Becoming Bestsellers: John Grisham and Danielle Steel (Sample from Chapter 2 of THE BESTSELLER CODE)

This excerpt from a data-driven analysis of bestselling fiction reveals what computer algorithms can teach us about blockbuster books, using literary giants John Grisham and Danielle Steel as case studies. The authors introduce their "bestseller-ometer," a tool that assigns percentages to quantify the importance of topic and theme in achieving commercial success. By framing the publishing landscape—where only about 200 of 55,000 annual novels hit the lists—the text establishes a compelling, numbers-based approach to understanding literary popularity.

The methodology offers a distinctive lens for aspiring writers, publishing professionals, and curious readers fascinated by the mechanics behind hit books. Moving beyond subjective criticism, this data analysis provides concrete insights into the patterns that resonate with massive audiences. For anyone who has ever wondered what separates a bestseller from the rest, this peek into algorithmic literary criticism delivers a provocative new perspective on the art and science of storytelling.