Soon, an author who is faced with the challenge of submitting his publishing proposal on a specific publisher’s website will be redirected to a dedicated landing page, where he will “upload” the manuscript he wrote or a fragment thereof. In a fraction of a second, the algorithms will determine the level of matching the song to the publisher’s offer.
A low adjustment of the publishing offer to the profile of a specific publisher will not prevent the author from publishing the book. Its content will be compared to other works from the database of publishing houses operating on the market. With the consent of the author, the work will also be placed in the so-called “Showroomie” (OpenBooks), where it can be discovered by literary agents or other publishers.
The entire fitting process is simplified as follows:
>> We collect and analyze data
– we have books considered the best in our database, according to readers’ ratings on literary websites
– we know the offers of all publishing houses operating in our country
– we have sales data, including derived from Nielsen
– we have lists of the best and worst selling books, obtained from both publishers and bookstores
– we have data on library loans
>> We analyze the content sent by the authors of the books
>> We create “maps” of all books in electronic form, specifying 65 different parameters of the work
>> We are looking for common features
>> We compare
>> We present the results and the level of matching as well as individual parameters in the form of a report
>>BookScout AI selects promising titles, determines to which category, series, target group the manuscript is directed and matches the publisher’s profile.
