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The Benefits of AI Recommender Systems

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The Benefits of AI Recommenders


Why are Recommender Engines important?

Artificial Intelligence (AI) is a term that many have heard of, but few understand its purpose and applications. While people tend to associate AI with robots and science fiction, it is already integrated into our daily lives. Recommender systems, which more than half of online consumers rely on for product recommendations, are essential for online commerce and serve as a prime example of AI in action. AI has been present for 50+ years and has various applications, with recommender systems as a crucial one.

If you have missed our previous article about AI Recommenders, their different types and how they work, please check it out here.

Whether you want to learn more about machine learning or how our future will be affected by AI recommendations, we've compiled a list of significant benefits of recommender systems.

 

The global recommendation engine market size was valued at USD 1.77 billion in 2020 and is expected to expand at a compound annual growth rate (CAGR) of 33.0% from 2021 to 2028 *

*Grand View Research

 


The Benefits of AI Recommender Systems

AI Recommenders have endless benefits that we have compiled into five major categories:

1- Improve user experience by delivering relevant content

AI Recommenders can enhance user experiences by providing tailored product recommendations based on a customer's browsing history and real-time site usage. By demonstrating that the platform values and understands the customer, personalized recommendations can build stronger relationships with them, increasing satisfaction and retention.

In addition, delivering relevant content can help form strong habits and influence usage patterns in customers, reducing the time spent searching for desired products and increasing the likelihood of purchase. Analyzing customers' browsing habits and using the information to provide more accurate recommendations in real time can further improve the quality of service provided.


2- Compile data and better evaluate user preferences for specific targeting

AI Recommenders can help businesses by analyzing and interpreting social interactions on their website, gaining a better understanding of the platform's value to customers. By evaluating preferences and purchasing patterns of users through specific social networks, businesses can target specific demographics and gain insights into the real needs of their users. Through this analysis of data, AI Recommenders can provide more relevant and customized recommendations to users, enhancing the user experience and increasing the likelihood of customer retention.

 

Genetiks AI Recommender helps you proactively recommend relevant products to your customers to improve sales and increase customer loyalty


3- Drive traffic and boost conversions, thus increasing revenue

AI Recommenders can have a significant impact on traffic, retention, sales and revenue. By providing personalized recommendations, businesses can boost key metrics like click-through rates, conversions, and website traffic.

Long-term loyalty can be fostered by showing customers that they are valued as individuals. Satisfied customers are more likely to stay loyal to a service and may recommend it to friends and family, increasing customer retention and profits. AI Recommenders can even suggest products that customers may not have thought of, leading to increased upselling revenue.

Research studies have shown that accurate product recommendations can lead to a 70% increase in sales, which is a pretty significant number.

 

4- Minimize cart abandonment and increase the number of items per order, therefore increasing average order value

When companies have a huge number of products, it becomes hard keeping up with relevant product recommendations. Here comes the role of AI Recommenders, which suggest new products to consumers that they are more likely to buy.

When customers are presented with products that meet their interest and desire, they are far more likely to add those items to their shopping carts and are more willing to spend generously on them. Typically, not only the number of items per cart increases but also the average order value.

AI Recommender engines can also monitor cart abandonment activities and interact with customers to minimize the chance that clients leave without a purchase.

 

impress your customers with AI powered product recommendations

 

5- Provide reports, reduce workload and offer advice

AI Recommenders provide detailed reports that help with product marketing and personalization, as well as add useful information to a customer’s profile to boost his/her shopping experience.

AI Recommenders speed up the pace of work for analysts and researchers and can save as much as 80% of their time when served with the necessary material for further research.
It can even ease the workload on IT staff as it automates the process of using data to create personalized shopping experiences for customers.

On top of that, a recommendation engine provider can offer advice on how best you can use the data collected through your AI Recommender.

If you’re interested in knowing more about how AI Recommenders work, we are more than pleased to help you. You can contact us here to get started.

 

52% of retailers are leveraging AI-driven personalization to deliver personalized product recommendations to their customers *


*Kibo Research

 

By demonstrating a deep understanding of your customers, you can gain their loyalty and trust. Through AI Recommendations and utilizing machine learning expertise, tailored suggestions are offered to meet each customer's unique preferences and interests at every point of interaction.


In various industries such as healthcare, retail, finance and entertainment, recommender systems play a crucial role in promoting customized user experiences, greater customer engagement, and efficient decision-making tools. On major commercial platforms, recommendations contribute to as much as 30% of the revenue. Even a small improvement of 1% in the recommendation quality can result in billions of dollars in profit.

Implementing a product recommendation system is definitely worth all the potential difficulties and challenges. And this statement is supported by all the reasons mentioned above.

 

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