There’s a high possibility that you’ve already been to a site which has a product recommendation engine installed. In fact, if you have already tried purchasing something from an online retailer or have participated in an auction on the web, then you might have actually seen these engines in action.
When you visit an online storefront, you might have noticed a small section on the page or a sidebar that contains recommended products and featured items. You might have also noticed that the items being featured are related to products that you might have searched about before or have bought from the site. This is all the doing of the product recommendation engine.
What Is A Product Recommendation Engine?
Product recommendation engines are platforms that work by providing predictions on user preferences when it comes to a certain product, service, or network. These engines actually belong to a subclass of information filtering systems that consider all the items on a database and filter it, so that only those relevant to your interests or user class are displayed.
Product recommendation engines utilize characteristics either from the item or from the social environment to make and display these predictions.
The Three Approaches of Product Recommendation Engines
Product recommendation engines can be implemented by collaborative filtering, content-based filtering, or with the use of hybrid recommender systems.
Collaborative filtering gathers data on users’ activities, behavior, and preferences from a larger pool of users. This information is then fed into a platform which segregates these interests into user channels, each having certain characteristic likes and dislikes. So when a user visits the site, he or she will be assigned a certain user profile, and recommendations stemming from similar interests from the assigned channel will be displayed.
On the other hand, content-based filtering utilizes algorithms that take into consideration only the user’s previous browsing history, activities, and preferences. The system will then make recommendations from the previous items that the user liked or purchased previously.
Lastly, hybrid recommender systems are actually a combination of collaborative filtering and content-based filtering platforms. These systems are generally more effective and more accurate when it comes to providing recommendations to users.
Where are Product Recommendation Engines Used?
Most online stores nowadays employ product recommendation engines. One of the most prominent is Amazon. After several visits or purchases on the site, you will notice that there’s a portion of the page that will present to you “items to consider,” “related items” to those you previously viewed or purchased, “product recommendations” based on your browsing history, among others. In order to provide you with these lists of related goods, Amazon pulled your previous data, behavior on the site, and earlier purchases, and used a product recommendation engine to generate all of these lists.
Entertainment service providers and music streaming sites also make use of these systems to provide related content and media to users. Social networks also use these engines to serve ads, as well as to let users connect with others that they might know in their networks. Online databases, review sites, and blogs also make use of product recommendation engines.
Advantages of Using Product Recommendation Engines
Product recommendation engines provide a lot of benefits, not only to those behind the site, but also to the site visitors. Online retailers can expect to see an increase in conversion and sales, because more of their products and goods are being shown and displayed to the customer.
Entertainment providers can also expect more media to be streamed, as users will find more related content that they are interested in to purchase or access.
Because of product recommendation engines, site visitors will be able to leave with a better site experience overall because of the convenience that they bring. For example, a user might have been looking for the item that the online retailer is recommending. Users will be able to access related articles and reviews, based on the current one they’re reading, saving time and making more content accessible.
Image: 4-tell.com, barilliance.com
yewande December 14, 2012 at 1:40 am
really helpful thank-you for sharing this, this are some of the things we see on big company websites but dont know how useful they are.
Anurag Pandey March 26, 2012 at 2:47 am
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Sara March 24, 2012 at 8:50 am
Nice article, Ruben.It’s really interesting the way that hybrid recommender systems are working and
very beneficial for both sides.Clients are getting all the useful information-recommendations according on their need and preferences and the company more sales.Pretty fair.Thanks for posting.
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neojit March 23, 2012 at 8:34 pm
Product recommendation is really great for achieving more and more clients with on their Favorites. I have noticed these many times but dont know deeply. Thanks for the article Ruben Corbo
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Paul March 23, 2012 at 4:21 am
I would suggest Item-based collaborative filtering as the best recommendation technique in terms of recommendation
quality, scalability, performance, and learning capability.This is benefitial to both consumers and businesses. Consumers profit by finding new interesting products and businesses ,thereby increasing the sales.
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sam March 22, 2012 at 4:14 pm
really ,product recommendation engines are or great use… they help a lot in product promotion
Bishwajeet March 22, 2012 at 10:18 am
Best product recommendation engine is of Amazon and its quite amazing to see how they store your cookies and then show you the products that you will be most likely to buy from them.
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Alex Sim March 22, 2012 at 9:19 am
Sounds familiar. Now that you mentioned it in this post, I’d been to sites that employ such platform without knowing the engines behind it. Kind of remind me of the future search algorithms that will evolve, with social media and personal data integration.
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abhinav March 22, 2012 at 2:24 am
Really product recommendation engine are great. Its very helpful for improving selling for online products and services. Thank you so much for info.
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Nikoya March 22, 2012 at 12:51 am
Very informative . I have always noticed this feature around, but its always great to learn the overview of what the technology is doing as a blogger!
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Gracie March 22, 2012 at 12:32 am
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ben March 21, 2012 at 10:06 pm
This is the first time I’ve heard about this product recommendation engine. I realized that I’ve been going to sites with this tool without my knowledge about this. Thanks for sharing this info Ruben!
Julie March 21, 2012 at 7:06 pm
Wow! I haven’t heard about product recommendation engines before, but they seems to be a genial tool for online marketing, I think I1m going to give it a try as soon as possible! Thanks for the useful information!
Morgan from Sociable Boost March 21, 2012 at 5:45 pm
Interesting, Ruben! I had never considered this route, but for people with products, this can definitely be useful.
Thanks for the tip!
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Jeremy from Modest Money March 21, 2012 at 2:58 pm
Product recommendation engines are great. It is basically just up-selling related products that there is a good chance they may be interested in as well. I’ve set this up on websites in the past and it really did help conversion rates. It not only gives retailers a chance to promote similar products, but it can also be used to push accessories or products that work in conjunction to the product they are viewing.
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