If you’ve spent any amount of time online, you’d know that there is a suggestion for everything that you view, save, or purchase. Head over to Amazon or Netflix and click on something that interests you and you will find:
- Customers who bought this item also bought…
- Other movies you may enjoy
Another example is the ‘People you may know’ message you get on Facebook and Instagram. All of these are examples of recommendation system usage.
What is A Recommendation Engine Or System?
A recommendation engine or system is a tool that developers use to foresee your choices in a long list of suggested items.
Recommendation systems generally rely on purchases and page views. However, many services today make recommendations in-the-moment, thanks to Artificial Intelligence (AI), a technology that aims to simulate human intelligence.
Recommendation systems use AI to analyze user interactions and suggest products specific to each user, based on their data. In other words, recommendation engines yield quick and accurate recommendations that are suited to every customer’s preferences and needs. Amazon, for instance, increased its sales by 29% after implementing a recommendation system.
There are primarily three techniques for recommendation systems namely,
- Content-based filtering
- Collaborative filtering
- Knowledge-based system
What is a Use-Case?
Uses cases are a methodology used in system analysis for:
- And Organizing system requirements
Use cases consist of a set of possible interactions between systems and users in a particular environment in relation to a specific goal or objective.
Use cases contain the following elements:
- The actor: This refers to the system user which is an individual or a group of people in the process.
- The goal: This is the outcome, the accomplishment of which completes the process.
- The system: This term describes the process to reach said goal, including essential functional requirements and expected events.
Most Popular Use Cases of AI Recommendation Systems
Now that you have got a general idea about recommendation systems and use cases, here are some of the most well-known use cases of AI recommendation systems:
1. Alternative Product Recommendations
Chances are you’ve tried to pick up a product you wanted, only to find that it was out of stock. However, you probably did not leave. Instead, you found something else, although you may not have purchased it.
In order to keep the customer, companies implement a recommendation system that gives the user alternatives to the product they want. Here’s an example of this:
2. Personalized Content
With so much content out there, it can be difficult, and often overwhelming for a user to make the right decision, which is why they may not buy from you immediately. They might visit your page and others for information, compare prices, etc. In other words, you need to grab them with an incentive.
AI allows you to understand what kind of content you need to present to get the user to take action. If you want to optimize your on-site experience, consider suggesting different recommendations for different audiences, which is what Netflix does. Personalized content is one of the most essential and popular use cases for AI-based recommendation systems.
3. Related Product Recommendations
Related product recommendations are another essential use case of recommendation systems. If a customer makes a purchase, it makes sense to offer them something that goes with that. If the user were to buy a pair of jeans, you could offer them a pair of shoes or a shirt that goes well with it.
Just about every store in existence implements this popular use case. Be sure to look out for the ‘Complete the look’ or ‘You might also like’ sections when you shop online the next time. The added advantage is that the recommendation system can analyze the individual’s search and purchase behavior, providing them with accurate suggestions based on the patterns it detects.
4. Recommendations For The 404 Page
Very few things annoy users more than when they encounter the 404 error on a website. If you want to reduce their annoyance and the chances of losing them to another site, implementing a recommendation system is an excellent idea.
Consider displaying products similar to the ones that the user has viewed on your site. You could also show them your best selling products under different categories. It is vital to ensure your visitors stay on your website to increase your chances of having them revisit you.
5. Product Recommendations For Voice Shoppers
If you haven’t heard, people are increasingly consuming content on audio platforms like Spotify, Apple Music, etc., with brands and content creators coming out with podcasts and repurposed pieces from videos to appeal to an entirely different audience that prefers audio.
Audio has penetrated online shopping as well, considering the success of products like Google Home and Amazon Echo. Implementing a recommendation system to target voice shoppers by keeping them updated on the latest sales, discounts, offers, promotions, news, etc. is an effective way to increase your sales, especially considering people do not mind receiving these updates this way.
6. Personalized Merchandising
Here’s another interesting use case of AI-based recommendation systems – personalized merchandising.
AI enables you to gather data from a customer’s current and past shopping sessions, thus helping you craft attractive offers. Depending on the type of customer or visitor you are dealing with, you can either show them your best sellers, personalized discounts, up-sell offers and so forth. A recommendation system can also help you choose which inventory to show your customers, depending on what they are looking for.
There you have it – these are some of the most well-known and utilized use cases for AI-based recommendation systems. Be sure to watch out for them the next time you open Amazon, Netflix, or any other online store. Other use cases include recommendations of weekly & monthly top products, location-based recommendations, and better product search experience. Leverage them to the fullest to unbox innumerable advantages.
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