A Data Analytics Platform That Can Improve the Book Recommendation Process—What a Novel Idea!

Just as Pandora matches music to the preferences of its listeners, ScoreIt!™ matches books to the preferences of readers.

When readers ask booksellers to suggest their next digital download or print book purchase, they typically receive a wide range of responses. At the Harvard Coop in Cambridge, MA, for example, booksellers rely on their personal knowledge to guide consumers. Yet, even the Coop’s bookselling expert Emi Loveridge concedes that her team “can’t read everything,” despite wanting to. So the art of matching reader preferences to the infinite pool of literary content is confined by human limitations.

At Cambridge’s Porter Square Books, a similar challenge exists. When requests for recommendations are received, Josh Cook’s bookselling team asks readers a series of questions related to the stories that they have liked or rejected, the genres that they prefer and the personal interests they explore in order to direct the selection process.  Asked which writing style elements rank as the primary parameters among inquiring readers, Cook explains, “Every reader is unique and it requires a supremely knowledgeable staff of well-read guides to interpret and respond to their varied and often nuanced requests.”

BooksellersSo what if there were an easier way to recommend books? What if technology could “learn” writing style and promote new works to readers based on the matching of hundreds, if not thousands, of nuanced data points? James Simpson, the Donald P. and Katherine B. Locker Professor of English at Harvard College (and the English Dept. Chair) sees value in technology capable of “calibrating writing style,” within the trade book industry.

Thanks to ScoreIt!™, Inkubate’s writing style analytics platform, a writer’s manuscript can now be analyzed and “calibrated” to reveal the literary features that define its unique “DNA.” By unlocking the unique writing style of each new commercially published book, booksellers can more effectively promote titles to consumers seeking those ineffable literary experiences that make reading so deeply satisfying and memorable.

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