Book Insights Based on Data

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Data is powerful, and can provide a lot of insights. Data also makes it easier to market books. For example, having good metadata makes it easier for readers to find certain books online. Here are some tips for how to use data to your advantage, as well as some awesome examples of what we can learn from data.

Metadata

• “3 Ways You Can Plant Metadata in Your Book Blurb” on Digital Book World
• Bibliocloud
• BookNet Canada
• “Making Metadata Do More: Building Batches in Digital Printing” on Publishing Perspectives
• “Metadata that kills” on Medium
• “Who Uses the Keywords in Metadata?” on Digital Book World

Google Analytics

• “5 Tips to Using Google Analytics to Better Understand Your Business or Blog” on The Every Girl
• “Introducing the Google Analytics Demo Account” on Google Analytics Solutions

Reader Habits Based on Data

• “Analytics and narratology” on MacGuffin
• “Andrew Rhomberg: How and Why We Measure a Book’s Audience” on Digital Book World
• “Big Data (and Big Metaphors) at London Book Fair” on Publishing Perspectives
• “Some Frankfurt Book Fair Notes” on Digital Book World
• “DBW Day Two: an appearance from ‘Data Guy’” on The Bookseller
• “How Does Age Affect Reading?” on Digital Book World
• “Foreign Rights and Reader Analytics” on Digital Book World
• “Men Are from Mars, Women Are from Venus, But What About Readers?” on Digital Book World
• “People who liked The Catcher in the Rye disliked…” on Medium
• “Reader Analytics Is No Silver Bullet” on Digital Book World
• “Reading Fast and Slow – Observing Book Readers in Their Natural Habitat” on Digital Book World
• “Start Strong or Lose Your Readers” on Digital Book World
• “Who’s Afraid of Reader Analytics?” on Digital Book World
• “Will an Open Web Liberate Reading Data?” on Digital Book World

Bestseller Predictions

• “Is It Possible to Predict the Next New York Times Bestseller?” on Digital Book World
• “Data Mining Reveals the Six Basic Emotional Arcs of Storytelling” on MIT Technology Review
• “Data-Driven Publisher Inkitt Signs First Predicted Bestseller with Tor Books” on Digital Book World
• “How Flight Chops Uses Data To Run His Business” on Patreon
• “How to Win the Man Booker Prize” on Digital Book World
• Inkett
• “Inkitt: Using Algorithms to Open Doors for Indie Authors to Become Bestsellers” on BookWorks
• “Machine Learning and Bestseller Prediction: More Than Words Can Say” on Digital Book World
• “Moneyball for Book Publishers: A Detailed Look at How We Read” on New York Times
• “What Books Have the X-Factor? Measuring a Book’s Net Promoter Score” on Digital Book World

Marketing With Data

• “For Publishers Looking to Make Inroads into Big Data, Bundling is Key” on Publisher’s Weekly
• “German publishers are pooling data to compete with Google and Facebook” on DigiDay
• “It’s the Cover, Stupid! Why Publishers Should A/B Test Book Covers” on Digital Book World
• “Data Vs. Instinct – The Publisher’s Dilemma” on Digital Book World

Searchable Content

• UNZ
• “Bookticker Promotes Ebook Deals and Discovery” on Digital Book World
• “Publishing’s Hot App: A Tinder for Intellectual Property” on Hollywood Reporter

Tools

• AlphaSheets
• Data Driven Documents
• Waybackpack
• “How The Telegraph built its new CMS by focusing on simplicity” on Nieman Lab
• Charted
• Plotly
• “The Beginner’s Guide to Excel Macros” on Zapier

Machine Learning

• “Machine Learning Explained” on Scholarly Kitchen
• “Machine Learning: Can a Computer Judge a Book By Its Cover?” on Publishing Perspectives

Examples of Stories Using Data

• American Panorama
• American Panorama on Github
• “Four Ways to Slice Obama’s 2013 Budget Proposal” on New York Times
• Poetry in Motion
• Film Dialogue
• Flowing Data

Projects

• “Computers read 1.8 billion words of fiction to learn how to anticipate human behaviour” on The Stacks
• “Big Media Data: “BBC Genome” Now Live, Data About Every Radio & TV Programme Ever Broadcast by BBC” on InfoDocket
• “When Robots Read Books” on Aeon
• “Human Or Machine: Can You Tell Who Wrote These Poems?” on NPR
• “Neuroscientists create ‘atlas’ showing how words are organised in the brain” on The Guardian
• “The Best Way to Predict Gentrification May Be Through Social Media Data” on Inverse
• “The Most Popular Books in Each State” on Scribd
• “Uber’s Ad-Toting Drones Are Heckling Drivers Stuck in Traffic” on Technology Review
• “We analyzed 4 million data points to see what makes it to the front page of Reddit. Here’s what we learned.” on Datastories
• “What’s the Future Hold for Altmetrics?” on Book Business