Product Recommendation - Boost sales and increase shopper satisfaction

I. Why your ecommerce needs a product recommendation engine

Along with the fast development of advanced technology, e-commerce has been increasingly popular in the market place. Therefore, there are several tools, applications, extensions, and so on to support the work of online merchants. Among these supporting tools, a product recommendation engine is highly appreciated by users because of numerous advantages as following

Personalize every customer’s web experience

One of the greatest benefits of applying a product recommendation to a product page is generating an individual web experience for every web browser. Typically, people have a tendency to have the good feeling with the company that gives them more attention. In other words, customers all expect to receive special care from online stores. With support from product recommendation engines, online store system can track all customer shopping behaviors and set up personal mode for every consumer. It means that, when a web browser visits your web page, he can have a bundle of products and recommendations from customers who already purchased your products. Besides, visitors are also supported to see a wide range of best seller items.

Furthermore, after a consumer decides to buy a product, a product recommendation engine such as Magento 2 Related Product extension will offer him different choices related to his products or his interest. For example, after purchasing an Iphone X, consumers will see recommendations about earphones or cases for their phone. All the keywords used by consumers are saved to build up their own personal experiences and shop owners do not need to waste their time finding related products or setting up.

Select the best products with minimal effort

An online merchant may sell hundreds or thousands of items; however, only a few among them work effectively. With the help of a product recommendation engine, a short list of most popular products with buyers will be created. In other words, a product recommendation engine is a multi-task taker who helps admins to analyze product performance and purchase pattern to finalize the best choices. Shop owners, as a result, can depend on this list to generate their better inventory to attract shopping doers.

Increase Customer Loyalty

Customer loyalty is integral part in any company’s targets since a number of instant consumers will help an enterprise to go through thick and thin. Moreover, these customers when being happy with both products and services offered have a tendency to recommend the company to their friends, who may be ideal buyers in the future. If a brand wants to raise customer loyalty, they need to treat every target customer as special one or instead make them feel valued. Using a product recommendation such as related product extension in this case is the best choice for any e-commerce enterprise. For every customer, they will receive a suggestion for products which are “just for” them via store website or their emails. This is an intelligent strategy that makes every shop buyer feel that they are important and they want to continue business with this store.

Product recommendation engines are vital to any online merchant to survive and perform well in the market place. Find more below about how remarkably they can support your online store.

Frequently Bought Together	Who Bought This Also Bought	Automatic Related Product

II. 9 most useful product recommendation techniques to improve sales for online merchants

E-commerce enterprises have been becoming increasing popular in the market place. To launch smoothly and effectively each online merchant will undoubtedly need the help from supporting tools such as product recommendation engines. Basically, product recommendation engines functions as advisors to provide appropriate suggestions for web browsers. However, there are different ways that are used to figure out the most suitable advices for consumers. Following are 10 most effective techniques used to increase revenues.

2.1 Frequently Bought Together

This method is mostly used to display suggested products on cart pages when a customer already chose a product. For example, if a consumer decides to buy an Iphone 8, some suggestions such as earphones, cases, rings, and so on will be recommended for him. Applying this technique to increase the number of items and the amount of value per order is highly effective since these items suggested are often of customer’s demands. However, there is still a drawback in this strategy that shop admins should take into their consideration is checkout process. As the more buyers click on products, the more suggested options will be displayed; checkout process as a consequence, will take longer and more complicated. Therefore, store owners should optimize their pages to make sure that checkout process is at ease to all consumers no matter how many items they add after receiving recommendations.

Click here to learn how to have the Frequently Bought Together block on your site.

2.2 Top selling products

A product recommendation engine to display best-seller products is applied for almost all online merchants as a strategic sale method. Especially, it is highly suggested in case the stores have limited customer data. In other words, best-selling product recommendation is a backup plan when other recommendation engines do not have enough information to perform its functions.

Click here to learn how to display Bestsellers block on your site.

2.3 Latest products

Latest product recommendation is quite similar to best-seller recommendation as it is specially suitable for a campaign that does not need to be personalized. This method is very useful and handy for web browsers as they can easily identify the most up-to-date products in the marketplace without wasting time looking for them. Additionally, this engine enables regular customers find out what is new in the store just in a second.

Click here to learn how to create New Products block.

2.4 Similar products

This method needs a certain amount of customer data about their tastes and preferences to figure out the most suitable suggestions for shopping doers. Data can be collected via customer shopping behavior such as the products they are looking for, products already bought in the past, keywords, and so on. If an online store system can determine that they thoroughly understand what customer’ needs and they care about customer’s interest, they probably create a sense of satisfaction and retention among consumers.

2.5 Recently viewed products

Imagine when a customer explores a product by chance and later they want to find more information about this product, recently viewed recommendation works perfectly in this field. Every item that a buyer used to search in your online store will be recorded and personalized to give them suitable recommendation whenever they need. Only by one simple click, can customer track all their search history; therefore, they can make shopping decision more easily.

