The myriad of sophisticated data analysis techniques that are widely available today is changing the landscape of every industry, including the publishing industry. Gone are the days when a work’s potential to become a bestseller would be judged largely on the basis of an editor’s knowledge and experience.
One startup, Inkitt (1), is taking advantage of data analysis tools to bridge the worlds of online publishing and print publishing. The company, co-founded by Ali Albazaz and Linda Gavin, purports to predict future bestsellers using an artificially intelligent algorithm that analyzes Inkitt users’ reading habits. Albazas and Gavin were inspired by how Fifty Shades of Grey author E.L. James used online publishing to get feedback from her readers. The ultimate goal of Inkitt’s co-founders is to develop a large category of books that are guaranteed bestsellers. They believe in the power of the printed word and want to use their data analysis techniques to help print publishers select which books to work with.
If successful, Inkitt’s work will largely eliminate the need for publishers to wait to determine if a book actually does perform on the mass print market as expected. Now a book’s potential can be judged based on data analysis metrics that are almost immediately available. In the past, a book’s performance would be measured by a metric such as quantity of books sold, which would take a long time to gather the relevant information. Now, via Inkitt’s work, publishers quickly have access to more specific data, such as how fast a book is read on average, how likely a reader is to complete the book and its Net Promoter Score, or how likely the book is to be recommended to others.
In a post for Media Medusa (2), author Nancy Basile reviews Inkitt and the advantages of its data analysis techniques over traditional publishing. She paints a picture of a publisher’s perspective before the impact of data analysis in the field. A publisher, motivated to make money, would do so by choosing to work with authors who already had a successful track history of producing bestsellers. Otherwise, he or she would take a chance on an author he or she knew personally. This means that talented new authors without any publishing history or connections would often be overlooked, to the detriment of both the publishing industry and the new authors.
If you are a writer on Inkitt, you can upload your work to the site and receive feedback from readers. Books that the data analysis algorithm marks as particularly engaging to readers are promoted by Inkitt, first in e-book form. If the book continues performing well, Inkitt will help you land a lucrative publishing deal with an agent. In this way, Inkitt hopes to be as unbiased as possible when selecting books to promote.
Inkitt has already proven its ability to succeed in the new world of data-driven publishing. So far, this world has mostly been inhabited by giants like Amazon, which provides a self-publishing platform called Kindle Direct that is driven by reader upvotes. Jonathon Sturgeon of Flavorwire (3) reported on Inkitt’s first major success: the respected and influential science fiction publisher Tor Books picked up an Inkitt novel for publication in 2017. The novel, Bright Star, was written by contributor Erin Swan as a young adult fiction contest entry. Sturgeon cautions that it remains to be seen whether Inkett’s success with Swan’s work is a function of its data analysis or of the power of crowd-sourced online publication. Still, it is captivating to think that there could be a way to nearly guarantee that a talented new author’s work will be seen by the world.