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Product Recommendation System
Everything You Need to Know About Product Recommendation Systems
Benefit from AI-powered product suggestions tailored to every visitor in your e‑shop with a recommender. By leveraging their preferences and past online activity, our tool provides the ultimate personalized shopping experience.
Trusted by more than 3,000 online businesses
Recommender
What is a product recommendation system?
Product recommendation engines are designed to help online stores and website visitors find the relevant content and items that best meet their needs and interests.
A recommendation system uses several user data, e.g., past purchases, browsing history, and ratings, to personalize product recommendations.
Personalization with Recommender
A recommender is an algorithm that considers the user’s previously viewed items and searches its database for similar products.
It helps narrow any search by presenting personalized recommendations based on observed behavior.
Improved customer experience
By providing customers with items tailored to their individual interests and preferences and products similar to what they have already viewed, you can greatly improve their user experience.
Creating a personalized experience leads to customer loyalty and repeat purchases.
It is extremely easy to use and has robust features to boost your e-commerce project. I especially like AI-powered search and personalized recommendations for our customers. In fact, thanks to Luigi's Box, we managed to increase our average order by more than 10%. Therefore, I highly recommend Luigi's Box to anyone who sells online.
Tomáš O.
Co-founder & CMO
How it works?
How product recommendation systems work
The recommendation process consists of several steps. First, with product strategies, AI technology can evaluate products, consumer interactions, and preferences. Based on this data, the system then generates recommendations for similar products or additions like extended warranties. It takes into account purchase history, time spent viewing a product, and other behavioral patterns.
Image analysis
In addition to analyzing customer data, product recommendation engines can also analyze the images of products. Recognition technology determines which items are similar and, therefore, recommends them. This helps customers find products they may not have found otherwise while still offering personalized recommendations tailored to their interests.
AI evaluation of previous interactions
AI technology can also evaluate customer behaviors across platforms. By analyzing their past activities, AI-powered recommendation systems can predict future purchases, helping you better anticipate your customers’ needs. Previous interactions are also crucial in providing relevant and valuable recommendations to the customer.
Recommend best sellers or selected products
Motivate your customers to buy more by featuring AI-driven recommendations for the most popular products. Leveraging cutting-edge technology tailored to match customer interests and preferences, our product recommendation system will expertly select bestsellers, complementary products, or items of interest that could be beneficial additions to their shopping cart.
Improved conversion rate
By providing customers with tailored recommendations, you can increase the likelihood that they will make a purchase. This leads to higher conversion rates and more sales for your business.
Increased average order value
With product recommendations, you also have the opportunity to increase the average order value. As customers are exposed to more items, they may be more likely to purchase additional items that complement their current purchases.
Enhanced user experience
Product recommendation systems can help create a personalized and convenient user experience. By providing users with tailored recommendations based on their interests, you can ensure that they have the best possible shopping experience.
Increased customer loyalty
Quality of recommendation is crucial to the customer journey. Customers will be more likely to become repeat purchasers and recommend your products to others if they find their experience pleasant and convenient.
Increased revenue
By leveraging product recommendation systems, you can increase your business’s revenue. As customers are exposed to more relevant items, they become more likely to purchase those items and generate more sales for your business.
Placements
Where can product recommendation systems be placed?
Product recommendations can be placed on various user-facing web pages. Doing so can increase the likelihood of customers discovering products they are interested in and significantly increase conversions.
Home page
On the home page, product recommendation lists can highlight new arrivals or best-selling products, helping customers better understand the store’s offerings.
Product detail pages
Recommender boxes can also be used on product detail pages to direct users towards items related to the ones they’re viewing, increasing their chances of buying multiple items from your store.
Shopping cart page
You can display product recommendations on shopping cart pages to remind customers of items they might have missed adding to their order. This can also help you upsell and cross-sell related items.
Category landing page
Product recommendations can be used on category landing pages to help customers easily find the items they need. By doing so, you will make it easier for them to navigate your store and increase their chances of purchasing.
Search results page
By displaying product recommendation lists on search results pages, customers can find items related to the ones they’re searching for. This will improve their search experience and increase the likelihood of them making a purchase.
