Recommendation Systems: A New Way To Target Your Customer
In order to stay competitive, meet customer needs, and maintain market share, businesses traditionally have used surveys, focus groups, tracking and other methods to understand customer needs and trends. New technologies, however, including Recommendation Systems and Deep Learning are now changing the way businesses reach their customer.
A Recommendation System is a filtering system or engine that is used to predict the rating or preference a consumer would use to choose an item. Similar to a search engine, Recommendation Systems are used in online shops, internet music sites, news sites, image and video libraries to help consumers find products or relevant information in real time. By providing information tailored to individual preferences this technology can also help drive sales.
Neuro Linguistic Programming (NLP) is another area that businesses are looking at to better understand their customer. NLP looks at changes in perception and how people make choices. NLP makes it possible to better understand market need and provide solutions to meet consumer demand.
With technological advances in the field of image processing, speech recognition and natural language processing, we have seen an interest in using Deep Learning methods in the area of Recommendation Systems and information retrieval. Three recently added components in the field of Recommendation systems utilize variations of deep learning technology – these include; Content Based Systems, Collaborative Systems, and Hybrid Systems.
Recommendation Systems along with Deep Learning technology has already proven to be a useful tool for businesses to effectively reach their customers and drive sales. With new capabilities continually being added, Recommendation Systems promise to become an increasingly important way to do business.
