The biggest challenge for e-commerce businesses is ensuring a superior customer service to shoppers. Helping them find what they’re looking for and guiding their shopping experience is what makes the process challengeable. In brick-and-mortar stores, you can always find savvy salespeople. They help to find what the shopper looks for and give specific recommendations based on their preferences and wishes.
The e-commerce stores have chatbots that are supposed to replace the helping salespeople in the brick-and-mortar shops. However, although online salespeople can handle some issues, they are unable to deliver as much value as the person in an actual store. Product recommendation engines were created specifically to overcome the issue of virtual communication in e-commerce stores with the help of personalization.
What is an E-commerce Recommendation Engine?
A product recommendation engine is a system that collects data and uses algorithms to make suggestions and recommendations. The data is collected for every user separately and analyzed per criteria, such as past purchases, demographics or search history. The recommendation engine takes a large pool of available data and eases the decision-making process by providing several targeted selections. So the whole idea behind the e-commerce recommendation system is to narrow down the pool of availability and show only relevant choices.
A recommender system is applicable to all e-commerce companies. For example, Amazon uses it to recommend products, and Netflix uses it to suggest movies. LinkedIn’s recommendation system narrows down the 500 million website users to show you only people, who are relevant to you and who you may know. The competitive nature of the online retail industry obliges all e-commerce businesses to make use of a recommendation system. In this blog post, we will discuss the five reason why your e-commerce store needs a recommendation engine.
1. Better User Experience
The most important benefit that recommender system will provide you is the improved customer experience on your website. The shoppers have big expectations from the ecommerce world. Given the competition, all ecommerce businesses try to offer the best possible experience to their users. This is simply impossible without setting-up a recommendation engine on your website. So to create the best customer experience, you need to exceed all expectations.
If your website visitors enjoy the shopping experience, they’ll keep returning, and eventually will become your customers. By collecting and analyzing data, ecommerce recommendation engines create personalized suggestions to the website visitors. Personalization is created by filtering the past data of the user.
Most of the recommendation systems use 2 types of filtering or the combination of both:
- Collaborative filtering – creates recommendations by comparing the actual user to other users that have similar preferences.
- Content-based filtering – makes recommendations based only on the specific user’s data, such as their past purchases or searches.
By using these filtering systems and sorting the data, the engine creates product recommendations that are personalized for specific user needs. Usually, people enjoy the experience with the brand when they feel a special attitude and attention towards them. The ecommerce recommendation engine generates an individual experience for each website user by tailoring suggestions per their needs. For example, when the person leaves the website and then comes back, he/she doesn’t want to start the whole experience fresh from the beginning. Showing recommendations based on their last browsing will be very helpful to the user.
2. Sales Boost
An intelligent product recommendation engine must be able to create recommendations of the right products, at the right price and in the right place. The core idea behind the recommender system is to optimize the content available on the website to the needs of a user. Optimizing the website will ensure a boost in sales by increasing the conversion rates and promoting the long-tail inventory. Your customers will keep returning to your site because when you know what they want, their shopping journey becomes easier.
In general, the recommendations can be personalized and non-personalized. Both can be used to boost sales. Personalized product recommendation system focuses on suggestions of such products that are relevant to the visitor’s preferences. These recommendations are generated by analyzing data like recently viewed, bought or searched items. In order to create individual recommendations like these, you must gain a lot of insights about the customer.
As for the non-personalized recommender systems, these are more useful for selling out the slow-moving inventory and for promoting popular items. As an ecommerce shop, you must have data on your best selling products. When the person visits your website for the first time, you won’t have enough data on them in order to create personalized recommendations. But you’ll still be able to make recommendations based on your most popular products among the rest of your customer base. Using a non-personalized recommender system, you will also boost the sales of your slow-moving inventory. Items that are not selling well will be recommended to people more often.