How to get one
How to get product recommendations for your e-shop
Getting product recommendations for your e-commerce shop can be done with multiple methods. Most e-commerce platforms offer a built-in product recommendation system, but for the best results, you may consider using a professional tool like Luigi’s Box.
Build your own recommender
Building your own product recommender can be done with various tools. You can use a framework to develop your own algorithms and generate tailored recommendations for each customer. This method is great for business owners who want complete control over their product recommendation system. However, it requires substantial technical knowledge and can be extremely time-consuming.
Order it from a trusted vendor
AI-powered Recommender from Luigi's Box provides tailored recommendations to each user based on their past interactions with your store. The system is designed to identify customers' interests and preferences and offer items that match those needs. All you need to do is create a free account, synchronize your product database, and let the Luigi's Box team do the magic.
How to get product recommendations from Luigi's Box
Luigi's Box can be integrated into any platform, and there are several options for how to, based on your needs and possibilities.
Create an account
You only need a few minutes to enter basic data and create an account for free.
Run analytics
Integrate Luigi’s Box Analytics service to enable learning with your website.
Sync the catalog
Simply synchronize the products via the API or link the feeds with our system.
Launch tools
The tools you’ve chosen will be matched with your design, and you're ready to go.
Demo call
Try Recommender from Luigi's Box
Luigi’s Box Recommender is a powerful and reliable product recommendation system trusted by over 2000 shops.
Book a demo call today to find out how you can get Luigi’s Box Recommender for your e-shop.
Book a Demo Call
Luigi's Box is compatible with any website
There are three ways how to deliver your product data to Luigi’s Box.
Case Studies
Real-world applications for recommender
28%
increase in conversion rate
+51%
Recommender CTR
+ 15%
increase revenue
+9,49%
search conversion rate
+10,5%
search conversion rate
+96%
search conversion rate
+320%
average conversion rate
+600%
search conversion rate
+32%
search conversion rate
+230%
conversion rate of selected product segment
More Tools
What's in the box
Analytics
Comprehensive analytics that identifies issues with search queries and helps find out how to optimize and improve them for better results.
Search
Smart search with autocomplete helps visitors quickly find the products they are looking for, considerably reducing wasteful shopping time.
Recommender
Personalized boxes with product recommendations help raise the average order value and can be placed anywhere on the website.
Product Listing
Personalized product listing pages, organized in a way that enhances browsing experience, supports your business goals and increases revenue.
Get started
Create your free account today & start measuring your e-shop’s performance
Sign up with Luigi’s Box today to unlock the power of AI-driven product recommendations, analytics, search, and personalized product listing pages. With our easy installation process for e-commerce stores, you’ll be ready to go in no time.
Simply fill out the form and give us your contact information. We'll contact you as soon as we can to schedule a demo call with you. You will learn everything you need to make a decision about Luigi's Box
- We'll show you how our products work and the benefits they bring
- We'll explain how our search processes languages
- We'll show you how Luigi's Box works from the UX & UI perspective
FAQ
Frequently asked questions
What is an e-commerce recommendation system?
An e-commerce recommendation system increases revenue and customer engagement by providing personalized product recommendations tailored for individual customers. It uses sophisticated machine learning algorithms to generate relevant recommendations based on past customer behavior.
Why do recommendation engines matter?
A recommendation engine helps customers easily find items related to their search and explore new products they may be interested in. By leveraging this technology, businesses can increase customer engagement, boost sales, and improve overall customer experience.
What are the main types of recommendation systems?
The main types of recommendation strategies are content-based filtering, collaborative filtering, and hybrid methods. Content-based filtering utilizes a user’s past activities to suggest relevant items. Collaborative filtering leverages the behavior of other users with similar interests to generate recommendations. Hybrid methods combine the two approaches for more accurate predictions.
What is one of the best e-commerce recommendation systems on the market?
Luigi’s Box is one of the best e-commerce product recommendation providers, proven by several awards and success stories from users. With their powerful AI-driven technology, they can help you increase customer engagement and drive sales with accurate recommendations. They also offer analytics, search with autocomplete, and personalized product listing pages to support your success.
