Recommendation systems allow brands to personalize the consumer experience and make suggestions for the items that make the most sense to them. A recommendation engine also lets businesses analyze the customer’s current usage and past browsing history to deliver relevant service and product recommendations.
Several industries use recommendation systems to serve as the best advice for a potential buyer. Recommendation helps businesses suggest the most relevant items to buy and boost the company’s revenue. These suggestions are entirely based on users’ behavior and history, including information on their past preferences.
They can obtain the most valuable insights into the consumers’ tastes allowing businesses to adjust their offerings and personalize them to satisfy users’ needs.
As a result, industries get several benefits from recommendation systems, such as:
Now that we have learned why businesses need to integrate recommendation systems with their platforms, let’s move ahead and unearth a few industries making the most of recommendation systems.
Finding a perfect match for a life partner is quite hard. There are several parameters to assess, such as personal views, education, and from hairstyle to eye color. The location is also a significant parameter as not everyone prefers a long-distance relationship.
The recommendation system identifies and helps users suggest their matching profiles to make this search for perfection easier. The recommender system calculates the probability that two users would like each other based on a range of explicit and implicit features.
The matchmaking algorithm was designed mainly to address the issues and leverage the benefits of online dating. It analyzes the profiles of people using the application nearby, making it possible for the end-user to find the most appropriate matches. With a sound recommendation system, online dating business could solve the problem of the users finding the most suitable match and, in turn, boosts user engagement and boosts business revenue.
Recently, the online gaming industry has rapidly earned revenue of approximately 21.1 billion US dollars in the year 2020. Game enthusiasts can sit at any corner of the world and enjoy playing their favorite games. With evolving technologies, gaming companies have all the information about their players. Hence, implementing a recommendation engine for suggesting the player’s favorite game and in-game products. The recommender system observes the games that people are frequently playing. If a particular group of players is playing the same game genre, there is the probability that they will play another similar game. The recommender tool will analyze and suggest similar games to these people. As a result, the recommender engine has transformed how users discover games. It helps game businesses improve monetization and attract more users to play the game from their list of games.
Streaming Media Services is booming and growing at a faster pace. Personalizing users’ experience is also a central aspect for any streaming media business to witness tremendous growth in the number of subscribers. Integration of the recommender system brings in billions of revenues to streaming businesses. Several OTT platforms must use a recommender system because it helps their users navigate the content catalog effectively. Suggesting the right content at the right time will help boost user engagement and enhance user experience.
Today, the most popular platforms such as Netflix, YouTube, and Spotify are using recommender systems, and this is helping businesses to provide users with better value for what they are paying for. This will make consumer retention and loyalty better than ever.
Metaverse is a virtual world where users, businesses, and digital platforms can exist and interact. It includes everything starting from virtual social to gaming platforms. It is becoming widely popular and making headlines globally. More and more brands and businesses have started to incorporate it into their long-term plans.
The Impedance of AI-based recommendations will help drive all seven technology layers of the metaverse and aid in powering spatial computing, offering scaffold to creators, and supplying novel yet sophisticated forms of storytelling.
Personalized product recommendation helps several eCommerce businesses suggest relevant products to their end-users at multiple touchpoints. Quick and instant suggestions will make every user feel valued and give them a personalized shopping experience.
Integrating a recommender system into eCommerce business sets online stores apart from their competitors and brings more sales. Recommendations help the eCommerce industry offer a personalized shopping experience to the end-user and thus witness a rapid boost in user engagement and revenue flow.
Alie is an AI-powered recommendation engine that easily integrates with your website or application and provides real-time suggestions to the end-users. It helps businesses provide a personalized experience by recommending precise real-time recommendations. It has API-led architecture that makes it flexible enough to be used across several domains. Start a 14-days free trial to experience how Alie can help your business grow and retain maximum users.
Written by: Ankit Jena
Ankit is Content Writer for Muvi’s Marketing unit. He is a passionate writer with 5+ Years of Experience in Content Creation And Development. In his past time, he likes to dance, play football and google various things to quench his thirst for knowledge.
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