Understanding Product Recommendation Technology for eCommerce
Understanding Product Recommendation Technology for eCommerce
The product recommendation engine could be the most exciting technology for customer service personalization to hit the market this decade. Today, customers are looking for highly unique, relevant, and engaging shopping experience, customized to suit their specific needs. However, that doesn’t mean they know exactly what product or service they want.
A product recommendation engine is a tool which helps companies to understand their audience and deliver custom advice on which products or services they need. Your client gets the support they need to make a confident purchasing decision, and you boost your chances of higher conversions, better brand loyalty, and even a greater customer lifetime value.
So, what exactly is product recommendation technology, how does it work, and why is it so important to your strategy for CX? Let’s find out.
What is a Product Recommendation Engine?
A product recommendation system or recommendation engine is a state-of-the-art tool designed to help you guide customers to the services or solutions most-suited to their needs. A good product recommendation example most companies are likely to be familiar with is the Netflix algorithm, which offers insights into the content users might like, based on their watching habits.
Product recommendation engines use algorithms and data to recommend the most relevant product suggestions to a customer, often based on a number of factors.
While the exact architecture and elements of a product recommendation system will depend on the tool you choose, most solutions use a combination of artificial intelligence and data analysis to deliver results. The focus is on providing a win/win transactional experience.
Your customers get:
- Relevant products they’re actually interested in
- More personalized shopping experiences from their favorite brands
- Faster, more convenient purchases
Your business gets:
- Higher customer satisfaction rates
- Stronger click-through rates and conversions
- Improved customer retention and loyalty
- Higher customer lifetime value
- Reduced cost per acquisition
How Do Product Recommendation Tools Work?
To deliver personalized product recommendation in eCommerce, companies need to use specialist tools capable of collecting information and converting that data into dynamic content for customers.
The best product recommendation tools collect information about your customer using cookies on their browser. Outside of Netflix, there are tons of examples of other companies using product recommendation these days.
Social media platforms use similar tools to decide what kind of content users will see when browsing on the platform, app stores from Google and Apple use the technology to suggest which apps you might like to download, and so on.
Even content creators can use product recommendation on their websites to help suggest to customers which blogs they might want to read based on their interests.
What Kind of Filtering Methods Do Recommendation Engines Use?
Collaborative filtering is one of the most common kinds of product recommendation engine.
Product recommendation engines with collaborative filtering tools collect and analyze various pieces of information such as buyer behavior, preferences, and activities. After looking at this information, the engine can suggest what the customer might like, by comparing their profile with other users. Think about how Amazon suggest what other customers buy after you add something to your basket.
This filtering method can recommend a wide range of items to a customer, without the system needing to understand what each item can do. There are various “sub-categories” of collaborative filtering too, such as:
- User collaborative filtering: Here, the algorithm recommends products based on what similar buyers have chosen. This requires a lot of time and data processing resources and requires the algorithm to create “customer segments” for the business. It’s not deal for ecommerce stores with extensive ranges of products.
- Item collaborative filtering: This product recommendation method organizes various product options into segments or groups. This means a customer will be recommended “similar” products to items they’ve bought or added to their basket, based on connected items in the backend algorithm.
- Content collaborative filtering: These types of product recommendation engines use cookies to track users over multiple visits, using insights into which pages they visit, what content they interact with and so on, to make suggestions. YouTube is a great example of a company using this method effectively.
As customers continue to demand more advanced, personalized experiences, many ecommerce companies are embracing “hybrid” recommendation systems, which combine collaborative content-based recommendations. Spotify’s “Discover Weekly” playlists are based on hybrid filtering methods which use algorithms to collect data on your listening habits, and similar user listening habits.
How Recommendation Engines Enhance Ecommerce Stores
Recommendation engines can transform every part of your ecommerce store. Today’s customers are looking for fast-paced and convenient shopping experiences, and product recommendation engines can help you to deliver exactly that.
Just some of the places you might embed your recommendations include:
- On product pages: Your recommendation engine can embed content into your product pages, suggesting potential additional products your customers might want to add to their basket with “You may also like” carousels. These smart recommendation showcases instantly increase order value.
- In catalogue pages: Ideal for customers who know what kind of product they want, but not exactly what they need, recommendations in the catalogue page can enhance the shopping experience. For instance, a customer who clicks on the “Jeans” section in a clothing store can instantly get a list of recommended products based on styles and sizes they’ve bought before.
- Home pages and landing pages: You can also add product recommendations to the home page, so your customers get instant inspiration on what they might like to buy from the moment they visit your website. Recommendations on your homepage can help to maintain the momentum you’ve already created by convincing someone to visit your store.
Do You Need a Product Recommendation Engine?
The short answer is every ecommerce business can benefit from a product recommendation engine.
No matter how small your business is, delivering more personalized, relevant recommendations to your customers improves your chances of conversions, while increasing sales and average order value. With a recommendation engine, you can help to guide your customer through the purchasing process, much like a sales rep would in a traditional brick-and-mortar store.
These days, adding product recommendation engines to your store can be as simple as installing a plugin for Shopify. When increasing your order value is that simple, who wouldn’t want a product recommendation engine?
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