT to understand user queries. To do this, ChatGPT needs access to your product database. After integration, it's crucial to test it to ensure it correctly analyzes user queries and offers suitable products. The whole process is being continually improved through data analysis and recommendation optimization.

ChatGPT also allows users to interact with your website naturally. This creates a more personalized and user-friendly experience. One of its most significant advantages is its ability to work with various types of content and information. This feature makes it a flexible option for displaying product recommendations and responding to user queries.

For example, let’s assume your website sells different categories of knives. These could include kitchen knives, hunting knives, knives for meat grinders, paring knives, and more. When a user types “knife” in the search and goes into the kitchen knives category, ChatGPT will offer only relevant product recommendations. This is because it understands cause-and-effect relationships and has a high depth of knowledge.

Conclusion

Product recommendations are an important component of your e-commerce selling strategies. Related products, cross-selling, and up-selling techniques help to increase your AOV, conversion rate, and customer loyalty.

When your customers feel you are aware of their preferences, they are more likely to stay loyal to the brand. Personalizing product recommendations also makes the online shopping process more enjoyable. It takes the monotony out and provides a more engaging experience. Such engaging experiences are what your customers are likelier to come back for.

We can help you craft and implement a solid product recommendation strategy. Our team of experts at Perspective Magento Team can also help you with your web design, Magento, and optimization needs. Get in touch with us today or book a personalized consultation to learn how to improve your e-commerce sales and customer engagement.