Gain insight into the most talked about topics related to AI and their Marketability
Be it any product or service, before making any purchase, customers generally tend to ask friends for their recommendations. And when it comes to buying books online, it’s an obvious thing for customers to research and compare contents. When books are available online, it is a typical fashion for readers to make their purchase decision after reading reviews on the Internet too.
Though this may be a common practice, what actually works behind the scenes to serve such recommendations online is a book recommendation engine.
In this blog, we will take you through how a book recommendation engine can help your customers get the right one for them, thereby increasing your sales.
To begin with it, you need to consider certain categories that your book recommendation engine would consider to make appropriate recommendations.
So, let’s have a look at them without further ado:
Remember the time when an online bookstore suggested you a list of books written by an author when you were looking for a particular book written by the same? This is exactly the case of content-based recommendation. Books, in hardback, paperback or e-format, are recommended based on the item description that includes the name of the author.
While setting up your own online bookstore app, you can train your recommendation engine to recommend users to read other books composed by the same author.
Just like the previous category that we just talked about, “genre” also happens to be used in a content-based recommendation system. When readers explore books virtually, genre is one parameter that they generally tend to consider. For example, they might look for novels or “non-fiction” books.
When integrated with a recommender system, your online bookstore website will identify and segregate books as per their genres and recommend those to the visitors.
Bestsellers or New Releases
An AI-based recommendation system will process the stored data, filter out irrelevant ones and make recommendations based on the interest of the user. It can then filter out data as per your required categories. In most cases, avid readers are keen to look for the top selling books or latest releases. Training your recommender system for filtering “Bestsellers” books will do the job for you here.
When you have a bookstore online, readers across all age groups happen to explore your ebook store website. Accordingly, you will have customers who look for books of a specific price range. Of-course, selecting books that are displayed on the screen as per the desired price range always helps in saving time and effort. Moreover, this enhances buying experience too.
Ratings are not about taking away readers’ choices, neither are they about forcing books to stop pushing boundaries. When it comes to picking books, ratings and reviews from readers having similar reading preferences can get your visitors some insight as well as encouragement to give the books a read.
You can have an artificial-intelligence based recommendation engine integrated with your ebook store and train it to filter out lists of books as per their ratings and reviews.
Basically, your visitors will have a brief idea about how the content of the book is before they pay for it.
With a powerful recommendation system at your disposal, you not only enhance the buying behavior of your visitors, but also increase your sales, hence, boost your revenue.
Alie, an AI-powered recommendation engine can personalize user experience for your online bookstore app.
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