Big Data Drives Book Publication

data show reading preferences, creating books that readers want

Ebooks Reveal Data about Readers

Book publishers have been mining deep data to decide which books to publish. Extensive amounts of data about readers’ likes and dislikes are available, thanks to the ubiquitous tracking of our digital usage, and publishers have been using that data to choose potential best sellers. With ebooks, publishers can ascertain when and where a book is read, how quickly the reader consumes it, and whether and when the reader abandons the book before reaching the end.

Typically, only about 3 percent of the books chosen by acquisitions editors hit the bestseller list, so using data to direct choices is a move in a positive direction.

Data Show Reading Preferences

Jellybooks, a start-up based in London, provides a data-discovery service to publishers. For a fee, Jellybooks will conduct virtual focus groups for publishers to determine how their books will fare once they reach the public forum. Jellybooks gives readers free ebooks that they’ve embedded with JavaScript and asks readers to click on a link as they complete each chapter. That data sent via those links are compiled by Jellybooks to help publishers determine how best to market that book, as well as whether to publish an author’s works again.

Inkitt, a Berlin-based start-up, also takes advantage of reader data, but from an entirely different angle. Inkitt’s website provides a platform where writers can post their novels for a vast reading audience. Its software scrutinizes engagement levels and reading patterns of the website’s visitors and then offers to help publish the best-performing books. Instead of actually publishing the books, Inkitt serves as an agent by pitching the books of its choice to traditional publishers.

Creating Books that Readers Want

Callisto Media, a California-based company, takes the data analysis model even further. This publisher, which Publishers Weekly deemed one of the most swiftly growing independent publishers in 2015 and 2016, first figures out what readers want to read, and then finds someone to write those books.

Thanks to big data, Callisto can figure out quite accurately which type of information people are seeking. It has created proprietary algorithms to research big data and uncover topics of interest to consumers. It then finds experts on those topics and hires them to write corresponding books.

For example, Callisto looks at which Amazon searches for books end in frustration. Based on the topics sought by those fruitless searches, Callisto hires writers to write niche books, such as DIY Fermentation, that cover new topics that have not yet been written about.

Individuals still own the choice of what and how to read, but, as in so many other areas of our lives, big data is steering the way.

Gilan Gertz is Content Marketing Manager at GreenPoint Global, a tri-continental outsourcing company. For the past six years, she has researched and written about a variety of topics for GreenPoint Global's online Publishing, Health-Care, and Education Divisions. Previously, she worked as a psychotherapist in outpatient settings. Gilan has a BA from Barnard College and a Master of Social Work degree from Yeshiva University.

Leave a Reply

Your email address will not be published. Required fields are marked *