Kadaxis provides publishers and authors with tools to intelligently connect with a book's audience. Use the latest machine learning technology to increase visibility of your titles online, and to help more readers discover your books. Publishers, for more information click here.
Find keywords customers actually use
Adding effective keywords to a book's metadata could be one of the highest return marketing activities for a book. Find out why, here.
The most effective keywords are closely matched to the words customers type into a search box. These words are often different to the terms a marketer produces, or the words found in a book's text (other book marketing experts agree). For example, more customers search for books using keywords like: "sad story", "bad guys", "real life" or "ya dystopian novel" than 'expert' keywords such as "character driven storyline" and "compelling writing style", or BISAC derived phrases like "fantasy contemporary".
Audience Driven Keywords
Our keyword system analyses book audience data to generate highly relevant keywords for a book, using the audience's own language. No need to distribute your book assets just to find keywords. See an example of keywords generated for 'All the Light We Cannot See' by Anthony Doerr:
Integrate our keyword APIs directly into your keyword system, or query keywords through our online web interface. We offer keyword research by book, keyword search by BISAC, similar keywords, keyword validation (for category relevance and customer user).
Book Discovery For Readers By Readers
Most book search and recommendation engines use the same old metadata or purchase history to try to direct customers to a relevant book. Our approach is different. We connect customers to books using the words and concepts they naturally use when thinking about a book or genre.
Our systems crawl the internet, reading conversations about books by real people, from blogs, review sites, social media and other sources. The most important information about readers' sentiment and their perspective about books is extracted and processed by our intelligent agents, to uncover unique insights about books and connections between them.
Book Recommendations by Human Expression
Because we use reader data and sentiment, our book recommendations are more closely aligned to the matches a human would come up with. Book comparisons based on reader's experience are more natural than comps based on artificial insights contrived from the book's text or buying behavior. Below is an example set of recommendations for "The Perks of Being a Wallflower" by "Stephen Chbosky" generated by our system, with a similarity percentage score.
Let customers search and browse in their own way
Most book search engines limit customers' search to only title, author and book category. We empower customers to search or browse for books using words that naturally come to mind, leading to more customers finding books they might buy.
Compare these searches on our bookdiscovery.co site, with the results from other book sites:
• plot twists
• new yorkers
• zombie apocalypse
• sad story
• amish life
• sirius black
• gluten free
• healthier life
• bad guys
Integrate with Kadaxis search and recommendation APIs, or generate custom feeds for your catalog.
Intelligent BISAC Categorization
The right BISAC categories help physical and online retailers position a book for the most appropriate audience. Categories are a key component for physical and online book discovery, enabling customers to browse books by subject and genre.
Choosing the best BISAC category for a title can be difficult and time consuming. In many cases the chosen categories are inconsistent across editors and publishers. Kadaxis systems analyze the text of a book to not only determine the correct BISAC categories in seconds, but also the percentage of content attributed to each category across the book.
Integrate Kadaxis' category classification API into your existing workflow, or generate custom BISAC feeds for your catalog.
Go Deeper Than BISAC with topics
Kadaxis topic analysis system breaks down a book into a topic hierarchy that gives editors and readers an astonishingly deep insight into a book's content, at a glance. This data has been used to position books by marketers and to aid customers in the book discovery process.
Integrate with Kadaxis book topic APIs or generate custom feeds to facilitate book discovery and positioning.
Editorial Marketability Assessment
Compare key writing metrics for a manuscript or published book against books that have previously sold well. Highlight editorial changes that may increase a book's accessibility.
Integrate with the Kadaxis marketability assessment API to generate writing metric scores.