Role of Artificial Intelligence in Recommendation Engine

The field of artificial intelligence (AI) was formally founded in 1956 and since then, it has been getting applied in diverse sectors. Starting from gaming to e-commerce websites, AI is everywhere transforming user experience in the best ways possible. One of the most prominent applications of artificial intelligence is in recommendation engines. With the proliferation of OTT platforms, B2B SaaS businesses, and various digital stores, recommendation engines have become an integral tool for most of the leading business players. In this era of data science and robotics, most of the top-rated recommendation engines are equipped with artificial intelligence. AI enhances the performance of a recommendation engine significantly and provides your customers with the most accurate real-time recommendations possible.

Role of Artificial Intelligence in Recommendation Engine

Let’s have a look at the role of artificial intelligence in a recommendation engine or better to say, how artificial intelligence can transform the whole experience of having a recommendation engine for your business!

  • Precise Recommendations

Every recommendation engine is designed to provide recommendations to the customers. But the difference of one from the other is determined by how precise those recommendations are. An AI-driven recommendation engine implies more precise and real time recommendations to your customers. The ‘Top Picks for You’ section of Netflix or YouTube’s recommended videos are some vivid examples of recommendation engines equipped with AI.

  • Recommendations Based on Customer Visual Preferences

With the help of artificial intelligence, a recommendation engine can focus on the visual preferences of customers while they are using any product or service on a digital store. Visual preferences are the user preferences regarding the physical attributes of digital products. AI-powered recommendation engines are highly user preference-oriented instead of depending only on the product descriptions. As a result, it improves the user experience drastically. A recent survey shows that more than 30% purchases on Amazon comes from product recommendations based on customer visual preferences.

  • Real-time Recommendations

Artificial Intelligence plays a vital role in recommendation engines as it provides instant recommendations to your customers based on their interactions with your digital products or services. This type of recommendations being way faster than the conventional recommendations, take the customer experience to a whole new level.

  • Advanced Search Engine Results

An AI-driven recommendation engine not only focuses on product description but 360 degree overview of customer preferences. As a result, it provides the customers with an enhanced version of search engine for the digital platform where they can get the most apt and tailored search results. For instance, in 2019 Hulu launched an advanced recommendation system equipped with AI which not only provides its customers with real-time recommendations, but also lets them have the experience of personalized search engine results on that platform.

  • Higher Accuracy

Most of the online businesses find it challenging to provide the customers with the content they prefer the most. As customer preferences vary widely based on the demographics and personal choices, a conventional recommendation system may not provide enough satisfactory results. And that’s why artificial intelligence is needed to be incorporated in a recommendation engine in order to come up with the more accurate recommendations. For instance, Amazon AWS machine learning model is capable of recognizing the actors in the video content which customers watch on prime. This in turn provides your customers with more accurate recommendations in the near future.

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