Dreaming of Personal Reading Analytics
Big brother knows what you’re reading….if you read ebooks.
It’s not really a secret that big companies like to collect big data on their customers. Free online services aren’t really free — you pay in personal information — and even services that cost money for often ask for an additional payment of information.
Over the holidays, The New York Times ran an article about new and existing services that track user behavior in while reading ebooks (not one to avoid an alarmist headline the NYT headline noted “ebooks are reading you”). Some of the findings the article included were interesting, if not entirely surprising:
The longer a mystery novel is, the more likely readers are to jump to the end to see who done it. People are more likely to finish biographies than business titles, but a chapter of a yoga book is all they need. They speed through romances faster than religious titles, and erotica fastest of all. …
Oyster data shows that readers are 25 percent more likely to finish books that are broken up into shorter chapters. That is an inevitable consequence of people reading in short sessions during the day on an iPhone.
While my initial reaction to reading the story was to toss down my tablet and return to the world of print books as soon as possible, the more I think about, the more excited I am about the idea of collecting my personal reading analytics. And I know I’m not the only one — a recent Book Riot post about strategies for tracking reading has garnered more than 100 comments already.
Right now, it’s pretty easy to keep track of which books I pick up and which books I put down. But wouldn’t it be cool to collect information about the point I quit a book? How quickly I read? Whether chapter length makes a difference in how fast or likely I am to finish a book? Those are data points that are cumbersome to track by hand, but easy to gather and analyze automatically if you are reading electronically.
A really great personal reading analytics program would also be able to pull in information about the books I read — when were they published? What is the author’s gender or race? What genres do I read most or fastest? Combine that with the number of hours spent with audio books and you’d get a fascinating look at an individual’s reading life. Giving up data can be a little scary, but this is one area where I think it would be worth it.
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