3. Enhanced Customer Engagement
The main game changer of a recommendation engine is the personalization. The improved customer experience will guarantee a higher customer engagement rate. When the customer feels valued and, at the same time, finds your website user-friendly, your chances of engagement will be enhanced. Keeping a one-to-one relationship with every customer is simply impossible, however, that doesn’t mean that you can’t engage them in a meaningful way.
Recommendation engines help with engagement process because they don’t concentrate on the purchase part only. They focus on the process as a whole to ensure a high-level customer experience. That’s how they enhance customer engagement. When a recommender system works properly, it will create tailored offers to the user. The customer will then feel more satisfied with the shopping journey. A satisfied customer will keep returning to your website and the engagement level will be increased.
Having engaged customers will also lead to higher retention rates and increase customer loyalty. Any company wants to boost the loyalty of its customers, as its the base for the long-term relationship with the brand. To raise customer loyalty, a brand must target each of its customers as a special one. In the ecommerce world, this goal can be reached only with the help of a recommendation engine. For example, apart of the on-site recommendations, the system will also send notifications and reminders to the users, who left their purchase unfinished. This is a strategy used by many businesses for increasing the engagement level.
4. More Traffic
When the content on your website is optimized for each user, this ensures the website visitor to go through all the possible options of the product they’re looking for. By clicking on one item, the recommendation engine will offer several other similar products to consider. The recommendation engine also increases the chances that your customer will be back to your website to buy again.
In general, the benefits of the product recommendations that we’ve already discussed affect the traffic on your website. The improved customer experience, better engagement, as well as the strategies that boost the sales rate create more internal traffic on your website. The greater are the performance numbers, the more is your internal traffic. People who click on recommendations visit more pages, putting a higher number of products into the carts. Such customers, who are satisfied with the product recommendations your website is generating, will most definitely buy more and come back for another purchase.
5. It Is a Must
The most leading and successful ecommerce companies are using recommendation engines. In the modern world, the recommender system is a must if you want to have effective results.
Amazon, the world’s leading online retailer uses a recommendation engine to generate offers to its users. The retail giant uses several different recommendation systems to achieve the best results. In fact, Amazon credits 35% of its revenue to the recommendation engine it uses.
As a matter of fact, this percentage is not wrong, however, it’s not that accurate too. A study was published in the conference Economics and Computation to find out how much traffic the recommender engine causes. Based on the activity analysis of 4000 products, experts found out that only a quarter of clicks are generated by recommenders. So without the recommender system, the internal traffic will drop only by 8%. Although this number doesn’t seem so impressive, it can still cause a decent effect. Especially if you’re start-up ecommerce, you want to capture all the possible traffic.
They recommend items that are frequently purchased with the items that the user already has in the cart. Also, they suggest those products that are similar to items recently viewed. Recommendations also include items that are upgrades to the products already bought. It’s also important to note that Amazon uses recommendation engines to generate suggestions both onsite and offsite. The offsite recommendations work via email and account for a higher conversion rate compared to those that are onsite.
With the help of Netflix’s recommender system, users find much more relevant movies to watch. As a recent study by McKinsey shows, up to 75% of what people watch on Netflix is generated by their recommendation engine. According to Netflix executives Carlos A. Gomez-Uribe and Neil Hunt, their recommender system saves them about (wait for it) $1 billion.
Best Buy, another retail giant, is also an example of ecommerce that has big returns thanks to their recommender engine. When the company was at the edge of failing in 2015, they started using a product recommendation engine and concentrated on the online sales. In the second quarter of 2016, Best Buy reported a 23.7% increase in sales. This number was partly generated with the help of their recommender system.
The success of any ecommerce store is heavily dependant on a recommendation engine. It doesn’t matter whether or not you have insights about your website visitors. You need to use recommendation engines to make their shopping journey more enjoyable and provide most of the value to them. The recommendation engines are becoming more accurate than ever before. They will bring a long-term value to your ecommerce shop.