2.6 Popular products

Popular product recommendation is applied to provide suggestions to customers who do not have any idea about detailed description of the product they want to purchase. The recommendation engine which offer popular items will be such a helpful advisor in this situation. A series of items which are favorable for many people will determine that these items are fashionable or have good quality. For example, when a female want to search for a dress and she only enters “dress” in the searching box. By giving her the most popular and favorable dresses chosen by other people, she can take them into her account. As a result, decision-making process will take lesser time and be easier as well.

2.7 Who bought this item also bought

This recommendation engine is a tool that offers suggestions after a shopping doer decides to buy a particular item. From other people’s experience and shopping behaviors, additional options are generated. Therefore, customers can treat these suggestions as useful advices from many consultants. Moreover, since these suggestions are based on other consumer’s purchases, it will become more reliable and trustworthy. Click here to learn more about Who Bought This Also Bought

2.8 Personalized recommendations

Personalized advisor provides recommendation to consumers based on their previous shopping behaviors. That is the reason why to function this method, online merchants need to accumulate a certain amount of customer data via their past purchase and browsing history. Each consumer, as a result, will receive a unique list of recommendations that highly match their preferences and tastes. A personalized recommendation engine is considered to the best one to give specific and useful suggestions for web browsers.

2.9 Off-site recommendations

Off-site recommendation engine is applied after a consumer already purchased a product and finished their online session in the stores. It is a follow up activity which is expected to increase customer’s demands about other products. Depending on what consumers bought in their previous session, algorithms will analyze several criteria to figure out the most appropriate results to offer to consumers. These results will later be sent to buyers through their emails. Some online merchants even take advantages of this chance to attach an appealing voucher such as discount to encourage customers to shop more.

Frequently Bought Together	Who Bought This Also Bought	Automatic Related Product

How Amazon succeeds with product recommendation

Product recommendation engines have increasingly determined its importance in boosting revenues by offering consumers chances to have better experience when shopping online. That is also the reason why many online merchants try to make the best of product recommendation engines and gain positive results. Among many e-commerce enterprises applying these tools, Amazon seems to be the most successful one with an impressive 35% of sales comes from the effect of product recommendation engine. Let’s see how Amazon has managed to raise customer’s demand by product recommendation engines.

3.1 Types of recommendation engines

To gain success, Amazon takes advantages of both onsite and offsite recommendations. On-site recommendation is the act of giving suggestions for web browsers during their online sessions. On the other hands, off-site recommendation happens when a series of suggested items are sent to consumers via email after they already bought a product. Although, these two ways of recommending possibly-bought products for visitors have differences in delivery, they have the same intention in increasing the desire to purchase a product among shopping doers. Additionally, besides giving various related products that consumers want to purchase, Amazon includes “add to cart” button for every single product that higher user’s demands to buy products immediately.

3.2 On-site recommendation

It is noticeable that Amazon has made use of numerous product recommendation engines to offer on-site suggestions to visitors. Some of the most outstanding tools should be listed are: your recommendation, frequently bought together, top best sellers, who bought this item also bought,…

3.3 “Your recommendations”

It can be said that this tool makes customer irresistible to purchase more products. Only by a click to “your recommendations”, a list of recommended products from different categories that users used to look for will be presented. In other words, with a simple click, web browsers can figure out the products that are of their tastes and preferences. As a result, they have a tendency to purchase more.

3.4 “Frequently bought together”

This recommendation method functions as a tool to increase the average order value by giving suggested product based on the already chosen items. For example, after a consumer decided to add an Iphone X in their cart, a list of frequently-go-together products will be showed as well such as earphones, charger, case, and so on. In short, “frequently bought together” is highly appreciated to up-sell and cross-sell.

3.5 “Best-sellers”

With a list of top best-selling items, Amazon tries to give a message to every customer that “many people choose to use these items, and you, why not?”. Additionally, by showing the most chosen products, Amazon help consumers update what is the most popular and trendy items at the present. Therefore, help them to make decisions easier with more fashionable products. By this way, Amazon also has more opportunities to upsell and cross-sell their products.

3.6 Off-site recommendations

Off-site recommendation is considered as a follow up activity after customers already purchased a product. Based on their shopping behaviors, their tastes and preferences, Amazon will then send them a list of recommended products via their email addresses. By getting to know many criteria that consumers take into their consideration, Amazon can easily catch their attention by suggested products and raise their demands to possess those items.

In conclusion, by learning what consumers are looking for, Amazon enhance customer’s experience by providing a series of appropriate products at the right time in suitable positions on the right pages. Besides, using tools to personalize every customer enables Amazon to attract more attention from them potential buyers.

If your online stores also need such amazing tools to support your ecommerce like Amazon, let’s take a look at our outstanding extensions below:

Frequently Bought Together	Who Bought This Also Bought	Automatic Related Product

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